[ { "path": ".devcontainer/devcontainer.json", "content": "{\n \"name\": \"nfcore\",\n \"image\": \"nfcore/gitpod:latest\",\n \"remoteUser\": \"gitpod\",\n\n // Configure tool-specific properties.\n \"customizations\": {\n // Configure properties specific to VS Code.\n \"vscode\": {\n // Set *default* container specific settings.json values on container create.\n \"settings\": {\n \"python.defaultInterpreterPath\": \"/opt/conda/bin/python\",\n \"python.linting.enabled\": true,\n \"python.linting.pylintEnabled\": true,\n \"python.formatting.autopep8Path\": \"/opt/conda/bin/autopep8\",\n \"python.formatting.yapfPath\": \"/opt/conda/bin/yapf\",\n \"python.linting.flake8Path\": \"/opt/conda/bin/flake8\",\n \"python.linting.pycodestylePath\": \"/opt/conda/bin/pycodestyle\",\n \"python.linting.pydocstylePath\": \"/opt/conda/bin/pydocstyle\",\n \"python.linting.pylintPath\": \"/opt/conda/bin/pylint\"\n },\n\n // Add the IDs of extensions you want installed when the container is created.\n \"extensions\": [\"ms-python.python\", \"ms-python.vscode-pylance\", \"nf-core.nf-core-extensionpack\"]\n }\n }\n}\n" }, { "path": ".editorconfig", "content": "root = true\n\n[*]\ncharset = utf-8\nend_of_line = lf\ninsert_final_newline = true\ntrim_trailing_whitespace = true\nindent_size = 4\nindent_style = space\n\n[*.{md,yml,yaml,html,css,scss,js}]\nindent_size = 2\n\n# These files are edited and tested upstream in nf-core/modules\n[/modules/nf-core/**]\ncharset = unset\nend_of_line = unset\ninsert_final_newline = unset\ntrim_trailing_whitespace = unset\nindent_style = unset\nindent_size = unset\n\n[/assets/email*]\nindent_size = unset\n\n[/assets/blacklists/GRCh37-blacklist.bed]\ntrim_trailing_whitespace = unset\n" }, { "path": ".gitattributes", "content": "*.config linguist-language=nextflow\n*.nf.test linguist-language=nextflow\nmodules/nf-core/** linguist-generated\nsubworkflows/nf-core/** linguist-generated\n" }, { "path": ".github/.dockstore.yml", "content": "# Dockstore config version, not pipeline version\nversion: 1.2\nworkflows:\n - subclass: nfl\n primaryDescriptorPath: /nextflow.config\n publish: True\n" }, { "path": ".github/CONTRIBUTING.md", "content": "# nf-core/atacseq: Contributing Guidelines\n\nHi there!\nMany thanks for taking an interest in improving nf-core/atacseq.\n\nWe try to manage the required tasks for nf-core/atacseq using GitHub issues, you probably came to this page when creating one.\nPlease use the pre-filled template to save time.\n\nHowever, don't be put off by this template - other more general issues and suggestions are welcome!\nContributions to the code are even more welcome ;)\n\n> If you need help using or modifying nf-core/atacseq then the best place to ask is on the nf-core Slack [#atacseq](https://nfcore.slack.com/channels/atacseq) channel ([join our Slack here](https://nf-co.re/join/slack)).\n\n## Contribution workflow\n\nIf you'd like to write some code for nf-core/atacseq, the standard workflow is as follows:\n\n1. Check that there isn't already an issue about your idea in the [nf-core/atacseq issues](https://github.com/nf-core/atacseq/issues) to avoid duplicating work. If there isn't one already, please create one so that others know you're working on this\n2. [Fork](https://help.github.com/en/github/getting-started-with-github/fork-a-repo) the [nf-core/atacseq repository](https://github.com/nf-core/atacseq) to your GitHub account\n3. Make the necessary changes / additions within your forked repository following [Pipeline conventions](#pipeline-contribution-conventions)\n4. Use `nf-core schema build` and add any new parameters to the pipeline JSON schema (requires [nf-core tools](https://github.com/nf-core/tools) >= 1.10).\n5. Submit a Pull Request against the `dev` branch and wait for the code to be reviewed and merged\n\nIf you're not used to this workflow with git, you can start with some [docs from GitHub](https://help.github.com/en/github/collaborating-with-issues-and-pull-requests) or even their [excellent `git` resources](https://try.github.io/).\n\n## Tests\n\nWhen you create a pull request with changes, [GitHub Actions](https://github.com/features/actions) will run automatic tests.\nTypically, pull-requests are only fully reviewed when these tests are passing, though of course we can help out before then.\n\nThere are typically two types of tests that run:\n\n### Lint tests\n\n`nf-core` has a [set of guidelines](https://nf-co.re/developers/guidelines) which all pipelines must adhere to.\nTo enforce these and ensure that all pipelines stay in sync, we have developed a helper tool which runs checks on the pipeline code. This is in the [nf-core/tools repository](https://github.com/nf-core/tools) and once installed can be run locally with the `nf-core lint ` command.\n\nIf any failures or warnings are encountered, please follow the listed URL for more documentation.\n\n### Pipeline tests\n\nEach `nf-core` pipeline should be set up with a minimal set of test-data.\n`GitHub Actions` then runs the pipeline on this data to ensure that it exits successfully.\nIf there are any failures then the automated tests fail.\nThese tests are run both with the latest available version of `Nextflow` and also the minimum required version that is stated in the pipeline code.\n\n## Patch\n\n:warning: Only in the unlikely and regretful event of a release happening with a bug.\n\n- On your own fork, make a new branch `patch` based on `upstream/master`.\n- Fix the bug, and bump version (X.Y.Z+1).\n- A PR should be made on `master` from patch to directly this particular bug.\n\n## Getting help\n\nFor further information/help, please consult the [nf-core/atacseq documentation](https://nf-co.re/atacseq/usage) and don't hesitate to get in touch on the nf-core Slack [#atacseq](https://nfcore.slack.com/channels/atacseq) channel ([join our Slack here](https://nf-co.re/join/slack)).\n\n## Pipeline contribution conventions\n\nTo make the nf-core/atacseq code and processing logic more understandable for new contributors and to ensure quality, we semi-standardise the way the code and other contributions are written.\n\n### Adding a new step\n\nIf you wish to contribute a new step, please use the following coding standards:\n\n1. Define the corresponding input channel into your new process from the expected previous process channel\n2. Write the process block (see below).\n3. Define the output channel if needed (see below).\n4. Add any new parameters to `nextflow.config` with a default (see below).\n5. Add any new parameters to `nextflow_schema.json` with help text (via the `nf-core schema build` tool).\n6. Add sanity checks and validation for all relevant parameters.\n7. Perform local tests to validate that the new code works as expected.\n8. If applicable, add a new test command in `.github/workflow/ci.yml`.\n9. Update MultiQC config `assets/multiqc_config.yml` so relevant suffixes, file name clean up and module plots are in the appropriate order. If applicable, add a [MultiQC](https://https://multiqc.info/) module.\n10. Add a description of the output files and if relevant any appropriate images from the MultiQC report to `docs/output.md`.\n\n### Default values\n\nParameters should be initialised / defined with default values in `nextflow.config` under the `params` scope.\n\nOnce there, use `nf-core schema build` to add to `nextflow_schema.json`.\n\n### Default processes resource requirements\n\nSensible defaults for process resource requirements (CPUs / memory / time) for a process should be defined in `conf/base.config`. These should generally be specified generic with `withLabel:` selectors so they can be shared across multiple processes/steps of the pipeline. A nf-core standard set of labels that should be followed where possible can be seen in the [nf-core pipeline template](https://github.com/nf-core/tools/blob/master/nf_core/pipeline-template/conf/base.config), which has the default process as a single core-process, and then different levels of multi-core configurations for increasingly large memory requirements defined with standardised labels.\n\nThe process resources can be passed on to the tool dynamically within the process with the `${task.cpu}` and `${task.memory}` variables in the `script:` block.\n\n### Naming schemes\n\nPlease use the following naming schemes, to make it easy to understand what is going where.\n\n- initial process channel: `ch_output_from_`\n- intermediate and terminal channels: `ch__for_`\n\n### Nextflow version bumping\n\nIf you are using a new feature from core Nextflow, you may bump the minimum required version of nextflow in the pipeline with: `nf-core bump-version --nextflow . [min-nf-version]`\n\n### Images and figures\n\nFor overview images and other documents we follow the nf-core [style guidelines and examples](https://nf-co.re/developers/design_guidelines).\n\n## GitHub Codespaces\n\nThis repo includes a devcontainer configuration which will create a GitHub Codespaces for Nextflow development! This is an online developer environment that runs in your browser, complete with VSCode and a terminal.\n\nTo get started:\n\n- Open the repo in [Codespaces](https://github.com/nf-core/atacseq/codespaces)\n- Tools installed\n - nf-core\n - Nextflow\n\nDevcontainer specs:\n\n- [DevContainer config](.devcontainer/devcontainer.json)\n" }, { "path": ".github/ISSUE_TEMPLATE/bug_report.yml", "content": "name: Bug report\ndescription: Report something that is broken or incorrect\nlabels: bug\nbody:\n - type: markdown\n attributes:\n value: |\n Before you post this issue, please check the documentation:\n\n - [nf-core website: troubleshooting](https://nf-co.re/usage/troubleshooting)\n - [nf-core/atacseq pipeline documentation](https://nf-co.re/atacseq/usage)\n\n - type: textarea\n id: description\n attributes:\n label: Description of the bug\n description: A clear and concise description of what the bug is.\n validations:\n required: true\n\n - type: textarea\n id: command_used\n attributes:\n label: Command used and terminal output\n description: Steps to reproduce the behaviour. Please paste the command you used to launch the pipeline and the output from your terminal.\n render: console\n placeholder: |\n $ nextflow run ...\n\n Some output where something broke\n\n - type: textarea\n id: files\n attributes:\n label: Relevant files\n description: |\n Please drag and drop the relevant files here. Create a `.zip` archive if the extension is not allowed.\n Your verbose log file `.nextflow.log` is often useful _(this is a hidden file in the directory where you launched the pipeline)_ as well as custom Nextflow configuration files.\n\n - type: textarea\n id: system\n attributes:\n label: System information\n description: |\n * Nextflow version _(eg. 23.04.0)_\n * Hardware _(eg. HPC, Desktop, Cloud)_\n * Executor _(eg. slurm, local, awsbatch)_\n * Container engine: _(e.g. Docker, Singularity, Conda, Podman, Shifter, Charliecloud, or Apptainer)_\n * OS _(eg. CentOS Linux, macOS, Linux Mint)_\n * Version of nf-core/atacseq _(eg. 1.1, 1.5, 1.8.2)_\n" }, { "path": ".github/ISSUE_TEMPLATE/config.yml", "content": "contact_links:\n - name: Join nf-core\n url: https://nf-co.re/join\n about: Please join the nf-core community here\n - name: \"Slack #atacseq channel\"\n url: https://nfcore.slack.com/channels/atacseq\n about: Discussion about the nf-core/atacseq pipeline\n" }, { "path": ".github/ISSUE_TEMPLATE/feature_request.yml", "content": "name: Feature request\ndescription: Suggest an idea for the nf-core/atacseq pipeline\nlabels: enhancement\nbody:\n - type: textarea\n id: description\n attributes:\n label: Description of feature\n description: Please describe your suggestion for a new feature. It might help to describe a problem or use case, plus any alternatives that you have considered.\n validations:\n required: true\n" }, { "path": ".github/PULL_REQUEST_TEMPLATE.md", "content": "\n\n## PR checklist\n\n- [ ] This comment contains a description of changes (with reason).\n- [ ] If you've fixed a bug or added code that should be tested, add tests!\n- [ ] If you've added a new tool - have you followed the pipeline conventions in the [contribution docs](https://github.com/nf-core/atacseq/tree/master/.github/CONTRIBUTING.md)\n- [ ] If necessary, also make a PR on the nf-core/atacseq _branch_ on the [nf-core/test-datasets](https://github.com/nf-core/test-datasets) repository.\n- [ ] Make sure your code lints (`nf-core lint`).\n- [ ] Ensure the test suite passes (`nextflow run . -profile test,docker --outdir `).\n- [ ] Usage Documentation in `docs/usage.md` is updated.\n- [ ] Output Documentation in `docs/output.md` is updated.\n- [ ] `CHANGELOG.md` is updated.\n- [ ] `README.md` is updated (including new tool citations and authors/contributors).\n" }, { "path": ".github/workflows/awsfulltest.yml", "content": "name: nf-core AWS full size tests\n# This workflow is triggered on published releases.\n# It can be additionally triggered manually with GitHub actions workflow dispatch button.\n# It runs the -profile 'test_full' on AWS batch\n\non:\n release:\n types: [published]\n workflow_dispatch:\njobs:\n run-tower:\n name: Run AWS full tests\n if: github.repository == 'nf-core/atacseq'\n runs-on: ubuntu-latest\n strategy:\n matrix:\n aligner: [\"bwa\", \"bowtie2\", \"chromap\", \"star\"]\n steps:\n - name: Launch workflow via tower\n uses: seqeralabs/action-tower-launch@v2\n with:\n workspace_id: ${{ secrets.TOWER_WORKSPACE_ID }}\n access_token: ${{ secrets.TOWER_ACCESS_TOKEN }}\n compute_env: ${{ secrets.TOWER_COMPUTE_ENV }}\n revision: ${{ github.sha }}\n workdir: s3://${{ secrets.AWS_S3_BUCKET }}/work/atacseq/work-${{ github.sha }}\n parameters: |\n {\n \"hook_url\": \"${{ secrets.MEGATESTS_ALERTS_SLACK_HOOK_URL }}\",\n \"outdir\": \"s3://${{ secrets.AWS_S3_BUCKET }}/atacseq/results-${{ github.sha }}\",\n \"aligner\": \"${{ matrix.aligner }}\"\n }\n profiles: test_full\n\n - uses: actions/upload-artifact@v3\n with:\n name: Tower debug log file\n path: |\n tower_action_*.log\n tower_action_*.json\n" }, { "path": ".github/workflows/awstest.yml", "content": "name: nf-core AWS test\n# This workflow can be triggered manually with the GitHub actions workflow dispatch button.\n# It runs the -profile 'test' on AWS batch\n\non:\n workflow_dispatch:\njobs:\n run-tower:\n name: Run AWS tests\n if: github.repository == 'nf-core/atacseq'\n runs-on: ubuntu-latest\n steps:\n # Launch workflow using Tower CLI tool action\n - name: Launch workflow via tower\n uses: seqeralabs/action-tower-launch@v2\n with:\n workspace_id: ${{ secrets.TOWER_WORKSPACE_ID }}\n access_token: ${{ secrets.TOWER_ACCESS_TOKEN }}\n compute_env: ${{ secrets.TOWER_COMPUTE_ENV }}\n revision: ${{ github.sha }}\n workdir: s3://${{ secrets.AWS_S3_BUCKET }}/work/atacseq/work-${{ github.sha }}\n parameters: |\n {\n \"outdir\": \"s3://${{ secrets.AWS_S3_BUCKET }}/atacseq/results-test-${{ github.sha }}\"\n }\n profiles: test\n\n - uses: actions/upload-artifact@v3\n with:\n name: Tower debug log file\n path: |\n tower_action_*.log\n tower_action_*.json\n" }, { "path": ".github/workflows/branch.yml", "content": "name: nf-core branch protection\n# This workflow is triggered on PRs to master branch on the repository\n# It fails when someone tries to make a PR against the nf-core `master` branch instead of `dev`\non:\n pull_request_target:\n branches: [master]\n\njobs:\n test:\n runs-on: ubuntu-latest\n steps:\n # PRs to the nf-core repo master branch are only ok if coming from the nf-core repo `dev` or any `patch` branches\n - name: Check PRs\n if: github.repository == 'nf-core/atacseq'\n run: |\n { [[ ${{github.event.pull_request.head.repo.full_name }} == nf-core/atacseq ]] && [[ $GITHUB_HEAD_REF == \"dev\" ]]; } || [[ $GITHUB_HEAD_REF == \"patch\" ]]\n\n # If the above check failed, post a comment on the PR explaining the failure\n # NOTE - this doesn't currently work if the PR is coming from a fork, due to limitations in GitHub actions secrets\n - name: Post PR comment\n if: failure()\n uses: mshick/add-pr-comment@v1\n with:\n message: |\n ## This PR is against the `master` branch :x:\n\n * Do not close this PR\n * Click _Edit_ and change the `base` to `dev`\n * This CI test will remain failed until you push a new commit\n\n ---\n\n Hi @${{ github.event.pull_request.user.login }},\n\n It looks like this pull-request is has been made against the [${{github.event.pull_request.head.repo.full_name }}](https://github.com/${{github.event.pull_request.head.repo.full_name }}) `master` branch.\n The `master` branch on nf-core repositories should always contain code from the latest release.\n Because of this, PRs to `master` are only allowed if they come from the [${{github.event.pull_request.head.repo.full_name }}](https://github.com/${{github.event.pull_request.head.repo.full_name }}) `dev` branch.\n\n You do not need to close this PR, you can change the target branch to `dev` by clicking the _\"Edit\"_ button at the top of this page.\n Note that even after this, the test will continue to show as failing until you push a new commit.\n\n Thanks again for your contribution!\n repo-token: ${{ secrets.GITHUB_TOKEN }}\n allow-repeats: false\n" }, { "path": ".github/workflows/ci.yml", "content": "name: nf-core CI\n# This workflow runs the pipeline with the minimal test dataset to check that it completes without any syntax errors\non:\n push:\n branches:\n - dev\n pull_request:\n release:\n types: [published]\n\nenv:\n NXF_ANSI_LOG: false\n\nconcurrency:\n group: \"${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}\"\n cancel-in-progress: true\n\njobs:\n test:\n name: Run pipeline with test data\n # Only run on push if this is the nf-core dev branch (merged PRs)\n if: \"${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/atacseq') }}\"\n runs-on: ubuntu-latest\n strategy:\n matrix:\n NXF_VER:\n - \"23.04.0\"\n - \"latest-everything\"\n steps:\n - name: Check out pipeline code\n uses: actions/checkout@v3\n\n - name: Install Nextflow\n uses: nf-core/setup-nextflow@v1\n with:\n version: \"${{ matrix.NXF_VER }}\"\n\n - name: Run pipeline with test data\n run: |\n nextflow run ${GITHUB_WORKSPACE} -profile test,docker --outdir ./results\n\n test_controls:\n name: Run pipeline with test data and controls\n # Only run on push if this is the nf-core dev branch (merged PRs)\n if: \"${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/atacseq') }}\"\n runs-on: ubuntu-latest\n steps:\n - name: Check out pipeline code\n uses: actions/checkout@v3\n\n - name: Install Nextflow\n uses: nf-core/setup-nextflow@v1\n\n - name: Run pipeline with test data and controls\n run: |\n nextflow run ${GITHUB_WORKSPACE} -profile test_controls,docker --outdir ./results\n\n parameters:\n name: Test workflow parameters\n if: ${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/atacseq') }}\n runs-on: ubuntu-latest\n strategy:\n matrix:\n parameters:\n - \"--skip_trimming\"\n - \"--skip_merge_replicates\"\n - \"--skip_consensus_peaks\"\n - \"--aligner bowtie2\"\n - \"--aligner chromap\"\n - \"--aligner star\"\n steps:\n - name: Check out pipeline code\n uses: actions/checkout@v2\n\n - name: Install Nextflow\n run: |\n wget -qO- get.nextflow.io | bash\n sudo mv nextflow /usr/local/bin/\n\n - name: Run pipeline with various parameters\n run: |\n nextflow run ${GITHUB_WORKSPACE} -profile test,docker ${{ matrix.parameters }} --outdir ./results\n" }, { "path": ".github/workflows/clean-up.yml", "content": "name: \"Close user-tagged issues and PRs\"\non:\n schedule:\n - cron: \"0 0 * * 0\" # Once a week\n\njobs:\n clean-up:\n runs-on: ubuntu-latest\n permissions:\n issues: write\n pull-requests: write\n steps:\n - uses: actions/stale@v7\n with:\n stale-issue-message: \"This issue has been tagged as awaiting-changes or awaiting-feedback by an nf-core contributor. Remove stale label or add a comment otherwise this issue will be closed in 20 days.\"\n stale-pr-message: \"This PR has been tagged as awaiting-changes or awaiting-feedback by an nf-core contributor. Remove stale label or add a comment if it is still useful.\"\n close-issue-message: \"This issue was closed because it has been tagged as awaiting-changes or awaiting-feedback by an nf-core contributor and then staled for 20 days with no activity.\"\n days-before-stale: 30\n days-before-close: 20\n days-before-pr-close: -1\n any-of-labels: \"awaiting-changes,awaiting-feedback\"\n exempt-issue-labels: \"WIP\"\n exempt-pr-labels: \"WIP\"\n repo-token: \"${{ secrets.GITHUB_TOKEN }}\"\n" }, { "path": ".github/workflows/fix-linting.yml", "content": "name: Fix linting from a comment\non:\n issue_comment:\n types: [created]\n\njobs:\n deploy:\n # Only run if comment is on a PR with the main repo, and if it contains the magic keywords\n if: >\n contains(github.event.comment.html_url, '/pull/') &&\n contains(github.event.comment.body, '@nf-core-bot fix linting') &&\n github.repository == 'nf-core/atacseq'\n runs-on: ubuntu-latest\n steps:\n # Use the @nf-core-bot token to check out so we can push later\n - uses: actions/checkout@v3\n with:\n token: ${{ secrets.nf_core_bot_auth_token }}\n\n # Action runs on the issue comment, so we don't get the PR by default\n # Use the gh cli to check out the PR\n - name: Checkout Pull Request\n run: gh pr checkout ${{ github.event.issue.number }}\n env:\n GITHUB_TOKEN: ${{ secrets.nf_core_bot_auth_token }}\n\n - uses: actions/setup-node@v3\n\n - name: Install Prettier\n run: npm install -g prettier @prettier/plugin-php\n\n # Check that we actually need to fix something\n - name: Run 'prettier --check'\n id: prettier_status\n run: |\n if prettier --check ${GITHUB_WORKSPACE}; then\n echo \"result=pass\" >> $GITHUB_OUTPUT\n else\n echo \"result=fail\" >> $GITHUB_OUTPUT\n fi\n\n - name: Run 'prettier --write'\n if: steps.prettier_status.outputs.result == 'fail'\n run: prettier --write ${GITHUB_WORKSPACE}\n\n - name: Commit & push changes\n if: steps.prettier_status.outputs.result == 'fail'\n run: |\n git config user.email \"core@nf-co.re\"\n git config user.name \"nf-core-bot\"\n git config push.default upstream\n git add .\n git status\n git commit -m \"[automated] Fix linting with Prettier\"\n git push\n" }, { "path": ".github/workflows/linting.yml", "content": "name: nf-core linting\n# This workflow is triggered on pushes and PRs to the repository.\n# It runs the `nf-core lint` and markdown lint tests to ensure\n# that the code meets the nf-core guidelines.\non:\n push:\n branches:\n - dev\n pull_request:\n release:\n types: [published]\n\njobs:\n EditorConfig:\n runs-on: ubuntu-latest\n steps:\n - uses: actions/checkout@v3\n\n - uses: actions/setup-node@v3\n\n - name: Install editorconfig-checker\n run: npm install -g editorconfig-checker\n\n - name: Run ECLint check\n run: editorconfig-checker -exclude README.md $(find .* -type f | grep -v '.git\\|.py\\|.md\\|json\\|yml\\|yaml\\|html\\|css\\|work\\|.nextflow\\|build\\|nf_core.egg-info\\|log.txt\\|Makefile')\n\n Prettier:\n runs-on: ubuntu-latest\n steps:\n - uses: actions/checkout@v3\n\n - uses: actions/setup-node@v3\n\n - name: Install Prettier\n run: npm install -g prettier\n\n - name: Run Prettier --check\n run: prettier --check ${GITHUB_WORKSPACE}\n\n PythonBlack:\n runs-on: ubuntu-latest\n steps:\n - uses: actions/checkout@v3\n\n - name: Check code lints with Black\n uses: psf/black@stable\n\n # If the above check failed, post a comment on the PR explaining the failure\n - name: Post PR comment\n if: failure()\n uses: mshick/add-pr-comment@v1\n with:\n message: |\n ## Python linting (`black`) is failing\n\n To keep the code consistent with lots of contributors, we run automated code consistency checks.\n To fix this CI test, please run:\n\n * Install [`black`](https://black.readthedocs.io/en/stable/): `pip install black`\n * Fix formatting errors in your pipeline: `black .`\n\n Once you push these changes the test should pass, and you can hide this comment :+1:\n\n We highly recommend setting up Black in your code editor so that this formatting is done automatically on save. Ask about it on Slack for help!\n\n Thanks again for your contribution!\n repo-token: ${{ secrets.GITHUB_TOKEN }}\n allow-repeats: false\n\n nf-core:\n runs-on: ubuntu-latest\n steps:\n - name: Check out pipeline code\n uses: actions/checkout@v3\n\n - name: Install Nextflow\n uses: nf-core/setup-nextflow@v1\n\n - uses: actions/setup-python@v4\n with:\n python-version: \"3.8\"\n architecture: \"x64\"\n\n - name: Install dependencies\n run: |\n python -m pip install --upgrade pip\n pip install nf-core\n\n - name: Run nf-core lint\n env:\n GITHUB_COMMENTS_URL: ${{ github.event.pull_request.comments_url }}\n GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}\n GITHUB_PR_COMMIT: ${{ github.event.pull_request.head.sha }}\n run: nf-core -l lint_log.txt lint --dir ${GITHUB_WORKSPACE} --markdown lint_results.md\n\n - name: Save PR number\n if: ${{ always() }}\n run: echo ${{ github.event.pull_request.number }} > PR_number.txt\n\n - name: Upload linting log file artifact\n if: ${{ always() }}\n uses: actions/upload-artifact@v3\n with:\n name: linting-logs\n path: |\n lint_log.txt\n lint_results.md\n PR_number.txt\n" }, { "path": ".github/workflows/linting_comment.yml", "content": "name: nf-core linting comment\n# This workflow is triggered after the linting action is complete\n# It posts an automated comment to the PR, even if the PR is coming from a fork\n\non:\n workflow_run:\n workflows: [\"nf-core linting\"]\n\njobs:\n test:\n runs-on: ubuntu-latest\n steps:\n - name: Download lint results\n uses: dawidd6/action-download-artifact@v2\n with:\n workflow: linting.yml\n workflow_conclusion: completed\n\n - name: Get PR number\n id: pr_number\n run: echo \"pr_number=$(cat linting-logs/PR_number.txt)\" >> $GITHUB_OUTPUT\n\n - name: Post PR comment\n uses: marocchino/sticky-pull-request-comment@v2\n with:\n GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}\n number: ${{ steps.pr_number.outputs.pr_number }}\n path: linting-logs/lint_results.md\n" }, { "path": ".gitignore", "content": ".nextflow*\nwork/\ndata/\nresults/\n.DS_Store\ntesting/\ntesting*\n*.pyc\n" }, { "path": ".gitpod.yml", "content": "image: nfcore/gitpod:latest\ntasks:\n - name: Update Nextflow and setup pre-commit\n command: |\n pre-commit install --install-hooks\n nextflow self-update\n\nvscode:\n extensions: # based on nf-core.nf-core-extensionpack\n - codezombiech.gitignore # Language support for .gitignore files\n # - cssho.vscode-svgviewer # SVG viewer\n - esbenp.prettier-vscode # Markdown/CommonMark linting and style checking for Visual Studio Code\n - eamodio.gitlens # Quickly glimpse into whom, why, and when a line or code block was changed\n - EditorConfig.EditorConfig # override user/workspace settings with settings found in .editorconfig files\n - Gruntfuggly.todo-tree # Display TODO and FIXME in a tree view in the activity bar\n - mechatroner.rainbow-csv # Highlight columns in csv files in different colors\n # - nextflow.nextflow # Nextflow syntax highlighting\n - oderwat.indent-rainbow # Highlight indentation level\n - streetsidesoftware.code-spell-checker # Spelling checker for source code\n" }, { "path": ".nf-core.yml", "content": "repository_type: pipeline\n" }, { "path": ".pre-commit-config.yaml", "content": "repos:\n - repo: https://github.com/pre-commit/mirrors-prettier\n rev: \"v2.7.1\"\n hooks:\n - id: prettier\n" }, { "path": ".prettierignore", "content": "email_template.html\nadaptivecard.json\nslackreport.json\n.nextflow*\nwork/\ndata/\nresults/\n.DS_Store\ntesting/\ntesting*\n*.pyc\nbin/\n" }, { "path": ".prettierrc.yml", "content": "printWidth: 120\n" }, { "path": "CHANGELOG.md", "content": "# nf-core/atacseq: Changelog\n\nThe format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)\nand this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).\n\n## [[2.1.2](https://github.com/nf-core/atacseq/releases/tag/2.1.2)] - 2022-08-07\n\n### Enhancements & fixes\n\n- [[#322](https://github.com/nf-core/atacseq/issues/322)]Remove fasta from required schema parameters so that when launching from tools it is not required.\n- Updates `homer_annotatepeaks` module.\n\n## [[2.1.1](https://github.com/nf-core/atacseq/releases/tag/2.1.1)] - 2022-07-21\n\n- Minor patch release to fix AWS full test.\n\n## [[2.1.0](https://github.com/nf-core/atacseq/releases/tag/2.1.0)] - 2022-07-21\n\n### Credits\n\nSpecial thanks to the following for their contributions to the release:\n\n- [Adam Talbot](https://github.com/adamrtalbot)\n- [Björn Langer](https://github.com/bjlang)\n- [Harshil Patel](https://github.com/drpatelh)\n- [Maxime Garcia](https://github.com/maxulysse)\n- [Rob Syme](https://github.com/robsyme)\n\nThank you to everyone else that has contributed by reporting bugs, enhancements or in any other way, shape or form.\n\n### Enhancements & fixes\n\n- [[#226](https://github.com/nf-core/atacseq/issues/262)] - Add `ataqv_mito_reference` parameter.\n- Optional support of control data analog to nf-core/chipseq.\n- [[#277](https://github.com/nf-core/atacseq/issues/277)] - Fix error when using a gunziped fasta file.\n- [[#286](https://github.com/nf-core/atacseq/issues/286)] - Fix error when no `--mito_name parameter is provided.\n- [[#268](https://github.com/nf-core/atacseq/issues/268)] - Fix error when a bed file is provided using the `--blacklist` option.\n- [[#278](https://github.com/nf-core/atacseq/issues/278)] - Make genome fasta file available when `IGV` process is run.\n- [[#276](https://github.com/nf-core/atacseq/issues/276)] - Bump version 1.3.1 of ataqv to fix enrichment plots rendering.\n- [[#290](https://github.com/nf-core/atacseq/issues/290)] - Fix case-sensitivity issue while sorting bedGraph.\n- [[#295](https://github.com/nf-core/atacseq/issues/295)] - Enable downstream steps for bam files produced from paired-end reads by `chromap` after its upgrade.\n- Updated pipeline template to [nf-core/tools 2.9](https://github.com/nf-core/tools/releases/tag/2.9)\n- Make fasta index available for IGV session.\n- [[nf-core/chipseq#347](https://github.com/nf-core/chipseq/issues/347)] - Add read group tag to bam files processed by bowtie2\n\n### Parameters\n\n| Old parameter | New parameter |\n| ------------- | ------------------------ |\n| | `--with_control` |\n| | `--ataqv_mito_reference` |\n\n> **NB:** Parameter has been **updated** if both old and new parameter information is present.\n> **NB:** Parameter has been **added** if just the new parameter information is present.\n> **NB:** Parameter has been **removed** if parameter information isn't present.\n\n### Software dependencies\n\nNote, since the pipeline is now using Nextflow DSL2, each process will be run with its own [Biocontainer](https://biocontainers.pro/#/registry). This means that on occasion it is entirely possible for the pipeline to be using different versions of the same tool. However, the overall software dependency changes compared to the last release have been listed below for reference.\n\n| Dependency | Old version | New version |\n| ----------------------- | ----------- | ----------- |\n| `ataqv` | 1.3.0 | 1.3.1 |\n| `chromap` | 0.2.1 | 0.2.4 |\n| `multiqc` | 1.13 | 1.14 |\n| `picard` | 2.27.4 | 3.0.0 |\n| `samtools` | 1.15.1 | 1.17 |\n| `ucsc-bedgraphtobigwig` | 377 | 445 |\n\n> **NB:** Dependency has been **updated** if both old and new version information is present.\n> **NB:** Dependency has been **added** if just the new version information is present.\n> **NB:** Dependency has been **removed** if version information isn't present.\n\n## [[2.0](https://github.com/nf-core/atacseq/releases/tag/2.0)] - 2022-11-30\n\n### :warning: Major enhancements\n\n- Samplesheet format has changed from `group,replicate,fastq_1,fastq_2` to `sample,fastq_1,fastq_2,replicate`.\n - This is primarily because we have removed the differential accessibility from the pipeline in favour of using more formal statistical methods downstream with the pipeline results. We kept replicate information as mandatory to merge samples at the replicate level to improve coverage for footprinting analysis.\n- Pipeline has been re-implemented in [Nextflow DSL2](https://www.nextflow.io/docs/latest/dsl2.html)\n- Bump minimum Nextflow version from `19.10.0` -> `21.10.3`\n- Updated pipeline template to [nf-core/tools 2.6](https://github.com/nf-core/tools/releases/tag/2.6)\n- [[#135](https://github.com/nf-core/atacseq/issues/135)] - ERROR: Please check design file header\n- [[#158](https://github.com/nf-core/atacseq/issues/158)] - Problem using hyphens in group names\n- [[#182](https://github.com/nf-core/atacseq/issues/182)] - Update `macs_gsize` in `igenomes.config`, create a new `--read_length` parameter and implement the logic to calculate `--macs_gsize` when the parameter is missing\n- [[#193](https://github.com/nf-core/atacseq/issues/193)] - TSS heatmap inconsistency between ChIPseeker and nf-core ATAC-seq pipeline\n- [[#201](https://github.com/nf-core/atacseq/issues/201)] - Update blacklist bed files.\n- [[#220](https://github.com/nf-core/atacseq/issues/220)] - Move FastQ files for minimal tests to S3\n- [[nf-core/chipseq#160](https://github.com/nf-core/chipseq/issues/160)] - Add `bowtie2` and `star` as available aligners, via the `--aligner` parameter\n- [[nf-core/chipseq#233](https://github.com/nf-core/chipseq/issues/233)] - Add `chromap` to the available aligners\n- Add `--save_unaligned` parameter (only available for `bowtie2` and `star`)\n- Preseq will be skipped by default (see [nf-core/rnaseq#897](https://github.com/nf-core/rnaseq/issues/897))\n- `--deseq2_vst` will be turned on by default\n\n### Parameters\n\n| Old parameter | New parameter |\n| ---------------------- | ------------------ |\n| `--clusterOptions` | |\n| `--conda` | `--enable_conda` |\n| | `--skip_qc` |\n| | `--aligner` |\n| | `--save_unaligned` |\n| | `--bowtie2_index` |\n| | `--chromap_index` |\n| | `--star_index` |\n| `--skip_diff_analysis` | `--skip_deseq2_qc` |\n| `--single_end` | |\n| | `--read_length` |\n\n> **NB:** Parameter has been **updated** if both old and new parameter information is present.\n> **NB:** Parameter has been **added** if just the new parameter information is present.\n> **NB:** Parameter has been **removed** if parameter information isn't present.\n\n### Software dependencies\n\nNote, since the pipeline is now using Nextflow DSL2, each process will be run with its own [Biocontainer](https://biocontainers.pro/#/registry). This means that on occasion it is entirely possible for the pipeline to be using different versions of the same tool. However, the overall software dependency changes compared to the last release have been listed below for reference.\n\n| Dependency | Old version | New version |\n| ----------------------- | ----------- | ----------- |\n| `ataqv` | 1.1.1 | 1.3.0 |\n| `bamtools` | 2.5.1 | 2.5.2 |\n| `bedtools` | 2.29.2 | 2.30.0 |\n| `bioconductor-deseq2` | 1.26.0 | 1.28.0 |\n| `deeptools` | 3.4.3 | 3.5.1 |\n| `multiqc` | 1.9 | 1.13 |\n| `ucsc-bedgraphtobigwig` | 357 | 377 |\n| `samtools` | 1.10 | 1.16.1 |\n| `picard` | 2.23.1 | 2.27.4 |\n| `preseq` | 2.0.3 | 3.1.2 |\n| `pysam` | 0.15.3 | 0.19.0 |\n| `r-base` | 3.6.1 | 4.0.3 |\n| `r-ggplot2` | 3.3.2 | 3.3.3 |\n| `trim-galore` | 0.6.5 | 0.6.7 |\n| `khmer` | - | 3.0.0a3 |\n| `r-optparse` | - | 1.7.1 |\n| `r-tidyr` | - | - |\n| `r-lattice` | - | - |\n| `r-xfun` | - | - |\n| `bioconductor-vsn` | - | - |\n\n> **NB:** Dependency has been **updated** if both old and new version information is present.\n> **NB:** Dependency has been **added** if just the new version information is present.\n> **NB:** Dependency has been **removed** if version information isn't present.\n\n## [1.2.2] - 2022-05-12\n\n- Minor patch release to fix Conda environment and enable DSL1 by default in the `nextflow.config`.\n\n### `Dependencies`\n\n- Update r-base `3.6.2` -> `3.6.3`\n- Update r-xfun `0.15` -> `0.22`\n\n## [1.2.1] - 2020-07-29\n\n- [#118](https://github.com/nf-core/atacseq/issues/118) - Minor patch release to update pipeline schema\n\n## [1.2.0] - 2020-07-02\n\n### `Added`\n\n- [#63](https://github.com/nf-core/atacseq/issues/63) - Added multicore support for Trim Galore!\n- [#75](https://github.com/nf-core/atacseq/issues/75) - Include gene annotation versions in multiqc report\n- [#76](https://github.com/nf-core/atacseq/issues/76) - featureCounts coupled to DESeq2\n- [#79](https://github.com/nf-core/atacseq/issues/79) - Parallelize DESeq2\n- [#80](https://github.com/nf-core/atacseq/pull/80) - Added social preview image\n- [#97](https://github.com/nf-core/atacseq/issues/97) - PBC1, PBC2 from pipeline?\n- [#107](https://github.com/nf-core/atacseq/issues/107) - Add options to change MACS2 parameters\n- [nf-core/chipseq#153](https://github.com/nf-core/chipseq/issues/153) - Add plotHeatmap\n- [nf-core/chipseq#159](https://github.com/nf-core/chipseq/issues/159) - expose bwa mem -T parameter\n- Regenerated screenshots and added collapsible sections for output files in `docs/output.md`\n- Update template to tools `1.9`\n- Replace `set` with `tuple` and `file()` with `path()` in all processes\n- Capitalise process names\n- Parameters:\n - `--bwa_min_score` to set minimum alignment score for BWA MEM\n - `--macs_fdr` to provide FDR threshold for MACS2 peak calling\n - `--macs_pvalue` to provide p-value threshold for MACS2 peak calling\n - `--skip_peak_qc` to skip MACS2 peak QC plot generation\n - `--skip_peak_annotation` to skip annotation of MACS2 and consensus peaks with HOMER\n - `--skip_consensus_peaks` to skip consensus peak generation\n - `--deseq2_vst` to use variance stabilizing transformation (VST) instead of regularized log transformation (rlog) with DESeq2\n - `--publish_dir_mode` to customise method of publishing results to output directory [nf-core/tools#585](https://github.com/nf-core/tools/issues/585)\n\n### `Fixed`\n\n- [#71](https://github.com/nf-core/atacseq/issues/71) - consensus_peaks.mLb.clN.boolean.intersect.plot.pdf not generated\n- [#73](https://github.com/nf-core/atacseq/issues/73) - macs_annotatePeaks.mLb.clN.summary.txt file is not created\n- [#86](https://github.com/nf-core/atacseq/issues/86) - bug in the plot_homer_annotatepeaks.r script\n- [#102](https://github.com/nf-core/atacseq/issues/102) - Incorrect Group ID assigned by featurecounts_deseq2.r\n- [#110](https://github.com/nf-core/atacseq/pull/110) - updated AWS test GitHub actions\n- [#109](https://github.com/nf-core/atacseq/issues/109) - Specify custom gtf but gene bed is not generated from that gtf?\n- [nf-core/chipseq#118](https://github.com/nf-core/chipseq/issues/118) - Running on with SGE\n- [nf-core/chipseq#132](https://github.com/nf-core/chipseq/issues/132) - BigWig Error: sort: cannot create temporary file in '': Read-only file system\n- [nf-core/chipseq#154](https://github.com/nf-core/chipseq/issues/154) - computeMatrix.val.mat.gz files not zipped\n- Make executables in `bin/` compatible with Python 3\n\n### `Dependencies`\n\n- Add bioconductor-biocparallel `1.20.0`\n- Add markdown `3.2.2`\n- Add pigz `2.3.4`\n- Add pygments `2.6.1`\n- Add pymdown-extensions `7.1`\n- Add python `3.7.6`\n- Add r-reshape2 `1.4.4`\n- Add r-tidyr `1.1.0`\n- Update ataqv `1.0.0` -> `1.1.1`\n- Update bedtools `2.27.1` -> `2.29.2`\n- Update bioconductor-deseq2 `1.20.0` -> `1.26.0`\n- Update bioconductor-vsn `3.46.0` -> `3.54.0`\n- Update deeptools `3.2.1` -> `3.4.3`\n- Update fastqc `0.11.8` -> `0.11.9`\n- Update gawk `4.2.1` -> `5.1.0`\n- Update homer `4.9.1` -> `4.11`\n- Update macs2 `2.1.2` -> `2.2.7.1`\n- Update multiqc `1.7` -> `1.8`\n- Update picard `2.19.0` -> `2.23.1`\n- Update pysam `0.15.2` -> `0.15.3`\n- Update r-base `3.4.1` -> `3.6.2`\n- Update r-ggplot2 `3.1.0` -> `3.3.2`\n- Update r-lattice `0.20_35` -> `0.20_41`\n- Update r-optparse `1.6.0` -> `1.6.6`\n- Update r-pheatmap `1.0.10` -> `1.0.12`\n- Update r-scales `1.0.0` -> `1.1.1`\n- Update r-upsetr `1.3.3` -> `1.4.0`\n- Update r-xfun `0.3` -> `0.15`\n- Update samtools `1.9` -> `1.10`\n- Update subread `1.6.4` -> `2.0.1`\n- Update trim-galore `0.5.0` -> `0.6.5`\n- Update ucsc-bedgraphtobigwig `377` -> `357`\n\n## [1.1.0] - 2019-11-05\n\n### `Added`\n\n- [#35](https://github.com/nf-core/atacseq/issues/35) - Add deepTools plotFingerprint\n- [#46](https://github.com/nf-core/atacseq/issues/46) - Missing gene_bed path in igenomes config\n- Merged in TEMPLATE branch for automated syncing\n- Update template to tools `1.7`\n- Add `CITATIONS.md` file\n- Capitalised process names\n- Add parameters:\n - `--seq_center`\n - `--trim_nextseq`\n - `--fingerprint_bins`\n - `--broad_cutoff`\n - `--min_reps_consensus`\n - `--save_macs_pileup`\n - `--skip_diff_analysis`\n - `--skip_*` for skipping QC steps\n\n### `Fixed`\n\n- **Change all parameters from `camelCase` to `snake_case` (see [Deprecated](#deprecated))**\n- [#41](https://github.com/nf-core/atacseq/issues/41) - Docs: Add example plot images\n- [#44](https://github.com/nf-core/atacseq/issues/44) - Output directory missing: macs2/consensus/deseq2\n- [#45](https://github.com/nf-core/atacseq/issues/45) - Wrong x-axis scale for the HOMER: Peak annotation Counts tab plot?\n- [#46](https://github.com/nf-core/atacseq/issues/46) - Stage blacklist file in channel properly\n- [#50](https://github.com/nf-core/atacseq/issues/50) - HOMER number of peaks does not correspond to found MACS2 peaks\n- Fixed bug in UpSetR peak intersection plot\n- IGV now uses relative instead of absolute paths\n- Smaller logo for completion email\n- Renamed all channels to start with `ch_` prefix\n- Increase default resource requirements in `base.config`\n- Increase process-specific requirements based on user-reported failures\n\n### `Dependencies`\n\n- Update Nextflow `0.32.0` -> `19.10.0`\n- Add preseq `2.0.3`\n- Add deeptools `3.2.1`\n- Add r-xfun `0.3`\n- Add gawk `4.2.1`\n\n### `Deprecated`\n\n| Deprecated | Replacement |\n| ---------------------------- | ------------------------- |\n| `--design` | `--input` |\n| `--singleEnd` | `--single_end` |\n| `--saveGenomeIndex` | `--save_reference` |\n| `--skipTrimming` | `--skip_trimming` |\n| `--saveTrimmed` | `--save_trimmed` |\n| `--keepMito` | `--keep_mito` |\n| `--keepDups` | `--keep_dups` |\n| `--keepMultiMap` | `--keep_multi_map` |\n| `--skipMergeReplicates` | `--skip_merge_replicates` |\n| `--saveAlignedIntermediates` | `--save_align_intermeds` |\n| `--narrowPeak` | `--narrow_peak` |\n\n## [1.0.0] - 2019-04-09\n\n### `Added`\n\nInitial release of nf-core/atacseq\nCreated with version 1.1 of the [nf-core](http://nf-co.re/) template.\n" }, { "path": "CITATIONS.md", "content": "# nf-core/atacseq: Citations\n\n## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/)\n\n> Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031.\n\n## [Nextflow](https://pubmed.ncbi.nlm.nih.gov/28398311/)\n\n> Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 28398311.\n\n## Pipeline tools\n\n- [BWA](https://www.ncbi.nlm.nih.gov/pubmed/19451168/)\n\n > Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009 Jul 15;25(14):1754-60. doi: 10.1093/bioinformatics/btp324. Epub 2009 May 18. PubMed PMID: 19451168; PubMed Central PMCID: PMC2705234.\n\n- [BEDTools](https://www.ncbi.nlm.nih.gov/pubmed/20110278/)\n\n > Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010 Mar 15;26(6):841-2. doi: 10.1093/bioinformatics/btq033. Epub 2010 Jan 28. PubMed PMID: 20110278; PubMed Central PMCID: PMC2832824.\n\n- [BamTools](https://www.ncbi.nlm.nih.gov/pubmed/21493652/)\n\n > Barnett DW, Garrison EK, Quinlan AR, Strömberg MP, Marth GT. BamTools: a C++ API and toolkit for analyzing and managing BAM files. Bioinformatics. 2011 Jun 15;27(12):1691-2. doi: 10.1093/bioinformatics/btr174. Epub 2011 Apr 14. PubMed PMID: 21493652; PubMed Central PMCID: PMC3106182.\n\n- [deepTools](https://www.ncbi.nlm.nih.gov/pubmed/27079975/)\n\n > Ramírez F, Ryan DP, Grüning B, Bhardwaj V, Kilpert F, Richter AS, Heyne S, Dündar F, Manke T. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 2016 Jul 8;44(W1):W160-5. doi: 10.1093/nar/gkw257. Epub 2016 Apr 13. PubMed PMID: 27079975; PubMed Central PMCID: PMC4987876.\n\n- [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)\n\n > Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. Available online https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.\n\n- [featureCounts](https://www.ncbi.nlm.nih.gov/pubmed/24227677/)\n\n > Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014 Apr 1;30(7):923-30. doi: 10.1093/bioinformatics/btt656. Epub 2013 Nov 13. PubMed PMID: 24227677.\n\n- [HOMER](https://www.ncbi.nlm.nih.gov/pubmed/20513432/)\n\n > Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010 May 28;38(4):576-89. doi: 10.1016/j.molcel.2010.05.004. PubMed PMID: 20513432; PubMed Central PMCID: PMC2898526.\n\n- [MACS2](https://www.ncbi.nlm.nih.gov/pubmed/18798982/)\n\n > Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9(9):R137. doi: 10.1186/gb-2008-9-9-r137. Epub 2008 Sep 17. PubMed PMID: 18798982; PubMed Central PMCID: PMC2592715.\n\n- [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/)\n\n > Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924.\n\n- [picard-tools](http://broadinstitute.github.io/picard)\n\n- [preseq](https://www.ncbi.nlm.nih.gov/pubmed/23435259/)\n\n > Daley T, Smith AD. Predicting the molecular complexity of sequencing libraries. Nat Methods. 2013 Apr;10(4):325-7. doi: 10.1038/nmeth.2375. Epub 2013 Feb 24. PubMed PMID: 23435259; PubMed Central PMCID: PMC3612374.\n\n- [pysam](https://github.com/pysam-developers/pysam)\n\n- [SAMtools](https://www.ncbi.nlm.nih.gov/pubmed/19505943/)\n\n > Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R; 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009 Aug 15;25(16):2078-9. doi: 10.1093/bioinformatics/btp352. Epub 2009 Jun 8. PubMed PMID: 19505943; PubMed Central PMCID: PMC2723002.\n\n- [Trim Galore!](https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/)\n\n- [UCSC tools](https://www.ncbi.nlm.nih.gov/pubmed/20639541/)\n\n > Kent WJ, Zweig AS, Barber G, Hinrichs AS, Karolchik D. BigWig and BigBed: enabling browsing of large distributed datasets. Bioinformatics. 2010 Sep 1;26(17):2204-7. doi: 10.1093/bioinformatics/btq351. Epub 2010 Jul 17. PubMed PMID: 20639541; PubMed Central PMCID: PMC2922891.\n\n- [ataqv](https://github.com/ParkerLab/ataqv)\n\n## R packages\n\n- [R](https://www.R-project.org/)\n\n > R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.\n\n- [DESeq2](https://www.ncbi.nlm.nih.gov/pubmed/25516281/)\n\n > Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. PubMed PMID: 25516281; PubMed Central PMCID: PMC4302049.\n\n- [UpSetR](https://CRAN.R-project.org/package=UpSetR)\n\n > Nils Gehlenborg (2017). UpSetR: A More Scalable Alternative to Venn and Euler Diagrams for Visualizing Intersecting Sets.\n\n- [ggplot2](https://cran.r-project.org/web/packages/ggplot2/index.html)\n\n > H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.\n\n- [reshape2](http://www.jstatsoft.org/v21/i12/)\n\n > Hadley Wickham (2007). Reshaping Data with the reshape Package. Journal of Statistical Software, 21(12), 1-20.\n\n- [scales](https://CRAN.R-project.org/package=scales)\n\n > Hadley Wickham (2018). scales: Scale Functions for Visualization.\n\n- [pheatmap](https://CRAN.R-project.org/package=pheatmap)\n\n > Raivo Kolde (2018). pheatmap: Pretty Heatmaps.\n\n- [RColorBrewer](https://CRAN.R-project.org/package=RColorBrewer)\n\n > Erich Neuwirth (2014). RColorBrewer: ColorBrewer Palettes.\n\n- [optparse](https://CRAN.R-project.org/package=optparse)\n\n > Trevor L Davis (2018). optparse: Command Line Option Parser.\n\n## Software packaging/containerisation tools\n\n- [Anaconda](https://anaconda.com)\n\n > Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.\n\n- [Bioconda](https://pubmed.ncbi.nlm.nih.gov/29967506/)\n\n > Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018 Jul;15(7):475-476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506.\n\n- [BioContainers](https://pubmed.ncbi.nlm.nih.gov/28379341/)\n\n > da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192. PubMed PMID: 28379341; PubMed Central PMCID: PMC5870671.\n\n- [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241)\n\n > Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239), 2. doi: 10.5555/2600239.2600241.\n\n- [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/)\n\n > Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675.\n" }, { "path": "CODE_OF_CONDUCT.md", "content": "# Code of Conduct at nf-core (v1.0)\n\n## Our Pledge\n\nIn the interest of fostering an open, collaborative, and welcoming environment, we as contributors and maintainers of nf-core, pledge to making participation in our projects and community a harassment-free experience for everyone, regardless of:\n\n- Age\n- Body size\n- Familial status\n- Gender identity and expression\n- Geographical location\n- Level of experience\n- Nationality and national origins\n- Native language\n- Physical and neurological ability\n- Race or ethnicity\n- Religion\n- Sexual identity and orientation\n- Socioeconomic status\n\nPlease note that the list above is alphabetised and is therefore not ranked in any order of preference or importance.\n\n## Preamble\n\n> Note: This Code of Conduct (CoC) has been drafted by the nf-core Safety Officer and been edited after input from members of the nf-core team and others. \"We\", in this document, refers to the Safety Officer and members of the nf-core core team, both of whom are deemed to be members of the nf-core community and are therefore required to abide by this Code of Conduct. This document will amended periodically to keep it up-to-date, and in case of any dispute, the most current version will apply.\n\nAn up-to-date list of members of the nf-core core team can be found [here](https://nf-co.re/about). Our current safety officer is Renuka Kudva.\n\nnf-core is a young and growing community that welcomes contributions from anyone with a shared vision for [Open Science Policies](https://www.fosteropenscience.eu/taxonomy/term/8). Open science policies encompass inclusive behaviours and we strive to build and maintain a safe and inclusive environment for all individuals.\n\nWe have therefore adopted this code of conduct (CoC), which we require all members of our community and attendees in nf-core events to adhere to in all our workspaces at all times. Workspaces include but are not limited to Slack, meetings on Zoom, Jitsi, YouTube live etc.\n\nOur CoC will be strictly enforced and the nf-core team reserve the right to exclude participants who do not comply with our guidelines from our workspaces and future nf-core activities.\n\nWe ask all members of our community to help maintain a supportive and productive workspace and to avoid behaviours that can make individuals feel unsafe or unwelcome. Please help us maintain and uphold this CoC.\n\nQuestions, concerns or ideas on what we can include? Contact safety [at] nf-co [dot] re\n\n## Our Responsibilities\n\nThe safety officer is responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behaviour.\n\nThe safety officer in consultation with the nf-core core team have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.\n\nMembers of the core team or the safety officer who violate the CoC will be required to recuse themselves pending investigation. They will not have access to any reports of the violations and be subject to the same actions as others in violation of the CoC.\n\n## When are where does this Code of Conduct apply?\n\nParticipation in the nf-core community is contingent on following these guidelines in all our workspaces and events. This includes but is not limited to the following listed alphabetically and therefore in no order of preference:\n\n- Communicating with an official project email address.\n- Communicating with community members within the nf-core Slack channel.\n- Participating in hackathons organised by nf-core (both online and in-person events).\n- Participating in collaborative work on GitHub, Google Suite, community calls, mentorship meetings, email correspondence.\n- Participating in workshops, training, and seminar series organised by nf-core (both online and in-person events). This applies to events hosted on web-based platforms such as Zoom, Jitsi, YouTube live etc.\n- Representing nf-core on social media. This includes both official and personal accounts.\n\n## nf-core cares 😊\n\nnf-core's CoC and expectations of respectful behaviours for all participants (including organisers and the nf-core team) include but are not limited to the following (listed in alphabetical order):\n\n- Ask for consent before sharing another community member’s personal information (including photographs) on social media.\n- Be respectful of differing viewpoints and experiences. We are all here to learn from one another and a difference in opinion can present a good learning opportunity.\n- Celebrate your accomplishments at events! (Get creative with your use of emojis 🎉 🥳 💯 🙌 !)\n- Demonstrate empathy towards other community members. (We don’t all have the same amount of time to dedicate to nf-core. If tasks are pending, don’t hesitate to gently remind members of your team. If you are leading a task, ask for help if you feel overwhelmed.)\n- Engage with and enquire after others. (This is especially important given the geographically remote nature of the nf-core community, so let’s do this the best we can)\n- Focus on what is best for the team and the community. (When in doubt, ask)\n- Graciously accept constructive criticism, yet be unafraid to question, deliberate, and learn.\n- Introduce yourself to members of the community. (We’ve all been outsiders and we know that talking to strangers can be hard for some, but remember we’re interested in getting to know you and your visions for open science!)\n- Show appreciation and **provide clear feedback**. (This is especially important because we don’t see each other in person and it can be harder to interpret subtleties. Also remember that not everyone understands a certain language to the same extent as you do, so **be clear in your communications to be kind.**)\n- Take breaks when you feel like you need them.\n- Using welcoming and inclusive language. (Participants are encouraged to display their chosen pronouns on Zoom or in communication on Slack.)\n\n## nf-core frowns on 😕\n\nThe following behaviours from any participants within the nf-core community (including the organisers) will be considered unacceptable under this code of conduct. Engaging or advocating for any of the following could result in expulsion from nf-core workspaces.\n\n- Deliberate intimidation, stalking or following and sustained disruption of communication among participants of the community. This includes hijacking shared screens through actions such as using the annotate tool in conferencing software such as Zoom.\n- “Doxing” i.e. posting (or threatening to post) another person’s personal identifying information online.\n- Spamming or trolling of individuals on social media.\n- Use of sexual or discriminatory imagery, comments, or jokes and unwelcome sexual attention.\n- Verbal and text comments that reinforce social structures of domination related to gender, gender identity and expression, sexual orientation, ability, physical appearance, body size, race, age, religion or work experience.\n\n### Online Trolling\n\nThe majority of nf-core interactions and events are held online. Unfortunately, holding events online comes with the added issue of online trolling. This is unacceptable, reports of such behaviour will be taken very seriously, and perpetrators will be excluded from activities immediately.\n\nAll community members are required to ask members of the group they are working within for explicit consent prior to taking screenshots of individuals during video calls.\n\n## Procedures for Reporting CoC violations\n\nIf someone makes you feel uncomfortable through their behaviours or actions, report it as soon as possible.\n\nYou can reach out to members of the [nf-core core team](https://nf-co.re/about) and they will forward your concerns to the safety officer(s).\n\nIssues directly concerning members of the core team will be dealt with by other members of the core team and the safety manager, and possible conflicts of interest will be taken into account. nf-core is also in discussions about having an ombudsperson, and details will be shared in due course.\n\nAll reports will be handled with utmost discretion and confidentially.\n\n## Attribution and Acknowledgements\n\n- The [Contributor Covenant, version 1.4](http://contributor-covenant.org/version/1/4)\n- The [OpenCon 2017 Code of Conduct](http://www.opencon2017.org/code_of_conduct) (CC BY 4.0 OpenCon organisers, SPARC and Right to Research Coalition)\n- The [eLife innovation sprint 2020 Code of Conduct](https://sprint.elifesciences.org/code-of-conduct/)\n- The [Mozilla Community Participation Guidelines v3.1](https://www.mozilla.org/en-US/about/governance/policies/participation/) (version 3.1, CC BY-SA 3.0 Mozilla)\n\n## Changelog\n\n### v1.0 - March 12th, 2021\n\n- Complete rewrite from original [Contributor Covenant](http://contributor-covenant.org/) CoC.\n" }, { "path": "LICENSE", "content": "MIT License\n\nCopyright (c) Patel H, Langer B, Espinosa-Carrasco J, Syme R\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n" }, { "path": "README.md", "content": "# ![nf-core/atacseq](docs/images/nf-core-atacseq_logo_light.png#gh-light-mode-only) ![nf-core/atacseq](docs/images/nf-core-atacseq_logo_dark.png#gh-dark-mode-only)\n\n[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/atacseq/results)[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.2634132-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.2634132)\n\n[![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A523.04.0-23aa62.svg)](https://www.nextflow.io/)\n[![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000&logo=anaconda)](https://docs.conda.io/en/latest/)\n[![run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?labelColor=000000&logo=docker)](https://www.docker.com/)\n[![run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg?labelColor=000000)](https://sylabs.io/docs/)\n[![Launch on Nextflow Tower](https://img.shields.io/badge/Launch%20%F0%9F%9A%80-Nextflow%20Tower-%234256e7)](https://tower.nf/launch?pipeline=https://github.com/nf-core/atacseq)\n\n[![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23atacseq-4A154B?labelColor=000000&logo=slack)](https://nfcore.slack.com/channels/atacseq)[![Follow on Twitter](http://img.shields.io/badge/twitter-%40nf__core-1DA1F2?labelColor=000000&logo=twitter)](https://twitter.com/nf_core)[![Follow on Mastodon](https://img.shields.io/badge/mastodon-nf__core-6364ff?labelColor=FFFFFF&logo=mastodon)](https://mstdn.science/@nf_core)[![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?labelColor=000000&logo=youtube)](https://www.youtube.com/c/nf-core)\n\n## Introduction\n\n**nfcore/atacseq** is a bioinformatics analysis pipeline used for ATAC-seq data.\n\nThe pipeline is built using [Nextflow](https://www.nextflow.io), a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The [Nextflow DSL2](https://www.nextflow.io/docs/latest/dsl2.html) implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from [nf-core/modules](https://github.com/nf-core/modules) in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!\n\nOn release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources.The results obtained from the full-sized test can be viewed on the [nf-core website](https://nf-co.re/atacseq/results).\n\n## Pipeline summary\n\n![nf-core/atacseq metro map](docs/images/nf-core-atacseq_metro_map_grey.png)\n\n1. Raw read QC ([`FastQC`](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/))\n2. Adapter trimming ([`Trim Galore!`](https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/))\n3. Choice of multiple aligners\n 1.([`BWA`](https://sourceforge.net/projects/bio-bwa/files/))\n 2.([`Chromap`](https://github.com/haowenz/chromap)). **For paired-end reads only working until mapping steps, see [here](https://github.com/nf-core/chipseq/issues/291)**\n 3.([`Bowtie2`](http://bowtie-bio.sourceforge.net/bowtie2/index.shtml))\n 4.([`STAR`](https://github.com/alexdobin/STAR))\n4. Mark duplicates ([`picard`](https://broadinstitute.github.io/picard/))\n5. Merge alignments from multiple libraries of the same sample ([`picard`](https://broadinstitute.github.io/picard/))\n 1. Re-mark duplicates ([`picard`](https://broadinstitute.github.io/picard/))\n 2. Filtering to remove:\n - reads mapping to mitochondrial DNA ([`SAMtools`](https://sourceforge.net/projects/samtools/files/samtools/))\n - reads mapping to blacklisted regions ([`SAMtools`](https://sourceforge.net/projects/samtools/files/samtools/), [`BEDTools`](https://github.com/arq5x/bedtools2/))\n - reads that are marked as duplicates ([`SAMtools`](https://sourceforge.net/projects/samtools/files/samtools/))\n - reads that are not marked as primary alignments ([`SAMtools`](https://sourceforge.net/projects/samtools/files/samtools/))\n - reads that are unmapped ([`SAMtools`](https://sourceforge.net/projects/samtools/files/samtools/))\n - reads that map to multiple locations ([`SAMtools`](https://sourceforge.net/projects/samtools/files/samtools/))\n - reads containing > 4 mismatches ([`BAMTools`](https://github.com/pezmaster31/bamtools))\n - reads that are soft-clipped ([`BAMTools`](https://github.com/pezmaster31/bamtools))\n - reads that have an insert size > 2kb ([`BAMTools`](https://github.com/pezmaster31/bamtools); _paired-end only_)\n - reads that map to different chromosomes ([`Pysam`](http://pysam.readthedocs.io/en/latest/installation.html); _paired-end only_)\n - reads that arent in FR orientation ([`Pysam`](http://pysam.readthedocs.io/en/latest/installation.html); _paired-end only_)\n - reads where only one read of the pair fails the above criteria ([`Pysam`](http://pysam.readthedocs.io/en/latest/installation.html); _paired-end only_)\n 3. Alignment-level QC and estimation of library complexity ([`picard`](https://broadinstitute.github.io/picard/), [`Preseq`](http://smithlabresearch.org/software/preseq/))\n 4. Create normalised bigWig files scaled to 1 million mapped reads ([`BEDTools`](https://github.com/arq5x/bedtools2/), [`bedGraphToBigWig`](http://hgdownload.soe.ucsc.edu/admin/exe/))\n 5. Generate gene-body meta-profile from bigWig files ([`deepTools`](https://deeptools.readthedocs.io/en/develop/content/tools/plotProfile.html))\n 6. Calculate genome-wide enrichment (optionally relative to control) ([`deepTools`](https://deeptools.readthedocs.io/en/develop/content/tools/plotFingerprint.html))\n 7. Call broad/narrow peaks ([`MACS2`](https://github.com/macs3-project/MACS))\n 8. Annotate peaks relative to gene features ([`HOMER`](http://homer.ucsd.edu/homer/download.html))\n 9. Create consensus peakset across all samples and create tabular file to aid in the filtering of the data ([`BEDTools`](https://github.com/arq5x/bedtools2/))\n 10. Count reads in consensus peaks ([`featureCounts`](http://bioinf.wehi.edu.au/featureCounts/))\n 11. Differential accessibility analysis, PCA and clustering ([`R`](https://www.r-project.org/), [`DESeq2`](https://bioconductor.org/packages/release/bioc/html/DESeq2.html))\n 12. Generate ATAC-seq specific QC html report ([`ataqv`](https://github.com/ParkerLab/ataqv))\n6. Merge filtered alignments across replicates ([`picard`](https://broadinstitute.github.io/picard/))\n 1. Re-mark duplicates ([`picard`](https://broadinstitute.github.io/picard/))\n 2. Remove duplicate reads ([`SAMtools`](https://sourceforge.net/projects/samtools/files/samtools/))\n 3. Create normalised bigWig files scaled to 1 million mapped reads ([`BEDTools`](https://github.com/arq5x/bedtools2/), [`bedGraphToBigWig`](http://hgdownload.soe.ucsc.edu/admin/exe/))\n 4. Call broad/narrow peaks ([`MACS2`](https://github.com/macs3-project/MACS))\n 5. Annotate peaks relative to gene features ([`HOMER`](http://homer.ucsd.edu/homer/download.html))\n 6. Create consensus peakset across all samples and create tabular file to aid in the filtering of the data ([`BEDTools`](https://github.com/arq5x/bedtools2/))\n 7. Count reads in consensus peaks relative to merged library-level alignments ([`featureCounts`](http://bioinf.wehi.edu.au/featureCounts/))\n 8. Differential accessibility analysis, PCA and clustering ([`R`](https://www.r-project.org/), [`DESeq2`](https://bioconductor.org/packages/release/bioc/html/DESeq2.html))\n7. Create IGV session file containing bigWig tracks, peaks and differential sites for data visualisation ([`IGV`](https://software.broadinstitute.org/software/igv/)).\n8. Present QC for raw read, alignment, peak-calling and differential accessibility results ([`ataqv`](https://github.com/ParkerLab/ataqv), [`MultiQC`](http://multiqc.info/), [`R`](https://www.r-project.org/))\n\n## Usage\n\n> **Note**\n> If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how\n> to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline)\n> with `-profile test` before running the workflow on actual data.\n\nTo run on your data, prepare a tab-separated samplesheet with your input data. Please follow the [documentation on samplesheets](https://nf-co.re/atacseq/usage#samplesheet-input) for more details. An example samplesheet for running the pipeline looks as follows:\n\n```csv\nsample,fastq_1,fastq_2,replicate\nCONTROL,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz,1\nCONTROL,AEG588A1_S1_L003_R1_001.fastq.gz,AEG588A1_S1_L003_R2_001.fastq.gz,2\nCONTROL,AEG588A1_S1_L004_R1_001.fastq.gz,AEG588A1_S1_L004_R2_001.fastq.gz,3\n```\n\nNow, you can run the pipeline using:\n\n```bash\nnextflow run nf-core/atacseq --input samplesheet.csv --outdir --genome GRCh37 --read_length <50|100|150|200> -profile \n```\n\nSee [usage docs](https://nf-co.re/atacseq/usage) for all of the available options when running the pipeline.\n\n> **Warning:**\n> Please provide pipeline parameters via the CLI or Nextflow `-params-file` option. Custom config files including those\n> provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_;\n> see [docs](https://nf-co.re/usage/configuration#custom-configuration-files).\n\nFor more details and further functionality, please refer to the [usage documentation](https://nf-co.re/atacseq/usage) and the [parameter documentation](https://nf-co.re/atacseq/parameters).\n\n## Pipeline output\n\nTo see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/atacseq/results) tab on the nf-core website pipeline page.\nFor more details about the output files and reports, please refer to the\n[output documentation](https://nf-co.re/atacseq/output).\n\n## Credits\n\nThe pipeline was originally written by Harshil Patel ([@drpatelh](https://github.com/drpatelh)) from [Seqera Labs, Spain](https://seqera.io/) and converted to Nextflow DSL2 by Björn Langer ([@bjlang](https://github.com/bjlang)) and Jose Espinosa-Carrasco ([@JoseEspinosa](https://github.com/JoseEspinosa)) from [The Comparative Bioinformatics Group](https://www.crg.eu/en/cedric_notredame) at [The Centre for Genomic Regulation, Spain](https://www.crg.eu/) under the umbrella of the [BovReg project](https://www.bovreg.eu/).\n\nMany thanks to others who have helped out and contributed along the way too, including (but not limited to): [@ewels](https://github.com/ewels), [@apeltzer](https://github.com/apeltzer), [@crickbabs](https://github.com/crickbabs), [drewjbeh](https://github.com/drewjbeh), [@houghtos](https://github.com/houghtos), [@jinmingda](https://github.com/jinmingda), [@ktrns](https://github.com/ktrns), [@MaxUlysse](https://github.com/MaxUlysse), [@mashehu](https://github.com/mashehu), [@micans](https://github.com/micans), [@pditommaso](https://github.com/pditommaso) and [@sven1103](https://github.com/sven1103).\n\n## Contributions and Support\n\nIf you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).\n\nFor further information or help, don't hesitate to get in touch on the [Slack `#atacseq` channel](https://nfcore.slack.com/channels/atacseq) (you can join with [this invite](https://nf-co.re/join/slack)).\n\n## Citations\n\nIf you use nf-core/atacseq for your analysis, please cite it using the following doi: [10.5281/zenodo.2634132](https://doi.org/10.5281/zenodo.2634132)\n\nAn extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.\n\nYou can cite the `nf-core` publication as follows:\n\n> **The nf-core framework for community-curated bioinformatics pipelines.**\n>\n> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.\n>\n> _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).\n" }, { "path": "assets/adaptivecard.json", "content": "{\n \"type\": \"message\",\n \"attachments\": [\n {\n \"contentType\": \"application/vnd.microsoft.card.adaptive\",\n \"contentUrl\": null,\n \"content\": {\n \"\\$schema\": \"http://adaptivecards.io/schemas/adaptive-card.json\",\n \"msteams\": {\n \"width\": \"Full\"\n },\n \"type\": \"AdaptiveCard\",\n \"version\": \"1.2\",\n \"body\": [\n {\n \"type\": \"TextBlock\",\n \"size\": \"Large\",\n \"weight\": \"Bolder\",\n \"color\": \"<% if (success) { %>Good<% } else { %>Attention<%} %>\",\n \"text\": \"nf-core/atacseq v${version} - ${runName}\",\n \"wrap\": true\n },\n {\n \"type\": \"TextBlock\",\n \"spacing\": \"None\",\n \"text\": \"Completed at ${dateComplete} (duration: ${duration})\",\n \"isSubtle\": true,\n \"wrap\": true\n },\n {\n \"type\": \"TextBlock\",\n \"text\": \"<% if (success) { %>Pipeline completed successfully!<% } else { %>Pipeline completed with errors. 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\"cigar\", \"cigar\": \"*S*\" }\n ],\n\n \"rule\": \" insert_min & insert_max & mismatch & !cigar \"\n}\n" }, { "path": "assets/bamtools_filter_se.json", "content": "{\n \"filters\": [\n { \"id\": \"mismatch\", \"tag\": \"NM:<=4\" },\n\n { \"id\": \"cigar\", \"cigar\": \"*S*\" }\n ],\n\n \"rule\": \" mismatch & !cigar \"\n}\n" }, { "path": "assets/blacklists/old/GRCm38-blacklist.bed", "content": 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"chr10\t3110060\t3110270\nchr10\t22142530\t22142880\nchr10\t22142830\t22143070\nchr10\t58223870\t58224100\nchr10\t58225260\t58225500\nchr10\t58228320\t58228520\nchr11\t3148660\t3148860\nchr11\t3154960\t3155170\nchr11\t3158530\t3158750\nchr11\t3161780\t3161990\nchr11\t3167020\t3167250\nchr11\t3169390\t3169620\nchr11\t3172450\t3172670\nchr11\t3172950\t3173190\nchr11\t3184190\t3185750\nchr11\t3185700\t3186360\nchr11\t3186330\t3189230\nchr11\t3189190\t3190740\nchr11\t3190750\t3191000\nchr11\t3190960\t3194430\nchr11\t3194400\t3195310\nchr11\t3195240\t3197220\nchr11\t3197340\t3197950\nchr11\t3197890\t3198700\nchr11\t3198630\t3199440\nchr11\t3199350\t3200120\nchr11\t54139940\t54140230\nchr11\t54140470\t54140740\nchr11\t88967720\t88969600\nchr11\t88969850\t88970350\nchr11\t109011550\t109012090\nchr12\t3109920\t3110150\nchr12\t105436040\t105436270\nchr13\t3372960\t3373380\nchr13\t3373410\t3373630\nchr13\t77438870\t77439090\nchr13\t97190460\t97190690\nchr13\t99790830\t99791090\nchr13\t119488570\t119489320\nchr13\t119597600\t119598320\nchr13\t119599860\t119600050\nchr13\t119601360\t119601600\nchr13\t119601800\t119602210\nchr13\t119602360\t119602580\nchr13\t119609430\t119611430\nchr13\t119612760\t119613370\nchr13\t119613360\t119617690\nchr14\t19415650\t19417330\nchr14\t19417240\t19417660\nchr14\t19417570\t19418920\nchr14\t19418830\t19419720\nchr14\t47454330\t47454510\nchr15\t75085430\t75085920\nchr15\t75085990\t75086240\nchr15\t75086150\t75086550\nchr15\t75086540\t75087110\nchr16\t11143960\t11144170\nchr16\t57391420\t57391740\nchr17\t13305860\t13306280\nchr17\t13590820\t13591650\nchr17\t13654880\t13655120\nchr17\t36231170\t36231390\nchr17\t39842910\t39846780\nchr17\t39846920\t39847160\nchr17\t39847090\t39847310\nchr17\t39847400\t39847720\nchr17\t39847630\t39848880\nchr18\t3005550\t3005770\nchr18\t3005700\t3006050\nchr18\t12949190\t12949400\nchr18\t40307970\t40308340\nchr18\t68691990\t68692230\nchr19\t45650030\t45650310\nchr19\t61199640\t61199880\nchr19\t61224310\t61224530\nchr19\t61266550\t61266760\nchr19\t61266920\t61267210\nchr1\t24612620\t24612850\nchr1\t48881430\t48881690\nchr1\t58613870\t58614090\nchr1\t78573920\t78574140\nchr1\t88217960\t88221950\nchr1\t88223300\t88224760\nchr1\t133595120\t133595340\nchr1\t183299040\t183299660\nchr1\t195241610\t195241820\nchr2\t3050030\t3050410\nchr2\t5379200\t5379420\nchr2\t22743580\t22743780\nchr2\t22744760\t22744980\nchr2\t90395030\t90395240\nchr2\t98662130\t98663060\nchr2\t98663540\t98664150\nchr2\t98664780\t98665020\nchr2\t98664970\t98665250\nchr2\t98666140\t98667390\nchr2\t181917260\t181917590\nchr2\t181917550\t181917990\nchr2\t181918970\t181919260\nchr2\t181928340\t181928570\nchr2\t181928950\t181929170\nchr2\t181929220\t181929430\nchr2\t181930800\t181931020\nchr3\t5860530\t5860830\nchr3\t8245690\t8245930\nchr3\t8246280\t8246640\nchr4\t34935690\t34935910\nchr4\t70378040\t70378320\nchr4\t118548460\t118548700\nchr5\t14914900\t14915120\nchr5\t15006590\t15006820\nchr5\t15462500\t15462730\nchr5\t15463060\t15463290\nchr5\t15486990\t15487190\nchr5\t134378920\t134379160\nchr5\t137152130\t137152510\nchr5\t146260900\t146261410\nchr6\t3201380\t3201610\nchr6\t103648970\t103649310\nchr7\t12010340\t12010870\nchr8\t14306800\t14307040\nchr8\t15519790\t15520030\nchr8\t19711890\t19712070\nchr9\t2999900\t3000320\nchr9\t3000270\t3000570\nchr9\t3000900\t3001100\nchr9\t3001300\t3001520\nchr9\t3004390\t3004680\nchr9\t3004690\t3004900\nchr9\t3005000\t3005220\nchr9\t3005800\t3006030\nchr9\t3006960\t3007180\nchr9\t3008880\t3009040\nchr9\t3015170\t3015420\nchr9\t3015590\t3015830\nchr9\t3016770\t3016980\nchr9\t3017410\t3017650\nchr9\t3018240\t3018540\nchr9\t3018650\t3018870\nchr9\t3019220\t3019450\nchr9\t3021160\t3021370\nchr9\t3021990\t3022300\nchr9\t3024660\t3024880\nchr9\t3025350\t3025690\nchr9\t3026530\t3026860\nchr9\t3027010\t3027250\nchr9\t3027660\t3027880\nchr9\t3028670\t3028880\nchr9\t3030040\t3030330\nchr9\t3031910\t3032130\nchr9\t3032250\t3032560\nchr9\t3032570\t3032790\nchr9\t3034090\t3034300\nchr9\t3034950\t3035160\nchr9\t3035610\t3036180\nchr9\t3036200\t3036480\nchr9\t3036420\t3036660\nchr9\t3037250\t3037460\nchr9\t3037910\t3038120\nchr9\t3038050\t3038300\nchr9\t24541940\t24542200\nchr9\t35305120\t35305620\nchr9\t110281190\t110281400\nchr9\t123872950\t123873160\n" }, { "path": "assets/blacklists/v1.0/GRCh37-blacklist.v1.bed", "content": "1\t564449\t570371\tHigh_Mappability_island\t1000\t.\n1\t724136\t727043\tSatellite_repeat\t1000\t.\n1\t825006\t825115\tBSR/Beta\t1000\t.\n1\t2583334\t2634374\tLow_mappability_island\t1000\t.\n1\t4363064\t4363242\t(CATTC)n\t1000\t.\n1\t5725866\t5736651\tLow_mappability_island\t1000\t.\n1\t16839923\t16841396\tLow_mappability_island\t1000\t.\n1\t38077347\t38077423\tLow_mappability_island\t1000\t.\n1\t91852785\t91853147\tLSU-rRNA_Hsa\t1000\t.\n1\t104163724\t104163860\tLow_mappability_island\t1000\t.\n1\t108112972\t108113707\tLSU-rRNA_Hsa\t1000\t.\n1\t121351474\t121487059\tcentromeric_repeat\t1000\t.\n1\t142535434\t142543081\tSatellite_repeat\t1000\t.\n1\t142723256\t142723968\tLow_mappability_island\t1000\t.\n1\t142792613\t142793303\tLow_mappability_island\t1000\t.\n1\t142835822\t142837333\tLow_mappability_island\t1000\t.\n1\t143274490\t143284340\tcentromeric_repeat\t1000\t.\n1\t145277108\t145277572\tLSU-rRNA_Hsa\t1000\t.\n1\t149033183\t149035829\tSatellite_repeat\t1000\t.\n1\t156186169\t156186712\tHigh_Mappability_island\t1000\t.\n1\t224199390\t224204260\tSatellite_repeat\t1000\t.\n1\t233318467\t233318516\t(CATTC)n\t1000\t.\n1\t236260366\t236260821\tLow_mappability_island\t1000\t.\n1\t237766308\t237766764\tLSU-rRNA_Hsa\t1000\t.\n1\t238105345\t238105511\tLow_mappability_island\t1000\t.\n1\t238108025\t238108378\tLow_mappability_island\t1000\t.\n1\t238108645\t238109697\tLow_mappability_island\t1000\t.\n10\t18841533\t18862467\t(CATTC)n\t1000\t.\n10\t20035661\t20037171\tLow_mappability_island\t1000\t.\n10\t36722282\t36723650\tLow_mappability_island\t1000\t.\n10\t38772277\t38819357\tSatellite_repeat\t1000\t.\n10\t38868892\t38889025\tSatellite_repeat\t1000\t.\n10\t39076515\t39155771\tSatellite_repeat\t1000\t.\n10\t42354835\t42548642\tcentromeric_repeat\t1000\t.\n10\t42596676\t42602082\tSatellite_repeat\t1000\t.\n10\t42596700\t42602110\tSatellite_repeat\t1000\t.\n10\t42661264\t42667623\tSatellite_repeat\t1000\t.\n10\t42790522\t42818398\tSatellite_repeat\t1000\t.\n10\t135498649\t135502716\tSatellite_repeat\t1000\t.\n11\t6831669\t6831838\tALR/Alpha\t1000\t.\n11\t10529403\t10531969\tLow_mappability_island\t1000\t.\n11\t48671444\t48902406\tcentromeric_repeat\t1000\t.\n11\t48931242\t48964015\tcentromeric_repeat\t1000\t.\n11\t50318471\t50784078\tcentromeric_repeat\t1000\t.\n11\t51090700\t51374066\tcentromeric_repeat\t1000\t.\n11\t51567242\t51594226\tcentromeric_repeat\t1000\t.\n11\t54694046\t55027975\tcentromeric_repeat\t1000\t.\n11\t73221660\t73221946\tLow_mappability_island\t1000\t.\n11\t85194913\t85195322\tLSU-rRNA_Hsa\t1000\t.\n11\t87524468\t87525005\tLow_mappability_island\t1000\t.\n11\t103275584\t103281729\tLow_mappability_island\t1000\t.\n11\t122874287\t122874443\tLow_mappability_island\t1000\t.\n12\t20704285\t20704583\tSSU-rRNA_Hsa\t1000\t.\n12\t34372315\t34372825\tLSU-rRNA_Hsa\t1000\t.\n12\t34432130\t34857010\tcentromeric_repeat\t1000\t.\n12\t37989447\t38441828\tcentromeric_repeat\t1000\t.\n12\t38531376\t38531930\tLSU-rRNA_Hsa\t1000\t.\n12\t41757383\t41757545\tLow_mappability_island\t1000\t.\n12\t127650407\t127651075\tLSU-rRNA_Hsa\t1000\t.\n12\t132061320\t132062046\tLow_mappability_island\t1000\t.\n13\t56545728\t56545925\tLow_mappability_island\t1000\t.\n13\t110076444\t110076782\tLow_mappability_island\t1000\t.\n14\t18999935\t19056900\tcentromeric_repeat\t1000\t.\n14\t32953263\t32954381\tLow_mappability_island\t1000\t.\n14\t84637832\t84639038\tLow_mappability_island\t1000\t.\n14\t90341302\t90341516\tSSU-rRNA_Hsa\t1000\t.\n15\t19999941\t20044132\tcentromeric_repeat\t1000\t.\n16\t32493036\t32570826\tALR/Alpha\t1000\t.\n16\t32590063\t32598801\tALR/Alpha\t1000\t.\n16\t33237130\t33241330\tLow_mappability_island\t1000\t.\n16\t33864355\t34023306\tcentromeric_repeat\t1000\t.\n16\t34180542\t34197081\tSatellite_repeat\t1000\t.\n16\t34530115\t34542632\tBSR/Beta\t1000\t.\n16\t35193580\t35285885\tcentromeric_repeat\t1000\t.\n16\t46385718\t46456668\tSatellite_repeat\t1000\t.\n16\t46497639\t46500515\tSatellite_repeat\t1000\t.\n16\t47538629\t47539297\tLSU-rRNA_Hsa\t1000\t.\n17\t19355538\t19356096\tLSU-rRNA_Hsa\t1000\t.\n17\t19502495\t19506773\tLow_mappability_island\t1000\t.\n17\t21905167\t21906712\tcentromeric_repeat\t1000\t.\n17\t22018524\t22032049\tLow_mappability_island\t1000\t.\n17\t22221073\t22263006\tcentromeric_repeat\t1000\t.\n17\t25263010\t25268059\tSatellite_repeat\t1000\t.\n17\t25415551\t25417559\ttelomeric_repeat\t1000\t.\n17\t31149365\t31149981\tHigh_Mappability_island\t1000\t.\n17\t33478114\t33478372\tLSU-rRNA_Hsa\t1000\t.\n17\t41381502\t41382591\tHigh_Mappability_island\t1000\t.\n17\t41463538\t41464075\tHigh_Mappability_island\t1000\t.\n17\t41464478\t41465015\tsnRNA\t1000\t.\n17\t41465562\t41467288\tHigh_Mappability_island\t1000\t.\n17\t51183038\t51183763\tLow_mappability_island\t1000\t.\n17\t55868618\t55868752\tLSU-rRNA_Hsa\t1000\t.\n17\t75158031\t75158430\tLSU-rRNA_Hsa\t1000\t.\n18\t96416\t97552\tSatellite_repeat\t1000\t.\n18\t105658\t112233\tSatellite_repeat\t1000\t.\n18\t2842252\t2842356\tLow_mappability_island\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"chr1\t564449\t570371\tHigh_Mappability_island\t1000\t.\nchr1\t724136\t727043\tSatellite_repeat\t1000\t.\nchr1\t825006\t825115\tBSR/Beta\t1000\t.\nchr1\t2583334\t2634374\tLow_mappability_island\t1000\t.\nchr1\t4363064\t4363242\t(CATTC)n\t1000\t.\nchr1\t5725866\t5736651\tLow_mappability_island\t1000\t.\nchr1\t16839923\t16841396\tLow_mappability_island\t1000\t.\nchr1\t38077347\t38077423\tLow_mappability_island\t1000\t.\nchr1\t91852785\t91853147\tLSU-rRNA_Hsa\t1000\t.\nchr1\t104163724\t104163860\tLow_mappability_island\t1000\t.\nchr1\t108112972\t108113707\tLSU-rRNA_Hsa\t1000\t.\nchr1\t121351474\t121487059\tcentromeric_repeat\t1000\t.\nchr1\t142535434\t142543081\tSatellite_repeat\t1000\t.\nchr1\t142723256\t142723968\tLow_mappability_island\t1000\t.\nchr1\t142792613\t142793303\tLow_mappability_island\t1000\t.\nchr1\t142835822\t142837333\tLow_mappability_island\t1000\t.\nchr1\t143274490\t143284340\tcentromeric_repeat\t1000\t.\nchr1\t145277108\t145277572\tLSU-rRNA_Hsa\t1000\t.\nchr1\t149033183\t149035829\tSatellite_repeat\t1000\t.\nchr1\t156186169\t156186712\tHigh_Mappability_island\t1000\t.\nchr1\t224199390\t224204260\tSatellite_repeat\t1000\t.\nchr1\t233318467\t233318516\t(CATTC)n\t1000\t.\nchr1\t236260366\t236260821\tLow_mappability_island\t1000\t.\nchr1\t237766308\t237766764\tLSU-rRNA_Hsa\t1000\t.\nchr1\t238105345\t238105511\tLow_mappability_island\t1000\t.\nchr1\t238108025\t238108378\tLow_mappability_island\t1000\t.\nchr1\t238108645\t238109697\tLow_mappability_island\t1000\t.\nchr10\t18841533\t18862467\t(CATTC)n\t1000\t.\nchr10\t20035661\t20037171\tLow_mappability_island\t1000\t.\nchr10\t36722282\t36723650\tLow_mappability_island\t1000\t.\nchr10\t38772277\t38819357\tSatellite_repeat\t1000\t.\nchr10\t38868892\t38889025\tSatellite_repeat\t1000\t.\nchr10\t39076515\t39155771\tSatellite_repeat\t1000\t.\nchr10\t42354835\t42548642\tcentromeric_repeat\t1000\t.\nchr10\t42596676\t42602082\tSatellite_repeat\t1000\t.\nchr10\t42596700\t42602110\tSatellite_repeat\t1000\t.\nchr10\t42661264\t42667623\tSatellite_repeat\t1000\t.\nchr10\t42790522\t42818398\tSatellite_repeat\t1000\t.\nchr10\t135498649\t135502716\tSatellite_repeat\t1000\t.\nchr11\t6831669\t6831838\tALR/Alpha\t1000\t.\nchr11\t10529403\t10531969\tLow_mappability_island\t1000\t.\nchr11\t48671444\t48902406\tcentromeric_repeat\t1000\t.\nchr11\t48931242\t48964015\tcentromeric_repeat\t1000\t.\nchr11\t50318471\t50784078\tcentromeric_repeat\t1000\t.\nchr11\t51090700\t51374066\tcentromeric_repeat\t1000\t.\nchr11\t51567242\t51594226\tcentromeric_repeat\t1000\t.\nchr11\t54694046\t55027975\tcentromeric_repeat\t1000\t.\nchr11\t73221660\t73221946\tLow_mappability_island\t1000\t.\nchr11\t85194913\t85195322\tLSU-rRNA_Hsa\t1000\t.\nchr11\t87524468\t87525005\tLow_mappability_island\t1000\t.\nchr11\t103275584\t103281729\tLow_mappability_island\t1000\t.\nchr11\t122874287\t122874443\tLow_mappability_island\t1000\t.\nchr12\t20704285\t20704583\tSSU-rRNA_Hsa\t1000\t.\nchr12\t34372315\t34372825\tLSU-rRNA_Hsa\t1000\t.\nchr12\t34432130\t34857010\tcentromeric_repeat\t1000\t.\nchr12\t37989447\t38441828\tcentromeric_repeat\t1000\t.\nchr12\t38531376\t38531930\tLSU-rRNA_Hsa\t1000\t.\nchr12\t41757383\t41757545\tLow_mappability_island\t1000\t.\nchr12\t127650407\t127651075\tLSU-rRNA_Hsa\t1000\t.\nchr12\t132061320\t132062046\tLow_mappability_island\t1000\t.\nchr13\t56545728\t56545925\tLow_mappability_island\t1000\t.\nchr13\t110076444\t110076782\tLow_mappability_island\t1000\t.\nchr14\t18999935\t19056900\tcentromeric_repeat\t1000\t.\nchr14\t32953263\t32954381\tLow_mappability_island\t1000\t.\nchr14\t84637832\t84639038\tLow_mappability_island\t1000\t.\nchr14\t90341302\t90341516\tSSU-rRNA_Hsa\t1000\t.\nchr15\t19999941\t20044132\tcentromeric_repeat\t1000\t.\nchr16\t32493036\t32570826\tALR/Alpha\t1000\t.\nchr16\t32590063\t32598801\tALR/Alpha\t1000\t.\nchr16\t33237130\t33241330\tLow_mappability_island\t1000\t.\nchr16\t33864355\t34023306\tcentromeric_repeat\t1000\t.\nchr16\t34180542\t34197081\tSatellite_repeat\t1000\t.\nchr16\t34530115\t34542632\tBSR/Beta\t1000\t.\nchr16\t35193580\t35285885\tcentromeric_repeat\t1000\t.\nchr16\t46385718\t46456668\tSatellite_repeat\t1000\t.\nchr16\t46497639\t46500515\tSatellite_repeat\t1000\t.\nchr16\t47538629\t47539297\tLSU-rRNA_Hsa\t1000\t.\nchr17\t19355538\t19356096\tLSU-rRNA_Hsa\t1000\t.\nchr17\t19502495\t19506773\tLow_mappability_island\t1000\t.\nchr17\t21905167\t21906712\tcentromeric_repeat\t1000\t.\nchr17\t22018524\t22032049\tLow_mappability_island\t1000\t.\nchr17\t22221073\t22263006\tcentromeric_repeat\t1000\t.\nchr17\t25263010\t25268059\tSatellite_repeat\t1000\t.\nchr17\t25415551\t25417559\ttelomeric_repeat\t1000\t.\nchr17\t31149365\t31149981\tHigh_Mappability_island\t1000\t.\nchr17\t33478114\t33478372\tLSU-rRNA_Hsa\t1000\t.\nchr17\t41381502\t41382591\tHigh_Mappability_island\t1000\t.\nchr17\t41463538\t41464075\tHigh_Mappability_island\t1000\t.\nchr17\t41464478\t41465015\tsnRNA\t1000\t.\nchr17\t41465562\t41467288\tHigh_Mappability_island\t1000\t.\nchr17\t51183038\t51183763\tLow_mappability_island\t1000\t.\nchr17\t55868618\t55868752\tLSU-rRNA_Hsa\t1000\t.\nchr17\t75158031\t75158430\tLSU-rRNA_Hsa\t1000\t.\nchr18\t96416\t97552\tSatellite_repeat\t1000\t.\nchr18\t105658\t112233\tSatellite_repeat\t1000\t.\nchr18\t2842252\t2842356\tLow_mappability_island\t1000\t.\nchr18\t15393801\t15393992\tcentromeric_repeat\t1000\t.\nchr18\t18510894\t18520356\tcentromeric_repeat\t1000\t.\nchr18\t44126235\t44126593\t(CATTC)n\t1000\t.\nchr18\t45379603\t45379864\tLow_mappability_island\t1000\t.\nchr18\t50319086\t50319301\tLow_mappability_island\t1000\t.\nchr18\t77772846\t77773065\tLSU-rRNA_Hsa\t1000\t.\nchr19\t246006\t247844\tTAR1\t1000\t.\nchr19\t22877614\t22877696\tSSU-rRNA_Hsa\t1000\t.\nchr19\t23235030\t23235504\tBSR/Beta\t1000\t.\nchr19\t24182398\t24186210\tLSU-rRNA_Hsa\t1000\t.\nchr19\t24385474\t24633168\tcentromeric_repeat\t1000\t.\nchr19\t27730611\t28262682\tcentromeric_repeat\t1000\t.\nchr19\t36066445\t36066810\tLSU-rRNA_Hsa\t1000\t.\nchr19\t36756398\t36800948\tcentromeric_repeat\t1000\t.\nchr19\t37759473\t37797722\tcentromeric_repeat\t1000\t.\nchr19\t44914313\t44916340\tACRO1\t1000\t.\nchr19\t44960681\t44962681\tACRO1\t1000\t.\nchr2\t739925\t740994\tLow_mappability_island\t1000\t.\nchr2\t49456729\t49457067\tLow_mappability_island\t1000\t.\nchr2\t88124390\t88124903\tLow_mappability_island\t1000\t.\nchr2\t89830421\t89880514\tSatellite_repeat\t1000\t.\nchr2\t90371401\t90394776\tSatellite_repeat\t1000\t.\nchr2\t90443001\t90545431\tLow_mappability_island\t1000\t.\nchr2\t91595080\t91616015\tSatellite_repeat\t1000\t.\nchr2\t92267428\t92326280\tcentromeric_repeat\t1000\t.\nchr2\t115695017\t115695281\tLSU-rRNA_Hsa\t1000\t.\nchr2\t117781085\t117781300\tLow_mappability_island\t1000\t.\nchr2\t132966248\t132989300\tcentromeric_repeat\t1000\t.\nchr2\t132994855\t133007983\tALR/Alpha\t1000\t.\nchr2\t133011824\t133013298\tSSU-rRNA_Hsa\t1000\t.\nchr2\t133036250\t133040042\tLSU-rRNA_Hsa\t1000\t.\nchr2\t133044095\t133045945\tACRO1\t1000\t.\nchr2\t143848503\t143848792\tLow_mappability_island\t1000\t.\nchr2\t148022736\t148022878\tLow_mappability_island\t1000\t.\nchr2\t149639207\t149639515\tLow_mappability_island\t1000\t.\nchr2\t156120500\t156120610\tLow_mappability_island\t1000\t.\nchr2\t162135000\t162139241\tLow_mappability_island\t1000\t.\nchr2\t230045426\t230045796\tLSU-rRNA_Hsa\t1000\t.\nchr20\t26257032\t26320267\tcentromeric_repeat\t1000\t.\nchr20\t29517710\t29521147\tcentromeric_repeat\t1000\t.\nchr20\t29803876\t29833334\tcentromeric_repeat\t1000\t.\nchr20\t55932703\t55936114\tchrM\t1000\t.\nchr20\t62916702\t62918053\ttelomeric_repeat\t1000\t.\nchr21\t9647205\t9648529\tLow_mappability_island\t1000\t.\nchr21\t9694896\t9704962\tcentromeric_repeat\t1000\t.\nchr21\t9825451\t9827612\tHigh_Mappability_island\t1000\t.\nchr21\t9827612\t9845233\tLow_mappability_island\t1000\t.\nchr21\t9881895\t9882569\tTAR1\t1000\t.\nchr21\t10084922\t10088004\tSatellite_repeat\t1000\t.\nchr21\t10492876\t10493049\tLow_mappability_island\t1000\t.\nchr21\t10599428\t10599915\tTAR1\t1000\t.\nchr21\t10697886\t10860890\tcentromeric_repeat\t1000\t.\nchr21\t11186054\t11188131\tSatellite_repeat\t1000\t.\nchr21\t14338127\t14369791\tcentromeric_repeat\t1000\t.\nchr21\t18800575\t18800997\t(GAGTG)n\t1000\t.\nchr21\t27228003\t27228242\tSSU-rRNA_Hsa\t1000\t.\nchr21\t46796081\t46796336\tLow_mappability_island\t1000\t.\nchr22\t16847814\t16862659\tSatellite_repeat\t1000\t.\nchr22\t18876789\t18884510\tSatellite_repeat\t1000\t.\nchr3\t25508897\t25509131\tLow_mappability_island\t1000\t.\nchr3\t73159606\t73161131\tsnRNA\t1000\t.\nchr3\t75696297\t75699304\tBSR/Beta\t1000\t.\nchr3\t75717841\t75720426\tSatellite_repeat\t1000\t.\nchr3\t80995858\t81014459\tALR/Alpha\t1000\t.\nchr3\t90311686\t90507410\tcentromeric_repeat\t1000\t.\nchr3\t93504815\t93519133\tcentromeric_repeat\t1000\t.\nchr3\t96335934\t96337436\tLow_mappability_island\t1000\t.\nchr3\t160665423\t160665642\tLow_mappability_island\t1000\t.\nchr3\t196625514\t196625860\tSatellite_repeat\t1000\t.\nchr3\t197825427\t197834080\tLow_mappability_island\t1000\t.\nchr4\t9987\t12694\ttelomeric_repeat\t1000\t.\nchr4\t12276463\t12292424\tALR/Alpha\t1000\t.\nchr4\t12641862\t12642305\tLow_mappability_island\t1000\t.\nchr4\t21583630\t21583719\t(GAATG)n\t1000\t.\nchr4\t27732004\t27732240\tLow_mappability_island\t1000\t.\nchr4\t47774268\t47774416\tLow_mappability_island\t1000\t.\nchr4\t49085372\t49342114\tcentromeric_repeat\t1000\t.\nchr4\t49488472\t49662085\tcentromeric_repeat\t1000\t.\nchr4\t52659961\t52688986\tcentromeric_repeat\t1000\t.\nchr4\t56194229\t56194584\tLow_mappability_island\t1000\t.\nchr4\t65473858\t65473941\tLow_mappability_island\t1000\t.\nchr4\t68264186\t68266830\tcentromeric_repeat\t1000\t.\nchr4\t70296565\t70296841\tLSU-rRNA_Hsa\t1000\t.\nchr4\t76807083\t76807320\tLSU-rRNA_Hsa\t1000\t.\nchr4\t78929660\t78929920\tLow_mappability_island\t1000\t.\nchr4\t156374749\t156377226\tchrM\t1000\t.\nchr4\t156384860\t156387314\tLow_mappability_island\t1000\t.\nchr4\t163342479\t163342744\tLow_mappabilit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Region\nX\t66316400\t66356900\tHigh Signal Region\nX\t67662500\t67708500\tHigh Signal Region\nX\t70055300\t70072000\tHigh Signal Region\nX\t72800000\t72818700\tHigh Signal Region\nX\t75582400\t75709000\tHigh Signal Region\nX\t76589100\t76607100\tHigh Signal Region\nX\t79135300\t79150400\tHigh Signal Region\nX\t81153100\t81154600\tHigh Signal Region\nX\t82475800\t82481000\tHigh Signal Region\nX\t84290800\t84296100\tHigh Signal Region\nX\t87222400\t87262500\tHigh Signal Region\nX\t87838600\t87845200\tHigh Signal Region\nX\t88230200\t88246900\tHigh Signal Region\nX\t89182800\t89232600\tHigh Signal Region\nX\t89914800\t89916600\tHigh Signal Region\nX\t90308600\t90336600\tHigh Signal Region\nX\t92765200\t92767900\tHigh Signal Region\nX\t94795400\t94980600\tHigh Signal Region\nX\t95265900\t95291700\tHigh Signal Region\nX\t97728000\t97734800\tHigh Signal Region\nX\t98008600\t98033000\tHigh Signal Region\nX\t98585800\t98612400\tHigh Signal Region\nX\t101111300\t101113600\tHigh Signal Region\nX\t102560800\t102585100\tHigh Signal Region\nX\t103455000\t103457100\tHigh Signal Region\nX\t104959400\t104966000\tHigh Signal Region\nX\t105523800\t105529900\tHigh Signal Region\nX\t108202600\t108222500\tHigh Signal Region\nX\t108567500\t108585200\tHigh Signal Region\nX\t109871000\t109876200\tHigh Signal Region\nX\t110976700\t110997000\tHigh Signal Region\nX\t112369800\t112402300\tHigh Signal Region\nX\t114412500\t114421300\tHigh Signal Region\nX\t118100900\t118102900\tHigh Signal Region\nX\t118901200\t118905100\tLow Mappability\nX\t119137300\t119142400\tHigh Signal Region\nX\t119247400\t119264800\tHigh Signal Region\nX\t119335000\t119339300\tHigh Signal Region\nX\t120351000\t120355400\tHigh Signal Region\nX\t121511200\t121514500\tHigh Signal Region\nX\t122901700\t122908000\tHigh Signal Region\nX\t123686000\t124042000\tHigh Signal Region\nX\t126695300\t126778800\tHigh Signal Region\nX\t127935800\t127964600\tHigh Signal Region\nX\t128512700\t128514400\tHigh Signal Region\nX\t128959800\t128965900\tHigh Signal Region\nX\t129055600\t129072400\tHigh Signal Region\nX\t129429300\t129448000\tHigh Signal Region\nX\t130696000\t130702200\tHigh Signal Region\nX\t131802300\t131832800\tHigh Signal Region\nX\t132024200\t132026400\tHigh Signal Region\nX\t132158700\t132160800\tHigh Signal Region\nX\t134149100\t134151200\tHigh Signal Region\nX\t135040100\t135056700\tHigh Signal Region\nX\t136459400\t136503800\tHigh Signal Region\nX\t136897900\t136925800\tHigh Signal Region\nX\t138302200\t138324600\tHigh Signal Region\nX\t143471300\t143484000\tHigh Signal Region\nX\t144699500\t144723900\tHigh Signal Region\nX\t145709800\t145739800\tHigh Signal Region\nX\t146582500\t146588700\tHigh Signal Region\nX\t146758100\t146761900\tHigh Signal Region\nX\t147619400\t147620700\tHigh Signal Region\nX\t153994800\t154073200\tHigh Signal Region\nX\t154242800\t154244800\tHigh Signal Region\nX\t158443900\t158460500\tHigh Signal Region\nX\t159120000\t159154900\tHigh Signal Region\nX\t161179200\t161185600\tHigh Signal Region\nX\t162381600\t162384600\tHigh Signal Region\nX\t164615100\t164622200\tHigh Signal Region\nX\t166063200\t166084500\tHigh Signal Region\nX\t167213400\t167220200\tHigh Signal Region\nX\t167246000\t167252200\tHigh Signal Region\nX\t169968900\t171031200\tHigh Signal Region\nY\t0\t806800\tHigh Signal Region\nY\t924800\t1005300\tHigh Signal Region\nY\t1276400\t1813700\tHigh Signal Region\nY\t1834500\t1940700\tHigh Signal Region\nY\t1973200\t1996400\tHigh Signal Region\nY\t2017200\t2068000\tLow Mappability\nY\t2104700\t2210800\tHigh Signal Region\nY\t2280300\t2288900\tLow Mappability\nY\t2471300\t3819300\tHigh Signal Region\nY\t3880300\t4177100\tHigh Signal Region\nY\t4249500\t4289100\tHigh Signal Region\nY\t4432000\t4956300\tHigh Signal Region\nY\t5062400\t5227700\tHigh Signal Region\nY\t6376700\t6382700\tHigh Signal Region\nY\t6530200\t6663200\tHigh Signal Region\nY\t6760200\t6835800\tHigh Signal Region\nY\t6984100\t8985400\tHigh Signal Region\nY\t10638500\t41003800\tHigh Signal Region\nY\t41159200\t91744600\tHigh Signal Region\n" }, { "path": "assets/blacklists/v2.0/ce10-blacklist.v2.bed", "content": "chrIII\t449300\t453600\tHigh Signal Region\nchrIII\t930200\t932600\tHigh Signal Region\nchrIII\t1016500\t1021400\tLow Mappability\nchrIII\t1293500\t1303900\tHigh Signal Region\nchrIII\t5352200\t5359400\tHigh Signal Region\nchrIII\t7404700\t7452200\tHigh Signal Region\nchrIII\t7593800\t7603300\tHigh Signal Region\nchrIII\t8861100\t8864700\tHigh Signal Region\nchrIII\t10215600\t10228400\tHigh Signal Region\nchrIII\t13775100\t14905900\tHigh Signal Region\nchrII\t0\t1300\tHigh Signal Region\nchrII\t2569700\t2571600\tHigh Signal Region\nchrII\t3464700\t3469600\tHigh Signal Region\nchrII\t3795600\t3798100\tHigh Signal Region\nchrII\t3993700\t3995700\tHigh Signal Region\nchrII\t4640300\t4645900\tHigh Signal Region\nchrII\t5143800\t5147500\tHigh Signal Region\nchrII\t6504400\t6509800\tHigh Signal Region\nchrII\t8286700\t8293600\tHigh Signal Region\nchrII\t8975300\t8977400\tHigh Signal Region\nchrII\t9631400\t9633700\tHigh Signal Region\nchrII\t10335100\t10339700\tHigh Signal Region\nchrII\t11527100\t11530900\tHigh Signal Region\nchrII\t12842800\t12846900\tLow Mappability\nchrII\t13597700\t13600700\tLow Mappability\nchrII\t13983900\t13987500\tLow Mappability\nchrII\t14323700\t14340100\tHigh Signal Region\nchrII\t14992100\t14994300\tHigh Signal Region\nchrI\t669000\t679400\tHigh Signal Region\nchrI\t931700\t935600\tHigh Signal Region\nchrI\t3170700\t3173300\tHigh Signal Region\nchrI\t3989200\t3991600\tHigh Signal Region\nchrI\t4535300\t4549400\tHigh Signal Region\nchrI\t5151000\t5154700\tHigh Signal Region\nchrI\t10203200\t10220100\tHigh Signal Region\nchrI\t10265700\t10277700\tHigh Signal Region\nchrI\t10945100\t10953900\tHigh Signal Region\nchrI\t15059400\t15373800\tHigh Signal Region\nchrIV\t2821200\t2831500\tHigh Signal Region\nchrIV\t3205500\t3210300\tHigh Signal Region\nchrIV\t3365800\t3368900\tLow Mappability\nchrIV\t4415600\t4422900\tHigh Signal Region\nchrIV\t6357100\t6361700\tHigh Signal Region\nchrIV\t6468100\t6470600\tLow Mappability\nchrIV\t6682800\t6704100\tHigh Signal Region\nchrIV\t6709900\t6734000\tHigh Signal Region\nchrIV\t7590900\t7600100\tHigh Signal Region\nchrIV\t8563000\t8582700\tHigh Signal Region\nchrIV\t9045100\t9049600\tHigh Signal Region\nchrIV\t10942600\t10951900\tHigh Signal Region\nchrIV\t11070000\t11076700\tHigh Signal Region\nchrIV\t12313600\t12325600\tHigh Signal Region\nchrIV\t12637100\t12639400\tLow Mappability\nchrIV\t13359700\t13362800\tHigh Signal Region\nchrIV\t13548500\t13550400\tHigh Signal Region\nchrIV\t14056400\t14059900\tHigh Signal Region\nchrIV\t14775600\t14782300\tLow Mappability\nchrIV\t15408400\t15424900\tLow Mappability\nchrV\t264100\t268100\tHigh Signal Region\nchrV\t1103700\t1106100\tLow Mappability\nchrV\t1637000\t1639900\tHigh Signal Region\nchrV\t3098000\t3100300\tHigh Signal Region\nchrV\t3434000\t3441600\tHigh Signal Region\nchrV\t5072400\t5084800\tHigh Signal Region\nchrV\t5278300\t5286700\tHigh Signal Region\nchrV\t6171000\t6183700\tHigh Signal Region\nchrV\t6936700\t6943800\tHigh Signal Region\nchrV\t7442400\t7445100\tHigh Signal Region\nchrV\t7912200\t7925700\tHigh Signal Region\nchrV\t7988100\t7993900\tHigh Signal Region\nchrV\t8698600\t8715600\tHigh Signal Region\nchrV\t9423500\t9436100\tHigh Signal Region\nchrV\t10604900\t10613200\tHigh Signal Region\nchrV\t12509100\t12511300\tHigh Signal Region\nchrV\t14765800\t14770600\tHigh Signal Region\nchrV\t15425800\t15436300\tHigh Signal Region\nchrV\t16706300\t16710300\tHigh Signal Region\nchrV\t17114500\t17133000\tHigh Signal Region\nchrV\t17307700\t17312400\tHigh Signal Region\nchrV\t17383300\t17395200\tLow Mappability\nchrV\t18399500\t18402500\tHigh Signal Region\nchrX\t108300\t115100\tHigh Signal Region\nchrX\t273800\t296200\tHigh Signal Region\nchrX\t1635300\t1645200\tHigh Signal Region\nchrX\t1747400\t1755900\tHigh Signal Region\nchrX\t3006400\t3008800\tHigh Signal Region\nchrX\t4025200\t4056900\tHigh Signal Region\nchrX\t5045000\t5058100\tHigh Signal Region\nchrX\t7076500\t7081700\tHigh Signal Region\nchrX\t9184100\t9189500\tHigh Signal Region\nchrX\t9437700\t9440000\tHigh Signal Region\nchrX\t10360200\t10369900\tHigh Signal Region\nchrX\t11784800\t11790300\tHigh Signal Region\nchrX\t11885600\t11889600\tHigh Signal Region\nchrX\t12275900\t12280400\tHigh Signal Region\nchrX\t14384000\t14390400\tHigh Signal Region\nchrX\t14907200\t14910200\tHigh Signal Region\nchrX\t15226100\t15229500\tHigh Signal Region\nchrX\t15806300\t15812000\tLow Mappability\nchrX\t16757900\t16761600\tHigh Signal Region\n" }, { "path": "assets/blacklists/v2.0/ce11-blacklist.v2.bed", "content": "chrIII\t449400\t453600\tHigh Signal Region\nchrIII\t930300\t932600\tHigh Signal Region\nchrIII\t1016500\t1021500\tLow Mappability\nchrIII\t1293500\t1303900\tHigh Signal Region\nchrIII\t5352200\t5359400\tHigh Signal Region\nchrIII\t7404700\t7452200\tHigh Signal Region\nchrIII\t7593800\t7598100\tHigh Signal Region\nchrIII\t8861200\t8864800\tHigh Signal Region\nchrIII\t10216000\t10228500\tHigh Signal Region\nchrIII\t13775200\t13783800\tHigh Signal Region\nchrII\t0\t1300\tHigh Signal Region\nchrII\t2569700\t2571800\tHigh Signal Region\nchrII\t3464700\t3469600\tHigh Signal Region\nchrII\t3795600\t3798100\tHigh Signal Region\nchrII\t3993700\t3995700\tHigh Signal Region\nchrII\t4640300\t4645900\tHigh Signal Region\nchrII\t5143800\t5147500\tHigh Signal Region\nchrII\t6504500\t6509800\tHigh Signal Region\nchrII\t8286700\t8293600\tHigh Signal Region\nchrII\t8975300\t8977500\tHigh Signal Region\nchrII\t9631500\t9633800\tHigh Signal Region\nchrII\t10335100\t10339700\tHigh Signal Region\nchrII\t11527200\t11530900\tHigh Signal Region\nchrII\t12842900\t12846900\tLow Mappability\nchrII\t13597800\t13600800\tHigh Signal Region\nchrII\t13984000\t13987600\tLow Mappability\nchrII\t14323700\t14340100\tHigh Signal Region\nchrII\t14992200\t14994400\tHigh Signal Region\nchrI\t669000\t679200\tHigh Signal Region\nchrI\t931700\t935600\tHigh Signal Region\nchrI\t3170700\t3173300\tHigh Signal Region\nchrI\t3989200\t3991600\tHigh Signal Region\nchrI\t4535300\t4549400\tHigh Signal Region\nchrI\t5151000\t5154700\tHigh Signal Region\nchrI\t10203200\t10220100\tHigh Signal Region\nchrI\t10265700\t10277700\tHigh Signal Region\nchrI\t10945100\t10953900\tHigh Signal Region\nchrI\t15059400\t15072400\tHigh Signal Region\nchrIV\t2821100\t2831500\tHigh Signal Region\nchrIV\t3205500\t3210300\tHigh Signal Region\nchrIV\t3365800\t3368800\tLow Mappability\nchrIV\t4415600\t4422800\tHigh Signal Region\nchrIV\t6357100\t6361700\tHigh Signal Region\nchrIV\t6468100\t6470600\tLow Mappability\nchrIV\t6682700\t6704200\tHigh Signal Region\nchrIV\t7590800\t7600100\tHigh Signal Region\nchrIV\t8563000\t8582600\tHigh Signal Region\nchrIV\t9045100\t9049600\tHigh Signal Region\nchrIV\t10942600\t10951900\tHigh Signal Region\nchrIV\t11070000\t11076700\tHigh Signal Region\nchrIV\t12023000\t12025800\tHigh Signal Region\nchrIV\t12313600\t12325600\tHigh Signal Region\nchrIV\t12637100\t12639500\tLow Mappability\nchrIV\t13359700\t13362800\tHigh Signal Region\nchrIV\t13548500\t13550500\tHigh Signal Region\nchrIV\t14056400\t14059900\tHigh Signal Region\nchrIV\t14775600\t14782300\tLow Mappability\nchrIV\t15076800\t15082900\tHigh Signal Region\nchrIV\t15408500\t15424900\tLow Mappability\nchrV\t264100\t268100\tHigh Signal Region\nchrV\t1103700\t1106100\tLow Mappability\nchrV\t1637000\t1639900\tHigh Signal Region\nchrV\t3098000\t3100400\tHigh Signal Region\nchrV\t3434100\t3441600\tHigh Signal Region\nchrV\t5278300\t5286800\tHigh Signal Region\nchrV\t6171000\t6183700\tHigh Signal Region\nchrV\t6936700\t6943900\tHigh Signal Region\nchrV\t7912300\t7925700\tHigh Signal Region\nchrV\t7988100\t7993700\tHigh Signal Region\nchrV\t8698700\t8715700\tHigh Signal Region\nchrV\t9423500\t9436100\tHigh Signal Region\nchrV\t10604900\t10613200\tHigh Signal Region\nchrV\t12509100\t12511300\tHigh Signal Region\nchrV\t14765800\t14770600\tHigh Signal Region\nchrV\t16706300\t16710300\tHigh Signal Region\nchrV\t17114600\t17133000\tHigh Signal Region\nchrV\t17307800\t17312400\tHigh Signal Region\nchrV\t17383300\t17395200\tHigh Signal Region\nchrV\t18399500\t18402500\tHigh Signal Region\nchrX\t108300\t115100\tHigh Signal Region\nchrX\t273800\t296200\tHigh Signal Region\nchrX\t1635300\t1645200\tHigh Signal Region\nchrX\t1747400\t1755900\tHigh Signal Region\nchrX\t3006400\t3008800\tHigh Signal Region\nchrX\t4025200\t4056900\tHigh Signal Region\nchrX\t5045000\t5058200\tHigh Signal Region\nchrX\t7076600\t7081600\tHigh Signal Region\nchrX\t9184200\t9189600\tHigh Signal Region\nchrX\t9437700\t9440000\tHigh Signal Region\nchrX\t10360300\t10370000\tHigh Signal Region\nchrX\t11784800\t11790400\tHigh Signal Region\nchrX\t11885700\t11889700\tHigh Signal Region\nchrX\t12275900\t12280400\tHigh Signal Region\nchrX\t14907200\t14910300\tHigh Signal Region\nchrX\t15226200\t15229600\tHigh Signal Region\nchrX\t15806400\t15812100\tLow Mappability\nchrX\t16758000\t16761600\tHigh Signal Region\n" }, { "path": "assets/blacklists/v2.0/dm3-blacklist.v2.bed", "content": "chr2LHet\t43400\t150800\tHigh Signal Region\nchr2LHet\t350800\t368800\tLow Mappability\nchr2L\t47200\t52500\tHigh Signal Region\nchr2L\t66000\t74500\tHigh Signal Region\nchr2L\t154400\t167500\tHigh Signal Region\nchr2L\t221100\t223300\tHigh Signal Region\nchr2L\t471400\t491700\tHigh Signal Region\nchr2L\t2191400\t2201000\tHigh Signal Region\nchr2L\t2749200\t2756400\tHigh Signal Region\nchr2L\t2884100\t2889800\tHigh Signal Region\nchr2L\t3161500\t3164300\tHigh Signal Region\nchr2L\t4937900\t4941000\tHigh Signal Region\nchr2L\t5206500\t5210500\tHigh Signal Region\nchr2L\t5943200\t5949200\tHigh Signal Region\nchr2L\t5976600\t5987500\tHigh Signal Region\nchr2L\t6991400\t6998500\tLow Mappability\nchr2L\t7343400\t7350800\tHigh Signal Region\nchr2L\t9898700\t9903100\tHigh Signal Region\nchr2L\t9973800\t9980900\tLow Mappability\nchr2L\t10333600\t10335600\tHigh Signal Region\nchr2L\t11992000\t12013100\tHigh Signal Region\nchr2L\t12558300\t12565400\tLow Mappability\nchr2L\t13522100\t13527800\tLow Mappability\nchr2L\t14489600\t14491600\tHigh Signal Region\nchr2L\t16267500\t16271800\tHigh Signal Region\nchr2L\t16283800\t16289200\tHigh Signal Region\nchr2L\t16512100\t16526900\tLow Mappability\nchr2L\t18942900\t18945500\tHigh Signal Region\nchr2L\t19570700\t19588100\tHigh Signal Region\nchr2L\t20647200\t20649100\tHigh Signal Region\nchr2L\t21019900\t21024300\tLow Mappability\nchr2L\t21236700\t21238800\tHigh Signal Region\nchr2L\t21416300\t21544000\tHigh Signal Region\nchr2L\t22378300\t22389200\tHigh Signal Region\nchr2L\t22657900\t22670900\tHigh Signal Region\nchr2RHet\t674900\t692100\tLow Mappability\nchr2RHet\t1142300\t1263300\tLow Mappability\nchr2RHet\t1422500\t1435900\tHigh Signal Region\nchr2RHet\t2823000\t2830800\tHigh Signal Region\nchr2RHet\t2924700\t2989000\tHigh Signal Region\nchr2RHet\t3179900\t3183800\tHigh Signal Region\nchr2RHet\t3269500\t3288700\tLow Mappability\nchr2R\t101000\t118400\tHigh Signal Region\nchr2R\t201300\t207900\tHigh Signal Region\nchr2R\t934100\t944600\tHigh Signal Region\nchr2R\t992900\t997600\tHigh Signal Region\nchr2R\t2217200\t2303300\tHigh Signal Region\nchr2R\t2548500\t2551600\tHigh Signal Region\nchr2R\t3123000\t3137600\tHigh Signal Region\nchr2R\t3322500\t3326700\tLow Mappability\nchr2R\t3495700\t3501600\tLow Mappability\nchr2R\t3692900\t3720700\tHigh Signal Region\nchr2R\t3902800\t3905600\tLow Mappability\nchr2R\t4552800\t4555900\tHigh Signal Region\nchr2R\t5367700\t5378100\tLow Mappability\nchr2R\t5430900\t5442200\tHigh Signal Region\nchr2R\t5615200\t5621600\tHigh Signal Region\nchr2R\t6311300\t6318700\tHigh Signal Region\nchr2R\t6364800\t6368500\tHigh Signal Region\nchr2R\t6420800\t6430300\tHigh Signal Region\nchr2R\t6835600\t6843000\tHigh Signal Region\nchr2R\t7538100\t7540600\tHigh Signal Region\nchr2R\t8473600\t8481800\tHigh Signal Region\nchr2R\t8706700\t8712000\tLow Mappability\nchr2R\t8867500\t8873800\tHigh Signal Region\nchr2R\t8883000\t8885600\tHigh Signal Region\nchr2R\t9981000\t9997000\tLow Mappability\nchr2R\t10076400\t10082900\tHigh Signal Region\nchr2R\t10776800\t10785300\tLow Mappability\nchr2R\t11985200\t11992700\tHigh Signal Region\nchr2R\t13034800\t13040100\tLow Mappability\nchr2R\t13344900\t13346800\tHigh Signal Region\nchr2R\t13569800\t13571700\tHigh Signal Region\nchr2R\t14243000\t14260400\tHigh Signal Region\nchr2R\t14463000\t14469700\tLow Mappability\nchr2R\t14745600\t14747800\tLow Mappability\nchr2R\t15616900\t15653700\tHigh Signal Region\nchr2R\t15663700\t15667500\tLow Mappability\nchr2R\t16667200\t16675500\tLow Mappability\nchr2R\t16882700\t16885400\tHigh Signal Region\nchr2R\t17038700\t17049200\tHigh Signal Region\nchr2R\t17532800\t17535100\tHigh Signal Region\nchr2R\t18413300\t18417100\tLow Mappability\nchr2R\t19865400\t19867600\tHigh Signal Region\nchr2R\t20897600\t20900500\tHigh Signal Region\nchr2R\t21144900\t21146700\tLow Mappability\nchr3LHet\t1345100\t1347600\tHigh Signal Region\nchr3LHet\t2162700\t2187800\tHigh Signal Region\nchr3LHet\t2202300\t2209300\tLow Mappability\nchr3LHet\t2244300\t2253000\tLow Mappability\nchr3L\t130400\t133100\tHigh Signal Region\nchr3L\t223200\t226000\tHigh Signal Region\nchr3L\t270300\t272600\tHigh Signal Region\nchr3L\t318400\t320800\tHigh Signal Region\nchr3L\t539500\t544400\tHigh Signal Region\nchr3L\t748200\t750200\tHigh Signal Region\nchr3L\t1334000\t1336300\tHigh Signal Region\nchr3L\t1545400\t1547500\tHigh Signal Region\nchr3L\t1567700\t1570700\tHigh Signal Region\nchr3L\t1793900\t1796200\tHigh Signal Region\nchr3L\t2063400\t2069800\tHigh Signal Region\nchr3L\t2585300\t2590700\tHigh Signal Region\nchr3L\t3059100\t3071600\tHigh Signal Region\nchr3L\t3147900\t3150300\tHigh Signal Region\nchr3L\t3218400\t3227200\tHigh Signal Region\nchr3L\t3896400\t3905700\tHigh Signal Region\nchr3L\t4133100\t4139800\tHigh Signal Region\nchr3L\t5104000\t5117900\tLow Mappability\nchr3L\t7349700\t7355100\tHigh Signal Region\nchr3L\t7662100\t7684600\tHigh Signal Region\nchr3L\t7972100\t7981100\tLow Mappability\nchr3L\t8012400\t8017600\tHigh Signal Region\nchr3L\t8784200\t8790000\tLow Mappability\nchr3L\t9385600\t9395900\tHigh Signal Region\nchr3L\t9415500\t9424500\tHigh Signal Region\nchr3L\t9569100\t9574400\tLow Mappability\nchr3L\t10729500\t10731200\tHigh Signal Region\nchr3L\t11238800\t11246200\tHigh Signal Region\nchr3L\t11479900\t11481800\tHigh Signal Region\nchr3L\t11545300\t11547300\tHigh Signal Region\nchr3L\t11605800\t11612700\tHigh Signal Region\nchr3L\t11955900\t11966000\tHigh Signal Region\nchr3L\t14747500\t14755700\tHigh Signal Region\nchr3L\t14773500\t14784000\tHigh Signal Region\nchr3L\t15134000\t15138400\tHigh Signal Region\nchr3L\t15818200\t15820000\tHigh Signal Region\nchr3L\t16038000\t16046600\tHigh Signal Region\nchr3L\t16639900\t16641900\tHigh Signal Region\nchr3L\t16653500\t16655400\tHigh Signal Region\nchr3L\t17003800\t17006300\tHigh Signal Region\nchr3L\t17636700\t17638700\tHigh Signal Region\nchr3L\t18827000\t18834000\tHigh Signal Region\nchr3L\t19887800\t19909000\tHigh Signal Region\nchr3L\t20391900\t20395600\tHigh Signal Region\nchr3L\t20466800\t20477400\tHigh Signal Region\nchr3L\t20510900\t20513100\tHigh Signal Region\nchr3L\t20808600\t20818200\tHigh Signal Region\nchr3L\t21000400\t21022000\tHigh Signal Region\nchr3L\t21358800\t21371300\tLow Mappability\nchr3L\t22092600\t22099100\tLow Mappability\nchr3L\t22734700\t22738400\tLow Mappability\nchr3L\t22754300\t22760100\tLow Mappability\nchr3L\t23817900\t23833100\tHigh Signal Region\nchr3L\t23935400\t23941300\tLow Mappability\nchr3L\t24447200\t24484400\tLow Mappability\nchr3RHet\t43700\t62000\tHigh Signal Region\nchr3RHet\t1342700\t1348400\tLow Mappability\nchr3RHet\t1508900\t1524800\tLow Mappability\nchr3RHet\t1816700\t1834500\tHigh Signal Region\nchr3RHet\t1947200\t1958800\tHigh Signal Region\nchr3RHet\t2307400\t2309300\tLow Mappability\nchr3R\t228600\t238600\tLow Mappability\nchr3R\t509000\t510400\tHigh Signal Region\nchr3R\t564200\t566200\tHigh Signal Region\nchr3R\t777000\t779000\tHigh Signal Region\nchr3R\t828100\t833700\tHigh Signal Region\nchr3R\t871500\t878800\tLow Mappability\nchr3R\t911600\t914500\tHigh Signal Region\nchr3R\t1076200\t1078200\tHigh Signal Region\nchr3R\t1424600\t1427600\tHigh Signal Region\nchr3R\t1448500\t1451200\tHigh Signal Region\nchr3R\t2230300\t2234000\tHigh Signal Region\nchr3R\t2645100\t2649200\tHigh Signal Region\nchr3R\t2899200\t2916800\tHigh Signal Region\nchr3R\t2933000\t2935200\tHigh Signal Region\nchr3R\t3176400\t3180900\tHigh Signal Region\nchr3R\t3917000\t3932800\tLow Mappability\nchr3R\t4396100\t4400900\tLow Mappability\nchr3R\t4872100\t4884300\tHigh Signal Region\nchr3R\t5242900\t5245900\tHigh Signal Region\nchr3R\t5335200\t5343100\tHigh Signal Region\nchr3R\t5376200\t5378000\tHigh Signal Region\nchr3R\t5415800\t5418000\tHigh Signal Region\nchr3R\t5454700\t5457000\tHigh Signal Region\nchr3R\t5510100\t5537700\tHigh Signal Region\nchr3R\t5697900\t5701200\tHigh Signal Region\nchr3R\t6080700\t6091100\tLow Mappability\nchr3R\t6167400\t6182800\tHigh Signal Region\nchr3R\t6207000\t6215100\tHigh Signal Region\nchr3R\t7583800\t7590800\tHigh Signal Region\nchr3R\t7779600\t7786900\tHigh Signal Region\nchr3R\t8228800\t8230500\tHigh Signal Region\nchr3R\t8290300\t8337000\tHigh Signal Region\nchr3R\t8452400\t8454700\tHigh Signal Region\nchr3R\t9509100\t9511200\tHigh Signal Region\nchr3R\t10109000\t10113200\tHigh Signal Region\nchr3R\t10548800\t10550700\tHigh Signal Region\nchr3R\t10920100\t10922000\tHigh Signal Region\nchr3R\t10956400\t10966900\tHigh Signal Region\nchr3R\t11112800\t11118600\tHigh Signal Region\nchr3R\t11798100\t11800500\tHigh Signal Region\nchr3R\t12054400\t12069200\tHigh Signal Region\nchr3R\t12074500\t12081400\tHigh Signal Region\nchr3R\t12813500\t12821900\tHigh Signal Region\nchr3R\t13506900\t13509400\tHigh Signal Region\nchr3R\t13542200\t13544300\tHigh Signal Region\nchr3R\t13751200\t13753400\tLow Mappability\nchr3R\t14022000\t14025900\tHigh Signal Region\nchr3R\t14962500\t14964700\tLow Mappability\nchr3R\t17121500\t17134300\tHigh Signal Region\nchr3R\t17173800\t17176100\tHigh Signal Region\nchr3R\t17430600\t17445700\tLow Mappability\nchr3R\t17456100\t17459600\tHigh Signal Region\nchr3R\t18275900\t18279300\tHigh Signal Region\nchr3R\t19358600\t19360500\tHigh Signal Region\nchr3R\t19383900\t19386200\tLow Mappability\nchr3R\t19715100\t19717300\tHigh Signal Region\nchr3R\t19902300\t19904500\tLow Mappability\nchr3R\t19929900\t19934800\tHigh Signal Region\nchr3R\t20407300\t20409000\tHigh Signal Region\nchr3R\t20874800\t20877200\tHigh Signal Region\nchr3R\t22922500\t22923900\tHigh Signal Region\nchr3R\t22966200\t22977000\tHigh Signal Region\nchr3R\t23406600\t23408200\tHigh Signal Region\nchr3R\t23551000\t23556900\tLow Mappability\nchr3R\t23682500\t23694400\tLow Mappability\nchr3R\t23894000\t23899900\tLow Mappability\nchr3R\t24151200\t24153300\tHigh Signal Region\nchr3R\t24889000\t24891200\tHigh Signal Region\nchr3R\t25563700\t25565800\tLow Mappability\nchr3R\t25910200\t25912400\tLow Mappability\nchr3R\t26900000\t26906600\tHigh Signal Region\nchr3R\t27041200\t27048400\tHigh Signal Region\nchr3R\t27238900\t27243600\tHigh Signal Region\nchr3R\t27433400\t27437700\tHigh Signal Region\nchr3R\t27572500\t27575000\tHigh Signal Region\nchr3R\t27893200\t27905000\tHigh Signal Region\nchr4\t97100\t102500\tLow Mappability\nchr4\t1278500\t1351800\tHigh Signal Region\nchrXHet\t32400\t43100\tLow Mappability\nchrXHet\t87400\t132300\tHigh Signal Region\nchrX\t0\t18800\tHigh Signal Region\nchrX\t322300\t328700\tLow Mappability\nchrX\t1251600\t1275300\tHigh Signal Region\nchrX\t2012900\t2033200\tHigh Signal Region\nchrX\t2504400\t2514500\tLow Mappability\nchrX\t2683600\t2687100\tHigh Signal Region\nchrX\t2964000\t2975200\tLow Mappability\nchrX\t3308900\t3315500\tLow Mappability\nchrX\t3620500\t3624500\tLow Mappability\nchrX\t3684200\t3699100\tHigh Signal Region\nchrX\t3834600\t3844200\tHigh Signal Region\nchrX\t4812700\t4831100\tHigh Signal Region\nchrX\t4884100\t4891200\tHigh Signal Region\nchrX\t6065700\t6073000\tHigh Signal Region\nchrX\t7019400\t7028400\tHigh Signal Region\nchrX\t7374800\t7376400\tHigh Signal Region\nchrX\t7791300\t7793200\tHigh Signal Region\nchrX\t7949800\t7957700\tHigh Signal Region\nchrX\t8186900\t8190800\tHigh Signal Region\nchrX\t8821300\t8824300\tLow Mappability\nchrX\t9517700\t9520200\tHigh Signal Region\nchrX\t10657000\t10663600\tHigh Signal Region\nchrX\t10990100\t10997200\tLow Mappability\nchrX\t11206200\t11212900\tHigh Signal Region\nchrX\t11473900\t11494400\tHigh Signal Region\nchrX\t11527500\t11542700\tLow Mappability\nchrX\t11607000\t11609700\tHigh Signal Region\nchrX\t12824600\t12831700\tLow Mappability\nchrX\t15705000\t15706900\tHigh Signal Region\nchrX\t15907200\t15953600\tHigh Signal Region\nchrX\t18323300\t18329000\tLow Mappability\nchrX\t18676100\t18682200\tHigh Signal Region\nchrX\t18757000\t18759500\tHigh Signal Region\nchrX\t19247000\t19252800\tLow Mappability\nchrX\t20070100\t20101800\tHigh Signal Region\nchrX\t21611900\t21630800\tHigh Signal Region\nchrX\t21833900\t21835900\tHigh Signal Region\nchrX\t21924100\t21927700\tLow Mappability\nchrYHet\t125600\t138300\tLow Mappability\nchrYHet\t195300\t225100\tHigh Signal Region\n" }, { "path": "assets/blacklists/v2.0/dm6-blacklist.v2.bed", "content": "chr2L\t154500\t167500\tHigh Signal Region\nchr2L\t348000\t365800\tHigh Signal Region\nchr2L\t471400\t482200\tHigh Signal Region\nchr2L\t2191400\t2200900\tHigh Signal Region\nchr2L\t2749200\t2756400\tHigh Signal Region\nchr2L\t3161500\t3164200\tHigh Signal Region\nchr2L\t4536500\t4544800\tHigh Signal Region\nchr2L\t4938100\t4941000\tHigh Signal Region\nchr2L\t5206500\t5210500\tHigh Signal Region\nchr2L\t5827800\t5836700\tHigh Signal Region\nchr2L\t5976700\t5987500\tHigh Signal Region\nchr2L\t7343400\t7349300\tHigh Signal Region\nchr2L\t9898700\t9902900\tHigh Signal Region\nchr2L\t11316200\t11317600\tHigh Signal Region\nchr2L\t11992200\t12013200\tHigh Signal Region\nchr2L\t16267500\t16271800\tHigh Signal Region\nchr2L\t16283900\t16289200\tHigh Signal Region\nchr2L\t18942900\t18945600\tHigh Signal Region\nchr2L\t20647200\t20649100\tHigh Signal Region\nchr2L\t21236600\t21238800\tHigh Signal Region\nchr2L\t21415900\t21544200\tHigh Signal Region\nchr2L\t21653300\t21656300\tHigh Signal Region\nchr2L\t22409400\t22479400\tHigh Signal Region\nchr2L\t22488500\t22506800\tHigh Signal Region\nchr2L\t22765200\t22909700\tHigh Signal Region\nchr2L\t23096400\t23122300\tHigh Signal Region\nchr2L\t23353200\t23387900\tHigh Signal Region\nchr2L\t23511900\t23513700\tHigh Signal Region\nchr2R\t0\t14900\tHigh Signal Region\nchr2R\t744200\t878700\tLow Mappability\nchr2R\t1492900\t1530200\tHigh Signal Region\nchr2R\t1818200\t1840700\tLow Mappability\nchr2R\t1931800\t1949300\tLow Mappability\nchr2R\t2158800\t2169900\tHigh Signal Region\nchr2R\t2218200\t2238300\tHigh Signal Region\nchr2R\t2652000\t2665400\tHigh Signal Region\nchr2R\t3601600\t3603200\tHigh Signal Region\nchr2R\t3718500\t3775000\tHigh Signal Region\nchr2R\t3943700\t3998100\tHigh Signal Region\nchr2R\t4274200\t4275400\tHigh Signal Region\nchr2R\t4863000\t4884000\tLow Mappability\nchr2R\t5046600\t5057100\tHigh Signal Region\nchr2R\t5105500\t5110000\tHigh Signal Region\nchr2R\t7235700\t7250000\tHigh Signal Region\nchr2R\t8015400\t8018000\tLow Mappability\nchr2R\t10177000\t10186000\tHigh Signal Region\nchr2R\t10948100\t10955500\tHigh Signal Region\nchr2R\t12586100\t12594400\tHigh Signal Region\nchr2R\t14188900\t14195500\tHigh Signal Region\nchr2R\t18575400\t18582400\tHigh Signal Region\nchr2R\t19715900\t19766800\tHigh Signal Region\nchr2R\t21151200\t21153700\tHigh Signal Region\nchr2R\t24177300\t24184700\tHigh Signal Region\nchr2R\t25257500\t25286800\tHigh Signal Region\nchr3L\t2063300\t2069900\tHigh Signal Region\nchr3L\t2447600\t2456600\tHigh Signal Region\nchr3L\t3899000\t3903000\tHigh Signal Region\nchr3L\t7669000\t7691700\tHigh Signal Region\nchr3L\t7978900\t7987800\tLow Mappability\nchr3L\t8019300\t8024500\tHigh Signal Region\nchr3L\t11968300\t11972800\tHigh Signal Region\nchr3L\t16596900\t16607900\tHigh Signal Region\nchr3L\t18833900\t18840800\tHigh Signal Region\nchr3L\t20473700\t20484300\tHigh Signal Region\nchr3L\t20815500\t20825000\tHigh Signal Region\nchr3L\t22099400\t22106200\tLow Mappability\nchr3L\t22761300\t22767100\tHigh Signal Region\nchr3L\t23111800\t23118300\tHigh Signal Region\nchr3L\t23825700\t23839600\tHigh Signal Region\nchr3L\t24384500\t24445600\tHigh Signal Region\nchr3L\t24576600\t24669400\tHigh Signal Region\nchr3L\t25051000\t25054100\tHigh Signal Region\nchr3L\t25129300\t25135900\tHigh Signal Region\nchr3L\t25962100\t25964900\tHigh Signal Region\nchr3L\t26877500\t27082600\tHigh Signal Region\nchr3L\t27137300\t27140300\tLow Mappability\nchr3L\t27471600\t27649900\tHigh Signal Region\nchr3R\t0\t32600\tHigh Signal Region\nchr3R\t43000\t82600\tHigh Signal Region\nchr3R\t236900\t285000\tHigh Signal Region\nchr3R\t499300\t529400\tHigh Signal Region\nchr3R\t1271100\t1279000\tLow Mappability\nchr3R\t1369500\t1390500\tLow Mappability\nchr3R\t2619300\t2623900\tHigh Signal Region\nchr3R\t2749700\t2768300\tHigh Signal Region\nchr3R\t2775800\t2782000\tLow Mappability\nchr3R\t3032500\t3058100\tHigh Signal Region\nchr3R\t3087400\t3136500\tHigh Signal Region\nchr3R\t3168900\t3171300\tLow Mappability\nchr3R\t3697900\t3702100\tHigh Signal Region\nchr3R\t4738400\t4740500\tHigh Signal Region\nchr3R\t4951200\t4953300\tHigh Signal Region\nchr3R\t5002300\t5009200\tHigh Signal Region\nchr3R\t5045500\t5053200\tLow Mappability\nchr3R\t5085900\t5088400\tHigh Signal Region\nchr3R\t5598800\t5602000\tHigh Signal Region\nchr3R\t5622700\t5625500\tHigh Signal Region\nchr3R\t6404600\t6408200\tHigh Signal Region\nchr3R\t6819500\t6823400\tHigh Signal Region\nchr3R\t7073500\t7076300\tHigh Signal Region\nchr3R\t7107300\t7109400\tHigh Signal Region\nchr3R\t8091300\t8107100\tLow Mappability\nchr3R\t8570200\t8575500\tLow Mappability\nchr3R\t9046400\t9058600\tHigh Signal Region\nchr3R\t9351800\t9354100\tHigh Signal Region\nchr3R\t9417100\t9420200\tHigh Signal Region\nchr3R\t9509400\t9517300\tHigh Signal Region\nchr3R\t9550400\t9552400\tHigh Signal Region\nchr3R\t9590000\t9592300\tHigh Signal Region\nchr3R\t9629000\t9631300\tHigh Signal Region\nchr3R\t9684500\t9712000\tHigh Signal Region\nchr3R\t10255100\t10265400\tLow Mappability\nchr3R\t10341700\t10357100\tHigh Signal Region\nchr3R\t10377600\t10389400\tHigh Signal Region\nchr3R\t11758100\t11765200\tHigh Signal Region\nchr3R\t11948900\t11961000\tHigh Signal Region\nchr3R\t12464500\t12511200\tHigh Signal Region\nchr3R\t12626600\t12629000\tHigh Signal Region\nchr3R\t13683300\t13685500\tHigh Signal Region\nchr3R\t14283200\t14287500\tHigh Signal Region\nchr3R\t14696300\t14698100\tHigh Signal Region\nchr3R\t14723000\t14725100\tHigh Signal Region\nchr3R\t15094300\t15096400\tHigh Signal Region\nchr3R\t15130700\t15135000\tHigh Signal Region\nchr3R\t15286000\t15292900\tHigh Signal Region\nchr3R\t15972300\t15974800\tHigh Signal Region\nchr3R\t16224000\t16243500\tHigh Signal Region\nchr3R\t16248800\t16255800\tHigh Signal Region\nchr3R\t16987900\t16996000\tHigh Signal Region\nchr3R\t17681200\t17683700\tHigh Signal Region\nchr3R\t17716400\t17718700\tHigh Signal Region\nchr3R\t17925400\t17927800\tHigh Signal Region\nchr3R\t18196300\t18200300\tHigh Signal Region\nchr3R\t21295600\t21308400\tHigh Signal Region\nchr3R\t21348100\t21350400\tHigh Signal Region\nchr3R\t21604900\t21620100\tLow Mappability\nchr3R\t21630200\t21633900\tHigh Signal Region\nchr3R\t22450200\t22453500\tHigh Signal Region\nchr3R\t23889300\t23891600\tHigh Signal Region\nchr3R\t24076500\t24078900\tLow Mappability\nchr3R\t24104200\t24109100\tHigh Signal Region\nchr3R\t24581500\t24590000\tHigh Signal Region\nchr3R\t25049000\t25051400\tHigh Signal Region\nchr3R\t27140500\t27151400\tHigh Signal Region\nchr3R\t27580600\t27582500\tHigh Signal Region\nchr3R\t27856800\t27868700\tLow Mappability\nchr3R\t28325400\t28327600\tHigh Signal Region\nchr3R\t29063200\t29065500\tHigh Signal Region\nchr3R\t29737800\t29740200\tLow Mappability\nchr3R\t30084400\t30086800\tLow Mappability\nchr3R\t31215500\t31222700\tHigh Signal Region\nchr3R\t31413100\t31417800\tHigh Signal Region\nchr3R\t31607700\t31611900\tHigh Signal Region\nchr3R\t31746800\t31749300\tHigh Signal Region\nchr3R\t32067500\t32079300\tLow Mappability\nchr4\t1274800\t1348100\tHigh Signal Region\nchrX\t0\t122400\tHigh Signal Region\nchrX\t201200\t246300\tHigh Signal Region\nchrX\t2610300\t2617700\tHigh Signal Region\nchrX\t4921800\t4937000\tHigh Signal Region\nchrX\t4990100\t4997200\tHigh Signal Region\nchrX\t7125300\t7134300\tHigh Signal Region\nchrX\t8292900\t8296800\tHigh Signal Region\nchrX\t11487700\t11494000\tHigh Signal Region\nchrX\t16013200\t16059600\tHigh Signal Region\nchrX\t19907800\t19958400\tHigh Signal Region\nchrX\t22257600\t22401900\tHigh Signal Region\nchrX\t22432100\t22434100\tHigh Signal Region\nchrX\t22996400\t23003500\tHigh Signal Region\nchrX\t23019600\t23022700\tLow Mappability\nchrX\t23204900\t23285000\tHigh Signal Region\nchrX\t23290700\t23442900\tHigh Signal Region\nchrX\t23450200\t23465000\tLow Mappability\nchrX\t23471400\t23489900\tLow Mappability\nchrX\t23512700\t23539400\tLow Mappability\nchrY\t113900\t125600\tHigh Signal Region\nchrY\t131500\t155700\tHigh Signal Region\nchrY\t199800\t248700\tHigh Signal Region\nchrY\t313600\t325400\tHigh Signal Region\nchrY\t641400\t654100\tLow Mappability\nchrY\t1456900\t1693500\tHigh Signal Region\nchrY\t3641100\t3667300\tHigh Signal Region\n" }, { "path": "assets/blacklists/v2.0/hg19-blacklist.v2.bed", "content": "chr10\t38726200\t42489100\tHigh Signal Region\nchr10\t42524900\t42819200\tHigh Signal Region\nchr10\t98560400\t98562500\tHigh Signal Region\nchr10\t135437600\t135534700\tHigh Signal Region\nchr11\t0\t196300\tHigh Signal Region\nchr11\t584400\t586500\tHigh Signal Region\nchr11\t964000\t966100\tLow Mappability\nchr11\t1015700\t1019100\tHigh Signal Region\nchr11\t1088800\t1094300\tHigh Signal Region\nchr11\t1141100\t1214300\tHigh Signal Region\nchr11\t3674100\t3676900\tLow Mappability\nchr11\t6830800\t6832700\tHigh Signal Region\nchr11\t10528500\t10532700\tLow Mappability\nchr11\t11267200\t11269500\tHigh Signal Region\nchr11\t48700000\t48964800\tHigh Signal Region\nchr11\t50505600\t50523400\tHigh Signal Region\nchr11\t50635500\t51200100\tHigh Signal Region\nchr11\t51244400\t51289000\tHigh Signal Region\nchr11\t51566300\t54834600\tHigh Signal Region\nchr11\t54876800\t55028400\tHigh Signal Region\nchr11\t62606300\t62651300\tHigh Signal Region\nchr11\t77596600\t77601800\tHigh Signal Region\nchr11\t85172700\t85196400\tHigh Signal Region\nchr11\t93965500\t93984500\tHigh Signal Region\nchr11\t100156600\t100162500\tHigh Signal Region\nchr11\t102239800\t102246000\tHigh Signal Region\nchr11\t129208700\t129234600\tHigh Signal Region\nchr12\t0\t187000\tHigh Signal Region\nchr12\t479900\t531700\tHigh Signal Region\nchr12\t2364000\t2366100\tHigh Signal Region\nchr12\t2628700\t2649700\tLow Mappability\nchr12\t4618500\t4624000\tHigh Signal Region\nchr12\t6037400\t6042400\tLow Mappability\nchr12\t7705200\t7717600\tHigh Signal Region\nchr12\t19881600\t19887000\tHigh Signal Region\nchr12\t20703400\t20705400\tHigh Signal Region\nchr12\t20921400\t20928000\tHigh Signal Region\nchr12\t34371700\t34400000\tHigh Signal Region\nchr12\t34574500\t34576400\tLow Mappability\nchr12\t34761600\t37887400\tHigh Signal Region\nchr12\t37989200\t38259900\tHigh Signal Region\nchr12\t38330900\t38375800\tLow Mappability\nchr12\t38443400\t38503500\tHigh Signal Region\nchr12\t38534900\t38537700\tHigh Signal Region\nchr12\t41756500\t41758400\tLow Mappability\nchr12\t54205000\t54206900\tHigh Signal Region\nchr12\t66867700\t66872600\tHigh Signal Region\nchr12\t69385000\t69391000\tHigh Signal Region\nchr12\t70167100\t70204100\tHigh Signal Region\nchr12\t75903800\t75916900\tHigh Signal Region\nchr12\t93771900\t93808100\tHigh Signal Region\nchr12\t97117400\t97122300\tHigh Signal Region\nchr12\t101540100\t101549000\tHigh Signal Region\nchr12\t113517400\t113519300\tHigh Signal Region\nchr12\t125394300\t125426400\tLow Mappability\nchr12\t126072900\t126074800\tLow Mappability\nchr12\t127649500\t127651900\tHigh Signal Region\nchr12\t130863600\t130878600\tHigh Signal Region\nchr12\t132060500\t132074200\tHigh Signal Region\nchr12\t133343000\t133345000\tHigh Signal Region\nchr12\t133825400\t133851800\tLow Mappability\nchr13\t0\t19194200\tHigh Signal Region\nchr13\t19344200\t19447900\tHigh Signal Region\nchr13\t19641600\t19652000\tHigh Signal Region\nchr13\t19677800\t19683400\tHigh Signal Region\nchr13\t19711000\t19713300\tHigh Signal Region\nchr13\t20051500\t20077000\tLow Mappability\nchr13\t20150200\t20228600\tHigh Signal Region\nchr13\t20352400\t20372400\tHigh Signal Region\nchr13\t20966500\t20984700\tHigh Signal Region\nchr13\t21068500\t21072900\tHigh Signal Region\nchr13\t21816000\t21826300\tHigh Signal Region\nchr13\t21950600\t21952600\tHigh Signal Region\nchr13\t22125500\t22129800\tHigh Signal Region\nchr13\t22429700\t22436000\tHigh Signal Region\nchr13\t23095400\t23108300\tLow Mappability\nchr13\t24900500\t24932100\tHigh Signal Region\nchr13\t25122300\t25128600\tHigh Signal Region\nchr13\t26467000\t26472000\tLow Mappability\nchr13\t27977100\t28035000\tHigh Signal Region\nchr13\t28710500\t28733700\tHigh Signal Region\nchr13\t29767400\t29769600\tHigh Signal Region\nchr13\t30215700\t30247400\tLow Mappability\nchr13\t30397900\t30426100\tHigh Signal Region\nchr13\t30787000\t30790100\tHigh Signal Region\nchr13\t30819100\t30845000\tHigh Signal Region\nchr13\t31412800\t31440600\tHigh Signal Region\nchr13\t31521900\t31523400\tHigh Signal Region\nchr13\t31916200\t31920700\tHigh Signal Region\nchr13\t31970100\t31971800\tHigh Signal Region\nchr13\t33109900\t33114000\tHigh Signal Region\nchr13\t33149400\t33182100\tHigh Signal Region\nchr13\t33441700\t33443500\tLow Mappability\nchr13\t34163100\t34164900\tHigh Signal Region\nchr13\t34558900\t34565000\tHigh Signal Region\nchr13\t35054300\t35073100\tHigh Signal Region\nchr13\t35656000\t35664300\tHigh Signal Region\nchr13\t35977500\t36001800\tHigh Signal Region\nchr13\t36531200\t36553700\tHigh Signal Region\nchr13\t36582200\t36588400\tHigh Signal Region\nchr13\t37723900\t37730200\tHigh Signal Region\nchr13\t38396200\t38402300\tLow Mappability\nchr13\t38640900\t38645800\tHigh Signal Region\nchr13\t38687300\t38721000\tHigh Signal Region\nchr13\t40422400\t40427800\tHigh Signal Region\nchr13\t40560400\t40580700\tLow Mappability\nchr13\t40920400\t40936600\tLow Mappability\nchr13\t41309000\t41315200\tLow Mappability\nchr13\t41343800\t41416000\tHigh Signal Region\nchr13\t41438500\t41477300\tHigh Signal Region\nchr13\t41530500\t41640400\tHigh Signal Region\nchr13\t42108700\t42114800\tHigh Signal Region\nchr13\t42165400\t42243300\tHigh Signal Region\nchr13\t42321000\t42324400\tHigh Signal Region\nchr13\t42445300\t42448800\tHigh Signal Region\nchr13\t42479700\t42497900\tHigh Signal Region\nchr13\t42928200\t42961000\tLow Mappability\nchr13\t42999000\t43005200\tLow Mappability\nchr13\t43128800\t43132300\tHigh Signal Region\nchr13\t43734900\t43740400\tHigh Signal Region\nchr13\t44391900\t44409800\tLow Mappability\nchr13\t44540800\t44550400\tHigh Signal Region\nchr13\t45491200\t45494100\tHigh Signal Region\nchr13\t46190900\t46244300\tHigh Signal Region\nchr13\t47322400\t47347500\tLow Mappability\nchr13\t47795600\t47799800\tLow Mappability\nchr13\t48288000\t48379400\tHigh Signal Region\nchr13\t48551900\t48636200\tHigh Signal Region\nchr13\t48776900\t48781200\tHigh Signal Region\nchr13\t48955700\t49045800\tHigh Signal Region\nchr13\t49587600\t49593700\tHigh Signal Region\nchr13\t49726300\t49750700\tHigh Signal Region\nchr13\t50655600\t50674000\tHigh Signal Region\nchr13\t50739500\t50760400\tHigh Signal Region\nchr13\t50804000\t50831700\tHigh Signal Region\nchr13\t51045000\t51047900\tLow Mappability\nchr13\t51069400\t51148800\tHigh Signal Region\nchr13\t51538700\t51562300\tHigh Signal Region\nchr13\t51643200\t51654900\tHigh Signal Region\nchr13\t52056600\t52177400\tHigh Signal Region\nchr13\t52209900\t52311100\tHigh Signal Region\nchr13\t52628400\t52634200\tLow Mappability\nchr13\t52767000\t52908600\tHigh Signal Region\nchr13\t53056600\t53198500\tHigh Signal Region\nchr13\t53667700\t53672500\tLow Mappability\nchr13\t54170800\t54195600\tHigh Signal Region\nchr13\t55314400\t55316200\tLow Mappability\nchr13\t55924900\t55928900\tLow Mappability\nchr13\t56386000\t56387700\tLow Mappability\nchr13\t57149500\t57152400\tHigh Signal Region\nchr13\t57613800\t57615800\tLow Mappability\nchr13\t57713200\t57748000\tHigh Signal Region\nchr13\t57793400\t57794800\tHigh Signal Region\nchr13\t57929500\t57933400\tLow Mappability\nchr13\t58055700\t58068300\tHigh Signal Region\nchr13\t58756200\t58759000\tHigh Signal Region\nchr13\t59246600\t59252600\tLow Mappability\nchr13\t60399100\t60401600\tLow Mappability\nchr13\t60558600\t60561900\tLow Mappability\nchr13\t60819900\t60825800\tHigh Signal Region\nchr13\t60868000\t60870400\tLow Mappability\nchr13\t61508300\t61510400\tHigh Signal Region\nchr13\t62142000\t62143900\tLow Mappability\nchr13\t62379800\t62381800\tHigh Signal Region\nchr13\t62407700\t62419700\tHigh Signal Region\nchr13\t63602300\t63649700\tHigh Signal Region\nchr13\t64291000\t64343600\tLow Mappability\nchr13\t64395200\t64410800\tLow Mappability\nchr13\t66567000\t66569000\tLow Mappability\nchr13\t66827800\t66833700\tHigh Signal Region\nchr13\t67311600\t67317700\tLow Mappability\nchr13\t67350200\t67352500\tHigh Signal Region\nchr13\t68136600\t68139600\tLow Mappability\nchr13\t68254200\t68260100\tHigh Signal Region\nchr13\t68566600\t68570000\tHigh Signal Region\nchr13\t68901600\t68915400\tHigh Signal Region\nchr13\t70357600\t70362900\tLow Mappability\nchr13\t70783800\t70789000\tHigh Signal Region\nchr13\t71751300\t71752700\tHigh Signal Region\nchr13\t71958500\t71963800\tHigh Signal Region\nchr13\t72799900\t72802600\tHigh Signal Region\nchr13\t73184400\t73190500\tHigh Signal Region\nchr13\t74027000\t74033300\tHigh Signal Region\nchr13\t74202200\t74220800\tHigh Signal Region\nchr13\t74809900\t74816100\tHigh Signal Region\nchr13\t75111000\t75116700\tHigh Signal Region\nchr13\t75606300\t75608100\tLow Mappability\nchr13\t75653600\t75655800\tHigh Signal Region\nchr13\t75815200\t75821400\tHigh Signal Region\nchr13\t76251800\t76322500\tHigh Signal Region\nchr13\t76528000\t76532300\tHigh Signal Region\nchr13\t76841900\t76843700\tHigh Signal Region\nchr13\t77119100\t77122400\tLow Mappability\nchr13\t77179200\t77192700\tLow Mappability\nchr13\t77773200\t77779300\tHigh Signal Region\nchr13\t78250500\t78260900\tLow Mappability\nchr13\t78453800\t78455300\tHigh Signal Region\nchr13\t78857200\t78859700\tHigh Signal Region\nchr13\t79087100\t79105000\tHigh Signal Region\nchr13\t79590600\t79592200\tHigh Signal Region\nchr13\t79809800\t79811600\tHigh Signal Region\nchr13\t80391100\t80420000\tHigh Signal Region\nchr13\t80726100\t80730600\tLow Mappability\nchr13\t81490500\t81492700\tLow Mappability\nchr13\t81638000\t81651500\tHigh Signal Region\nchr13\t82132700\t82135500\tLow Mappability\nchr13\t82322400\t82327400\tHigh Signal Region\nchr13\t82619500\t82625600\tLow Mappability\nchr13\t82805900\t82809300\tHigh Signal Region\nchr13\t83315600\t83317200\tLow Mappability\nchr13\t84095600\t84097700\tHigh Signal Region\nchr13\t84535300\t84540600\tHigh Signal Region\nchr13\t85075900\t85078300\tLow Mappability\nchr13\t85299500\t85302300\tHigh Signal Region\nchr13\t85695400\t85703500\tHigh Signal Region\nchr13\t86143500\t86147200\tLow Mappability\nchr13\t86485900\t86502200\tLow Mappability\nchr13\t86572000\t86573600\tHigh Signal Region\nchr13\t87297900\t87303700\tHigh Signal Region\nchr13\t88351600\t88353900\tHigh Signal Region\nchr13\t89335000\t89337000\tLow Mappability\nchr13\t89482500\t89486800\tLow Mappability\nchr13\t89740300\t89746300\tLow Mappability\nchr13\t91181200\t91182800\tLow Mappability\nchr13\t91305800\t91322300\tLow Mappability\nchr13\t92256000\t92259400\tHigh Signal Region\nchr13\t92622900\t92628600\tHigh Signal Region\nchr13\t93127200\t93129400\tLow Mappability\nchr13\t93170900\t93175000\tHigh Signal Region\nchr13\t94140200\t94148600\tHigh Signal Region\nchr13\t95024400\t95030600\tLow Mappability\nchr13\t95471000\t95472500\tLow Mappability\nchr13\t95561600\t95563600\tHigh Signal Region\nchr13\t96217900\t96220200\tHigh Signal Region\nchr13\t96377900\t96393100\tHigh Signal Region\nchr13\t96481000\t96493700\tHigh Signal Region\nchr13\t96556500\t96572100\tHigh Signal Region\nchr13\t96616700\t96633300\tLow Mappability\nchr13\t96699300\t96705200\tHigh Signal Region\nchr13\t97807500\t97812400\tHigh Signal Region\nchr13\t97873500\t98016000\tHigh Signal Region\nchr13\t98083600\t98086200\tHigh Signal Region\nchr13\t98256400\t98266100\tLow Mappability\nchr13\t99386700\t99407200\tHigh Signal Region\nchr13\t100970400\t100973100\tHigh Signal Region\nchr13\t101327900\t101356500\tLow Mappability\nchr13\t102191500\t102196900\tHigh Signal Region\nchr13\t102250800\t102254200\tHigh Signal Region\nchr13\t102293700\t102296000\tHigh Signal Region\nchr13\t102560800\t102562600\tHigh Signal Region\nchr13\t103174700\t103180600\tHigh Signal Region\nchr13\t103770000\t103772400\tHigh Signal Region\nchr13\t104155400\t104159600\tHigh Signal Region\nchr13\t105306100\t105307700\tLow Mappability\nchr13\t105609500\t105613300\tHigh Signal Region\nchr13\t105951400\t105953800\tLow Mappability\nchr13\t106035100\t106040800\tLow Mappability\nchr13\t106536800\t106542400\tHigh Signal Region\nchr13\t106651900\t106669100\tHigh Signal Region\nchr13\t106866200\t106872100\tHigh Signal Region\nchr13\t107430500\t107436700\tHigh Signal Region\nchr13\t108868800\t108909300\tLow Mappability\nchr13\t109162700\t109168900\tHigh Signal Region\nchr13\t110075500\t110098100\tLow Mappability\nchr13\t110691900\t110705300\tHigh Signal Region\nchr13\t111036900\t111039000\tHigh Signal Region\nchr13\t111107500\t111163000\tHigh Signal Region\nchr13\t111512100\t111527200\tHigh Signal Region\nchr13\t111959100\t111964000\tHigh Signal Region\nchr13\t111992000\t111994500\tLow Mappability\nchr13\t112148400\t112153300\tHigh Signal Region\nchr13\t112628400\t112630400\tHigh Signal Region\nchr13\t112668600\t112670300\tHigh Signal Region\nchr13\t112931200\t112973400\tHigh Signal Region\nchr13\t113179900\t113244400\tHigh Signal Region\nchr13\t113319400\t113321900\tHigh Signal Region\nchr13\t113440500\t113444300\tHigh Signal Region\nchr13\t113526200\t113540600\tHigh Signal Region\nchr13\t113765500\t113767700\tHigh Signal Region\nchr13\t113916300\t113951000\tLow Mappability\nchr13\t114089500\t114102600\tHigh Signal Region\nchr13\t114191600\t114218700\tHigh Signal Region\nchr13\t114247100\t114280800\tHigh Signal Region\nchr13\t114452900\t114520000\tHigh Signal Region\nchr13\t114553300\t114571100\tHigh Signal Region\nchr13\t114601800\t114772500\tHigh Signal Region\nchr13\t114848900\t114852600\tHigh Signal Region\nchr14\t0\t20303800\tHigh Signal Region\nchr14\t27098600\t27104100\tHigh Signal Region\nchr14\t32263100\t32280800\tHigh Signal Region\nchr14\t32350600\t32352500\tHigh Signal Region\nchr14\t32934800\t32955200\tLow Mappability\nchr14\t35006400\t35031800\tLow Mappability\nchr14\t36416700\t36419200\tHigh Signal Region\nchr14\t39980200\t39995800\tHigh Signal Region\nchr14\t54700600\t54706600\tHigh Signal Region\nchr14\t67508000\t67534600\tHigh Signal Region\nchr14\t80556900\t80561000\tHigh Signal Region\nchr14\t86540300\t86577300\tHigh Signal Region\nchr14\t87058300\t87078200\tHigh Signal Region\nchr14\t87879900\t87894500\tHigh Signal Region\nchr14\t88236600\t88243300\tHigh Signal Region\nchr14\t90340400\t90342300\tHigh Signal Region\nchr14\t102140800\t102142700\tHigh Signal Region\nchr14\t105681400\t105707200\tHigh Signal Region\nchr14\t106034900\t106185200\tHigh Signal Region\nchr14\t107151000\t107176900\tHigh Signal Region\nchr15\t0\t20166200\tHigh Signal Region\nchr15\t20200400\t22365100\tHigh Signal Region\nchr15\t22387400\t22749100\tLow Mappability\nchr15\t23266700\t23612800\tHigh Signal Region\nchr15\t26002700\t26004600\tLow Mappability\nchr15\t28538400\t28956300\tHigh Signal Region\nchr15\t30358500\t30919300\tHigh Signal Region\nchr15\t31136500\t31143800\tLow Mappability\nchr15\t32445900\t32915200\tHigh Signal Region\nchr15\t56603300\t56608500\tHigh Signal Region\nchr15\t69255900\t69257800\tHigh Signal Region\nchr15\t72085400\t72090500\tHigh Signal Region\nchr15\t72923800\t72979000\tLow Mappability\nchr15\t74357800\t74398000\tHigh Signal Region\nchr15\t75546200\t75592100\tHigh Signal Region\nchr15\t77991000\t77993000\tHigh Signal Region\nchr15\t82582300\t83213900\tHigh Signal Region\nchr15\t84835000\t85142500\tHigh Signal Region\nchr15\t85732700\t85814600\tHigh Signal Region\nchr15\t102283600\t102305300\tLow Mappability\nchr15\t102411600\t102531300\tHigh Signal Region\nchr16\t32923000\t33427100\tHigh Signal Region\nchr16\t33726300\t34197900\tHigh Signal Region\nchr16\t35191100\t46501300\tHigh Signal Region\nchr16\t90155800\t90354700\tLow Mappability\nchr17\t66700\t167600\tHigh Signal Region\nchr17\t964700\t969400\tHigh Signal Region\nchr17\t1210900\t1236400\tLow Mappability\nchr17\t4734800\t4736700\tLow Mappability\nchr17\t18928600\t19140800\tHigh Signal Region\nchr17\t21492100\t21686000\tHigh Signal Region\nchr17\t21901400\t21908600\tHigh Signal Region\nchr17\t22019700\t22024900\tHigh Signal Region\nchr17\t22207000\t25341300\tHigh Signal Region\nchr17\t30264500\t30277600\tHigh Signal Region\nchr17\t31148500\t31150800\tHigh Signal Region\nchr17\t33477200\t33479300\tHigh Signal Region\nchr17\t34476000\t34812200\tLow Mappability\nchr17\t36253600\t36406900\tHigh Signal Region\nchr17\t41378900\t41402100\tHigh Signal Region\nchr17\t41432200\t41467700\tHigh Signal Region\nchr17\t43588700\t43718700\tHigh Signal Region\nchr17\t45108700\t45130400\tLow Mappability\nchr17\t45211900\t45283300\tHigh Signal Region\nchr17\t45612500\t45671300\tLow Mappability\nchr17\t51182300\t51184600\tLow Mappability\nchr17\t64794200\t64796200\tLow Mappability\nchr17\t78717100\t78719200\tLow Mappability\nchr17\t81151700\t81195200\tLow Mappability\nchr18\t0\t127000\tHigh Signal Region\nchr18\t952000\t976900\tHigh Signal Region\nchr18\t2247200\t2253300\tHigh Signal Region\nchr18\t2841300\t2866100\tLow Mappability\nchr18\t6687500\t6705800\tHigh Signal Region\nchr18\t12134400\t12227800\tHigh Signal Region\nchr18\t14163200\t14270800\tHigh Signal Region\nchr18\t15139700\t15271400\tHigh Signal Region\nchr18\t15293900\t18552900\tHigh Signal Region\nchr18\t19792100\t19813600\tHigh Signal Region\nchr18\t20109800\t20115600\tHigh Signal Region\nchr18\t20388600\t20400600\tHigh Signal Region\nchr18\t27088800\t27090300\tHigh Signal Region\nchr18\t28927900\t28933700\tHigh Signal Region\nchr18\t30436500\t30442100\tHigh Signal Region\nchr18\t32114600\t32137900\tHigh Signal Region\nchr18\t32924100\t32938700\tHigh Signal Region\nchr18\t33196300\t33213600\tHigh Signal Region\nchr18\t33342300\t33346200\tHigh Signal Region\nchr18\t38424600\t38428200\tHigh Signal Region\nchr18\t42024800\t42028200\tHigh Signal Region\nchr18\t42607900\t42611000\tHigh Signal Region\nchr18\t44125300\t44127400\tHigh Signal Region\nchr18\t44503000\t44515000\tHigh Signal Region\nchr18\t44541400\t44558200\tHigh Signal Region\nchr18\t45378700\t45380700\tLow Mappability\nchr18\t46175800\t46204100\tHigh Signal Region\nchr18\t46572200\t46634900\tHigh Signal Region\nchr18\t47297100\t47302900\tHigh Signal Region\nchr18\t50318200\t50320200\tHigh Signal Region\nchr18\t52710600\t52712900\tHigh Signal Region\nchr18\t53382700\t53388400\tHigh Signal Region\nchr18\t54391800\t54393600\tHigh Signal Region\nchr18\t60853700\t60886800\tHigh Signal Region\nchr18\t61530100\t61533700\tHigh Signal Region\nchr18\t68386500\t68419400\tHigh Signal Region\nchr18\t74678000\t74695900\tHigh Signal Region\nchr18\t76196600\t76198900\tLow Mappability\nchr18\t76272400\t76275200\tHigh Signal Region\nchr18\t76773800\t76800400\tHigh Signal Region\nchr18\t77031200\t77124400\tHigh Signal Region\nchr18\t77233300\t77236000\tHigh Signal Region\nchr18\t77377700\t77394500\tHigh Signal Region\nchr18\t77679100\t77681700\tHigh Signal Region\nchr18\t77772000\t77796400\tHigh Signal Region\nchr19\t7514300\t7516900\tHigh Signal Region\nchr19\t8850900\t8910700\tHigh Signal Region\nchr19\t24182700\t24198600\tHigh Signal Region\nchr19\t24501500\t27995100\tHigh Signal Region\nchr19\t35349800\t35357000\tHigh Signal Region\nchr19\t36065600\t36067700\tHigh Signal Region\nchr19\t37756400\t37795100\tHigh Signal Region\nchr19\t44912700\t44921200\tHigh Signal Region\nchr19\t44958200\t44964700\tLow Mappability\nchr19\t48406200\t48463100\tHigh Signal Region\nchr19\t50593500\t50643700\tHigh Signal Region\nchr1\t0\t750100\tHigh Signal Region\nchr1\t814500\t845200\tHigh Signal Region\nchr1\t2052400\t2056000\tHigh Signal Region\nchr1\t2582800\t2693900\tHigh Signal Region\nchr1\t4362200\t4364300\tHigh Signal Region\nchr1\t5714800\t5736800\tHigh Signal Region\nchr1\t16821600\t17301500\tHigh Signal Region\nchr1\t38076400\t38078300\tLow Mappability\nchr1\t91836500\t91854100\tHigh Signal Region\nchr1\t120531600\t120896300\tHigh Signal Region\nchr1\t120926100\t121149300\tHigh Signal Region\nchr1\t121341500\t145396500\tHigh Signal Region\nchr1\t147424800\t147731700\tHigh Signal Region\nchr1\t147832000\t149058800\tHigh Signal Region\nchr1\t152185700\t152191100\tHigh Signal Region\nchr1\t156185300\t156187600\tHigh Signal Region\nchr1\t161392300\t161442700\tHigh Signal Region\nchr1\t168317300\t168322800\tHigh Signal Region\nchr1\t203888700\t203890700\tHigh Signal Region\nchr1\t224175500\t224213600\tHigh Signal Region\nchr1\t228743700\t228782800\tHigh Signal Region\nchr1\t236876100\t236879100\tLow Mappability\nchr1\t237765500\t237767500\tHigh Signal Region\nchr1\t246980600\t246982700\tHigh Signal Region\nchr1\t249225300\t249250600\tHigh Signal Region\nchr20\t25733100\t25945000\tLow Mappability\nchr20\t25984200\t26150000\tLow Mappability\nchr20\t26184300\t29519700\tHigh Signal Region\nchr20\t29546800\t29853000\tHigh Signal Region\nchr20\t46521400\t46531600\tHigh Signal Region\nchr20\t47130700\t47133900\tHigh Signal Region\nchr20\t62887700\t63025500\tLow Mappability\nchr21\t9594900\t10366000\tHigh Signal Region\nchr21\t10491900\t10494000\tLow Mappability\nchr21\t10646000\t10861500\tHigh Signal Region\nchr21\t11004200\t14370200\tHigh Signal Region\nchr22\t0\t16962100\tHigh Signal Region\nchr22\t17348200\t17393500\tLow Mappability\nchr22\t17494600\t17519200\tLow Mappability\nchr22\t18358700\t18361200\tHigh Signal Region\nchr22\t18657400\t18889800\tHigh Signal Region\nchr22\t20304800\t20708400\tHigh Signal Region\nchr22\t21466100\t21916600\tHigh Signal Region\nchr22\t23826900\t23829900\tLow Mappability\nchr22\t33517600\t33519500\tHigh Signal Region\nchr22\t36280800\t36282700\tLow Mappability\nchr22\t51058600\t51083400\tHigh Signal Region\nchr22\t51220000\t51304500\tHigh Signal Region\nchr2\t2298400\t2300500\tLow Mappability\nchr2\t3183400\t3185800\tHigh Signal Region\nchr2\t13858600\t13877800\tHigh Signal Region\nchr2\t33140400\t33143500\tHigh Signal Region\nchr2\t49455800\t49457900\tLow Mappability\nchr2\t62956900\t62981700\tHigh Signal Region\nchr2\t70656600\t70659500\tHigh Signal Region\nchr2\t86882000\t86896800\tHigh Signal Region\nchr2\t87441300\t88290400\tHigh Signal Region\nchr2\t89534800\t89985900\tHigh Signal Region\nchr2\t90267000\t95326200\tHigh Signal Region\nchr2\t95471500\t95565900\tLow Mappability\nchr2\t97718400\t98232300\tHigh Signal Region\nchr2\t109814800\t109817200\tHigh Signal Region\nchr2\t114147600\t114441900\tHigh Signal Region\nchr2\t132763200\t132836700\tLow Mappability\nchr2\t132946300\t133122100\tHigh Signal Region\nchr2\t149638400\t149640300\tLow Mappability\nchr2\t162134100\t162148700\tHigh Signal Region\nchr2\t230044500\t230046500\tHigh Signal Region\nchr2\t243052100\t243199300\tHigh Signal Region\nchr3\t612200\t662600\tLow Mappability\nchr3\t3762200\t3767100\tHigh Signal Region\nchr3\t4958300\t4964200\tHigh Signal Region\nchr3\t8414500\t8434100\tHigh Signal Region\nchr3\t15009100\t15010800\tLow Mappability\nchr3\t15228200\t15245300\tHigh Signal Region\nchr3\t16995500\t17013700\tLow Mappability\nchr3\t25740700\t25759100\tLow Mappability\nchr3\t26426200\t26445700\tHigh Signal Region\nchr3\t39913800\t39931100\tHigh Signal Region\nchr3\t43527700\t43530900\tLow Mappability\nchr3\t51490400\t51496100\tHigh Signal Region\nchr3\t63719200\t63725000\tHigh Signal Region\nchr3\t73159000\t73161500\tHigh Signal Region\nchr3\t75678100\t75917700\tHigh Signal Region\nchr3\t75982800\t75999500\tHigh Signal Region\nchr3\t78995600\t78999800\tHigh Signal Region\nchr3\t80490200\t80492100\tLow Mappability\nchr3\t80916400\t80946200\tHigh Signal Region\nchr3\t90205400\t90224700\tHigh Signal Region\nchr3\t90312300\t93518500\tHigh Signal Region\nchr3\t93957200\t93959600\tLow Mappability\nchr3\t96335200\t96338100\tLow Mappability\nchr3\t96457300\t96459000\tHigh Signal Region\nchr3\t98184700\t98186900\tHigh Signal Region\nchr3\t100827300\t100833600\tLow Mappability\nchr3\t107053900\t107058800\tLow Mappability\nchr3\t118633600\t118639100\tLow Mappability\nchr3\t135154400\t135158200\tHigh Signal Region\nchr3\t135304100\t135329200\tHigh Signal Region\nchr3\t139309800\t139333000\tHigh Signal Region\nchr3\t155996600\t156002700\tHigh Signal Region\nchr3\t157599200\t157620600\tHigh Signal Region\nchr3\t160658900\t160666400\tLow Mappability\nchr3\t169397300\t169454100\tHigh Signal Region\nchr3\t173977500\t173983300\tLow Mappability\nchr3\t175499400\t175504900\tHigh Signal Region\nchr3\t182734900\t182736900\tLow Mappability\nchr3\t183673200\t183676500\tHigh Signal Region\nchr3\t183796800\t183798700\tHigh Signal Region\nchr3\t185265900\t185305500\tLow Mappability\nchr3\t189237500\t189238900\tLow Mappability\nchr3\t195201400\t195233900\tLow Mappability\nchr3\t195341900\t195476900\tHigh Signal Region\nchr3\t195502200\t195519800\tHigh Signal Region\nchr3\t195640700\t195745500\tHigh Signal Region\nchr3\t196624700\t196639200\tHigh Signal Region\nchr3\t196757600\t196762600\tHigh Signal Region\nchr3\t197110400\t197187600\tHigh Signal Region\nchr3\t197325200\t197407700\tHigh Signal Region\nchr3\t197798000\t198022400\tHigh Signal Region\nchr4\t0\t69600\tHigh Signal Region\nchr4\t1420500\t1478600\tHigh Signal Region\nchr4\t9199300\t9371400\tHigh Signal Region\nchr4\t40293300\t40341800\tHigh Signal Region\nchr4\t49073900\t52683800\tHigh Signal Region\nchr4\t68263300\t68273300\tHigh Signal Region\nchr4\t70294400\t70297700\tHigh Signal Region\nchr4\t76806200\t76808200\tHigh Signal Region\nchr4\t80272500\t80275600\tHigh Signal Region\nchr4\t114909000\t114911500\tHigh Signal Region\nchr4\t120158500\t120222800\tHigh Signal Region\nchr4\t153843200\t153846400\tHigh Signal Region\nchr4\t167475600\t167502500\tLow Mappability\nchr4\t190153700\t190157200\tHigh Signal Region\nchr4\t190190600\t190230500\tHigh Signal Region\nchr4\t190469400\t190685100\tHigh Signal Region\nchr4\t190756300\t190770700\tHigh Signal Region\nchr4\t190795300\t191154200\tHigh Signal Region\nchr5\t0\t85500\tHigh Signal Region\nchr5\t629900\t651800\tHigh Signal Region\nchr5\t1326400\t1334600\tHigh Signal Region\nchr5\t2144800\t2147800\tHigh Signal Region\nchr5\t2490000\t2491700\tHigh Signal Region\nchr5\t3322200\t3325200\tHigh Signal Region\nchr5\t6967500\t6971800\tHigh Signal Region\nchr5\t14633500\t14653400\tLow Mappability\nchr5\t16335700\t16341500\tHigh Signal Region\nchr5\t17516900\t17600400\tHigh Signal Region\nchr5\t17631100\t17633300\tLow Mappability\nchr5\t21458600\t21581100\tHigh Signal Region\nchr5\t25360400\t25384600\tHigh Signal Region\nchr5\t32369500\t32391600\tHigh Signal Region\nchr5\t34177800\t34246500\tHigh Signal Region\nchr5\t45523000\t45550600\tHigh Signal Region\nchr5\t45932400\t45978600\tHigh Signal Region\nchr5\t46072400\t46096800\tHigh Signal Region\nchr5\t46239900\t46241800\tLow Mappability\nchr5\t46265500\t49594200\tHigh Signal Region\nchr5\t60055500\t60058300\tLow Mappability\nchr5\t68830000\t70669400\tHigh Signal Region\nchr5\t71145800\t71149800\tHigh Signal Region\nchr5\t73981300\t74008300\tHigh Signal Region\nchr5\t79945000\t79949100\tHigh Signal Region\nchr5\t80324700\t80351700\tHigh Signal Region\nchr5\t84936300\t84958500\tHigh Signal Region\nchr5\t90445100\t90458900\tHigh Signal Region\nchr5\t93283200\t93284600\tHigh Signal Region\nchr5\t93903700\t93906100\tLow Mappability\nchr5\t99381200\t99426800\tHigh Signal Region\nchr5\t113477000\t113496900\tHigh Signal Region\nchr5\t126439200\t126461500\tHigh Signal Region\nchr5\t130208300\t130210400\tHigh Signal Region\nchr5\t134258200\t134265100\tHigh Signal Region\nchr5\t136835200\t136886000\tHigh Signal Region\nchr5\t137304800\t137310300\tHigh Signal Region\nchr5\t138341100\t138347500\tHigh Signal Region\nchr5\t142677200\t142690000\tLow Mappability\nchr5\t143013900\t143015800\tHigh Signal Region\nchr5\t155138700\t155189100\tHigh Signal Region\nchr5\t156085200\t156093100\tHigh Signal Region\nchr5\t170510900\t170517200\tHigh Signal Region\nchr5\t173440700\t173444600\tHigh Signal Region\nchr5\t174540800\t174565800\tHigh Signal Region\nchr5\t175331400\t175545200\tHigh Signal Region\nchr5\t176017900\t176019800\tLow Mappability\nchr5\t177061900\t177360500\tHigh Signal Region\nchr5\t177387600\t177408100\tLow Mappability\nchr5\t178011600\t178013600\tHigh Signal Region\nchr5\t180599700\t180915200\tHigh Signal Region\nchr6\t0\t162100\tLow Mappability\nchr6\t256600\t382800\tHigh Signal Region\nchr6\t519000\t521400\tLow Mappability\nchr6\t851500\t864200\tHigh Signal Region\nchr6\t1428700\t1434800\tLow Mappability\nchr6\t2200300\t2202700\tLow Mappability\nchr6\t4809700\t4840300\tLow Mappability\nchr6\t5886400\t5892500\tLow Mappability\nchr6\t6141100\t6143900\tLow Mappability\nchr6\t6212500\t6217900\tLow Mappability\nchr6\t8770600\t8776400\tLow Mappability\nchr6\t9966100\t9971700\tHigh Signal Region\nchr6\t10984500\t10987800\tLow Mappability\nchr6\t14480600\t14486400\tLow Mappability\nchr6\t15189400\t15190800\tHigh Signal Region\nchr6\t20079900\t20093100\tLow Mappability\nchr6\t20615000\t20619200\tLow Mappability\nchr6\t22166500\t22181200\tLow Mappability\nchr6\t23232900\t23235900\tLow Mappability\nchr6\t26668800\t26830200\tHigh Signal Region\nchr6\t26850500\t26925900\tLow Mappability\nchr6\t30027900\t30071800\tLow Mappability\nchr6\t31783300\t31806300\tLow Mappability\nchr6\t33451700\t33454300\tHigh Signal Region\nchr6\t34038400\t34041700\tHigh Signal Region\nchr6\t37096000\t37117300\tHigh Signal Region\nchr6\t38241900\t38269500\tHigh Signal Region\nchr6\t44011400\t44047700\tHigh Signal Region\nchr6\t44148500\t44150800\tHigh Signal Region\nchr6\t45637100\t45683300\tLow Mappability\nchr6\t45814800\t45817800\tLow Mappability\nchr6\t45963800\t45965300\tLow Mappability\nchr6\t48331100\t48336800\tLow Mappability\nchr6\t48705800\t48711100\tLow Mappability\nchr6\t49759100\t49764900\tLow Mappability\nchr6\t50999100\t51004700\tHigh Signal Region\nchr6\t51531300\t51535800\tLow Mappability\nchr6\t54270500\t54273400\tHigh Signal Region\nchr6\t54364700\t54372500\tLow Mappability\nchr6\t54826700\t54832300\tLow Mappability\nchr6\t56911200\t56913200\tLow Mappability\nchr6\t56954700\t56956700\tLow Mappability\nchr6\t57133300\t57608800\tHigh Signal Region\nchr6\t57671300\t57673300\tLow Mappability\nchr6\t58061300\t58288100\tHigh Signal Region\nchr6\t58724800\t58738300\tLow Mappability\nchr6\t58772700\t61920700\tHigh Signal Region\nchr6\t62283100\t62285000\tLow Mappability\nchr6\t62371500\t62383900\tLow Mappability\nchr6\t62770600\t62781900\tHigh Signal Region\nchr6\t63265300\t63298700\tLow Mappability\nchr6\t65966100\t65967700\tLow Mappability\nchr6\t70193400\t70231500\tLow Mappability\nchr6\t71454100\t71514000\tLow Mappability\nchr6\t71981600\t71986300\tHigh Signal Region\nchr6\t72027300\t72029200\tLow Mappability\nchr6\t72875000\t72876900\tHigh Signal Region\nchr6\t73680200\t73704400\tLow Mappability\nchr6\t74417700\t74420300\tLow Mappability\nchr6\t74707400\t74738700\tLow Mappability\nchr6\t77455300\t77457000\tLow Mappability\nchr6\t77670600\t77687700\tLow Mappability\nchr6\t77752900\t77797700\tLow Mappability\nchr6\t78426700\t78455800\tLow Mappability\nchr6\t78508100\t78509800\tLow Mappability\nchr6\t79681400\t79687300\tLow Mappability\nchr6\t80401000\t80403400\tHigh Signal Region\nchr6\t81193300\t81207500\tLow Mappability\nchr6\t83257400\t83275700\tLow Mappability\nchr6\t86694600\t86736600\tLow Mappability\nchr6\t87552300\t87637100\tLow Mappability\nchr6\t89091200\t89122300\tLow Mappability\nchr6\t90764500\t90769800\tHigh Signal Region\nchr6\t91272000\t91298000\tHigh Signal Region\nchr6\t94341300\t94347000\tHigh Signal Region\nchr6\t95516600\t95540000\tLow Mappability\nchr6\t96310100\t96313200\tLow Mappability\nchr6\t97430400\t97437100\tLow Mappability\nchr6\t97824400\t97828600\tHigh Signal Region\nchr6\t99151500\t99156200\tLow Mappability\nchr6\t99314300\t99316400\tLow Mappability\nchr6\t100802600\t100817600\tHigh Signal Region\nchr6\t101028300\t101034500\tLow Mappability\nchr6\t101633800\t101663000\tLow Mappability\nchr6\t102617900\t102623600\tHigh Signal Region\nchr6\t102983200\t102985100\tLow Mappability\nchr6\t103200700\t103206700\tHigh Signal Region\nchr6\t104937300\t104943400\tLow Mappability\nchr6\t105185700\t105210800\tLow Mappability\nchr6\t107045300\t107046900\tLow Mappability\nchr6\t109454700\t109471400\tLow Mappability\nchr6\t109566300\t109571600\tLow Mappability\nchr6\t112224100\t112229600\tLow Mappability\nchr6\t112853400\t112873000\tLow Mappability\nchr6\t114754200\t114756900\tLow Mappability\nchr6\t115121100\t115123800\tLow Mappability\nchr6\t115496600\t115502400\tLow Mappability\nchr6\t115575100\t115578000\tHigh Signal Region\nchr6\t116960800\t116966000\tHigh Signal Region\nchr6\t117134700\t117144000\tLow Mappability\nchr6\t117413300\t117429300\tLow Mappability\nchr6\t119557600\t119559600\tHigh Signal Region\nchr6\t121732200\t121734100\tLow Mappability\nchr6\t121887100\t121892400\tLow Mappability\nchr6\t123793600\t123799300\tLow Mappability\nchr6\t125028000\t125052900\tHigh Signal Region\nchr6\t125126000\t125131800\tLow Mappability\nchr6\t129226700\t129244600\tLow Mappability\nchr6\t131556000\t131561800\tLow Mappability\nchr6\t132019100\t132037100\tLow Mappability\nchr6\t132177400\t132179000\tLow Mappability\nchr6\t133341700\t133347800\tLow Mappability\nchr6\t133593100\t133595000\tHigh Signal Region\nchr6\t136492700\t136494600\tLow Mappability\nchr6\t138120400\t138136600\tLow Mappability\nchr6\t142456500\t142469200\tLow Mappability\nchr6\t144117700\t144122900\tHigh Signal Region\nchr6\t145393200\t145395000\tLow Mappability\nchr6\t145824200\t145826400\tLow Mappability\nchr6\t145984700\t146002900\tLow Mappability\nchr6\t146291400\t146318300\tLow Mappability\nchr6\t148276600\t148278600\tLow Mappability\nchr6\t148480500\t148484700\tLow Mappability\nchr6\t150782100\t150797500\tLow Mappability\nchr6\t156062900\t156064800\tHigh Signal Region\nchr6\t156355300\t156361300\tHigh Signal Region\nchr6\t156646100\t156651900\tHigh Signal Region\nchr6\t156803000\t156804800\tLow Mappability\nchr6\t157730500\t157736300\tHigh Signal Region\nchr6\t160073000\t160134300\tLow Mappability\nchr6\t161032400\t161068500\tLow Mappability\nchr6\t165716800\t165720000\tLow Mappability\nchr6\t165782200\t165787800\tLow Mappability\nchr6\t166828700\t166843000\tLow Mappability\nchr6\t167196600\t167208400\tLow Mappability\nchr6\t167745800\t167752500\tLow Mappability\nchr6\t167786100\t167802900\tLow Mappability\nchr6\t168635100\t168638700\tLow Mappability\nchr6\t168961200\t168963300\tLow Mappability\nchr6\t169054200\t169061300\tHigh Signal Region\nchr6\t169239700\t169241700\tLow Mappability\nchr6\t170460500\t170462500\tLow Mappability\nchr6\t170528700\t170531000\tLow Mappability\nchr6\t170686000\t170710200\tHigh Signal Region\nchr6\t170774700\t170777400\tLow Mappability\nchr6\t170803900\t170839700\tLow Mappability\nchr6\t170915300\t171115000\tLow Mappability\nchr7\t0\t49700\tHigh Signal Region\nchr7\t1311000\t1313200\tHigh Signal Region\nchr7\t45290700\t45292600\tLow Mappability\nchr7\t56437000\t56447500\tHigh Signal Region\nchr7\t57544900\t57557600\tHigh Signal Region\nchr7\t57597800\t57782700\tHigh Signal Region\nchr7\t57884200\t62120800\tHigh Signal Region\nchr7\t62403000\t62404900\tHigh Signal Region\nchr7\t64929600\t65063200\tHigh Signal Region\nchr7\t84878700\t84884900\tHigh Signal Region\nchr7\t100549000\t100611600\tHigh Signal Region\nchr7\t100634800\t100648100\tHigh Signal Region\nchr7\t101981900\t102013400\tHigh Signal Region\nchr7\t102114900\t102445700\tHigh Signal Region\nchr7\t121919200\t121925000\tHigh Signal Region\nchr7\t140761800\t140784200\tHigh Signal Region\nchr7\t142373000\t142376300\tLow Mappability\nchr7\t145693500\t145735200\tLow Mappability\nchr7\t152072600\t152132400\tHigh Signal Region\nchr7\t157924100\t157945100\tHigh Signal Region\nchr7\t158387000\t158388900\tHigh Signal Region\nchr7\t158685900\t158710600\tHigh Signal Region\nchr8\t0\t185300\tHigh Signal Region\nchr8\t7012600\t8066200\tHigh Signal Region\nchr8\t11994400\t12230100\tHigh Signal Region\nchr8\t12252000\t12466300\tHigh Signal Region\nchr8\t13501500\t13503800\tHigh Signal Region\nchr8\t43091800\t43118200\tHigh Signal Region\nchr8\t43758900\t46908900\tHigh Signal Region\nchr8\t46946900\t46959100\tHigh Signal Region\nchr8\t47367600\t47369500\tHigh Signal Region\nchr8\t48792700\t48794600\tHigh Signal Region\nchr8\t51581600\t51584700\tHigh Signal Region\nchr8\t52729900\t52737900\tHigh Signal Region\nchr8\t58117400\t58128700\tHigh Signal Region\nchr8\t59283300\t59288700\tHigh Signal Region\nchr8\t60782300\t60800500\tHigh Signal Region\nchr8\t70600600\t70603500\tHigh Signal Region\nchr8\t82753700\t82764200\tHigh Signal Region\nchr8\t86554300\t86841600\tHigh Signal Region\nchr8\t100501000\t100509100\tHigh Signal Region\nchr8\t104795400\t104807700\tHigh Signal Region\nchr8\t106801200\t106807000\tHigh Signal Region\nchr8\t127325400\t127331100\tHigh Signal Region\nchr8\t142501600\t142503600\tHigh Signal Region\nchr8\t144743300\t144752700\tHigh Signal Region\nchr9\t6593800\t6595700\tHigh Signal Region\nchr9\t35903000\t35915300\tHigh Signal Region\nchr9\t40815000\t43489000\tHigh Signal Region\nchr9\t43684600\t44102400\tHigh Signal Region\nchr9\t44852100\t44881200\tHigh Signal Region\nchr9\t44908300\t66250200\tHigh Signal Region\nchr9\t66344100\t68143800\tHigh Signal Region\nchr9\t68306800\t69121200\tHigh Signal Region\nchr9\t69141700\t70957900\tHigh Signal Region\nchr9\t72652100\t72654500\tHigh Signal Region\nchr9\t78789200\t78791100\tHigh Signal Region\nchr9\t79185700\t79187900\tHigh Signal Region\nchr9\t87779800\t87780900\tHigh Signal Region\nchr9\t140221300\t140223800\tHigh Signal Region\nchr9\t141053300\t141213400\tLow Mappability\nchrX\t0\t290100\tHigh Signal Region\nchrX\t392200\t529200\tLow Mappability\nchrX\t1006400\t1334000\tHigh Signal Region\nchrX\t7505600\t7509900\tHigh Signal Region\nchrX\t9371800\t9400200\tHigh Signal Region\nchrX\t49164900\t49386300\tHigh Signal Region\nchrX\t55207100\t55210900\tLow Mappability\nchrX\t58329700\t58433500\tHigh Signal Region\nchrX\t58461000\t61920100\tHigh Signal Region\nchrX\t62005100\t62007000\tHigh Signal Region\nchrX\t78057800\t78060000\tHigh Signal Region\nchrX\t99512200\t99516600\tHigh Signal Region\nchrX\t101446100\t101744100\tHigh Signal Region\nchrX\t108258600\t108312300\tHigh Signal Region\nchrX\t111555900\t111595100\tHigh Signal Region\nchrX\t114959100\t115006100\tHigh Signal Region\nchrX\t125595300\t125608200\tLow Mappability\nchrX\t132242600\t132250600\tHigh Signal Region\nchrX\t134852300\t134971100\tHigh Signal Region\nchrX\t136518800\t136521500\tHigh Signal Region\nchrX\t154528900\t154616300\tHigh Signal Region\nchrX\t155038500\t155270500\tHigh Signal Region\nchrY\t7432700\t13491000\tHigh Signal Region\nchrY\t13633400\t14289000\tHigh Signal Region\nchrY\t28783400\t59373500\tHigh Signal Region\n" }, { "path": "assets/blacklists/v2.0/hg38-blacklist.v2.bed", "content": "chr10\t0\t45700\tLow Mappability\nchr10\t38481300\t38596500\tHigh Signal Region\nchr10\t38782600\t38967900\tHigh Signal Region\nchr10\t39901300\t41712900\tHigh Signal Region\nchr10\t41838900\t42107300\tHigh Signal Region\nchr10\t42279400\t42322500\tHigh Signal Region\nchr10\t126946300\t126953400\tLow Mappability\nchr10\t133625800\t133797400\tHigh Signal Region\nchr11\t0\t194500\tLow Mappability\nchr11\t518900\t520700\tLow Mappability\nchr11\t584400\t586500\tHigh Signal Region\nchr11\t964100\t966000\tLow Mappability\nchr11\t1015700\t1019300\tHigh Signal Region\nchr11\t1091000\t1098200\tLow Mappability\nchr11\t3652800\t3655600\tHigh Signal Region\nchr11\t10506900\t10511100\tHigh Signal Region\nchr11\t28206300\t28236700\tHigh Signal Region\nchr11\t50813600\t54383000\tHigh Signal Region\nchr11\t61084500\t61130400\tHigh Signal Region\nchr11\t70370400\t70372400\tHigh Signal Region\nchr11\t73509800\t73511700\tHigh Signal Region\nchr11\t77885600\t77887600\tHigh Signal Region\nchr11\t93417500\t93427700\tHigh Signal Region\nchr11\t94232700\t94240400\tHigh Signal Region\nchr11\t103408700\t103410600\tHigh Signal Region\nchr11\t121175000\t121187000\tHigh Signal Region\nchr11\t131679500\t131681500\tHigh Signal Region\nchr11\t135075600\t135086600\tHigh Signal Region\nchr12\t0\t77800\tHigh Signal Region\nchr12\t371800\t422400\tHigh Signal Region\nchr12\t2254900\t2257000\tHigh Signal Region\nchr12\t2519800\t2540500\tLow Mappability\nchr12\t5928900\t5933000\tLow Mappability\nchr12\t20550500\t20552400\tLow Mappability\nchr12\t20768400\t20770300\tHigh Signal Region\nchr12\t29790400\t29834600\tHigh Signal Region\nchr12\t34715400\t37269100\tHigh Signal Region\nchr12\t41362700\t41364600\tHigh Signal Region\nchr12\t61471100\t61473000\tHigh Signal Region\nchr12\t66473900\t66475800\tHigh Signal Region\nchr12\t101147000\t101155000\tHigh Signal Region\nchr12\t113079600\t113081500\tHigh Signal Region\nchr12\t124430500\t124440300\tHigh Signal Region\nchr12\t124905900\t124941800\tHigh Signal Region\nchr12\t130386400\t130394100\tHigh Signal Region\nchr12\t131475300\t131478600\tHigh Signal Region\nchr12\t131576000\t131589700\tHigh Signal Region\nchr12\t132223300\t132243400\tHigh Signal Region\nchr12\t132455100\t132465200\tHigh Signal Region\nchr12\t133249000\t133275300\tHigh Signal Region\nchr13\t16087600\t16165300\tHigh Signal Region\nchr13\t16226300\t18171400\tHigh Signal Region\nchr13\t18211000\t18216100\tHigh Signal Region\nchr13\t57140500\t57172500\tHigh Signal Region\nchr13\t109423200\t109425200\tHigh Signal Region\nchr13\t114353300\t114364300\tLow Mappability\nchr14\t0\t18670900\tHigh Signal Region\nchr14\t18695400\t19724300\tHigh Signal Region\nchr14\t23033300\t23098600\tHigh Signal Region\nchr14\t26629300\t26634900\tHigh Signal Region\nchr14\t31793800\t31798100\tHigh Signal Region\nchr14\t32483400\t32486000\tHigh Signal Region\nchr14\t34537100\t34562600\tHigh Signal Region\nchr14\t35947200\t35950000\tHigh Signal Region\nchr14\t37351000\t37356700\tHigh Signal Region\nchr14\t44025100\t44027200\tHigh Signal Region\nchr14\t44705100\t44709900\tHigh Signal Region\nchr14\t45477100\t45482500\tHigh Signal Region\nchr14\t46865300\t46866500\tHigh Signal Region\nchr14\t54235600\t54240000\tHigh Signal Region\nchr14\t57112100\t57118100\tHigh Signal Region\nchr14\t74711700\t74729000\tHigh Signal Region\nchr14\t86074000\t86076000\tHigh Signal Region\nchr14\t86593300\t86595200\tHigh Signal Region\nchr14\t88443700\t88458100\tHigh Signal Region\nchr14\t100525900\t100527800\tHigh Signal Region\nchr14\t101267600\t101272200\tHigh Signal Region\nchr14\t101674400\t101676400\tHigh Signal Region\nchr14\t104288100\t104290200\tHigh Signal Region\nchr14\t105215000\t105240900\tHigh Signal Region\nchr14\t105568500\t105583900\tHigh Signal Region\nchr14\t105616500\t105618600\tHigh Signal Region\nchr14\t106326900\t106367700\tHigh Signal Region\nchr15\t0\t17035000\tHigh Signal Region\nchr15\t17058500\t19790100\tHigh Signal Region\nchr15\t20005600\t22606300\tHigh Signal Region\nchr15\t23125400\t23357400\tHigh Signal Region\nchr15\t25757700\t25759100\tLow Mappability\nchr15\t28304900\t28683400\tHigh Signal Region\nchr15\t30066300\t30627500\tHigh Signal Region\nchr15\t30844100\t30859900\tHigh Signal Region\nchr15\t32153700\t32626200\tHigh Signal Region\nchr15\t54925700\t54932200\tHigh Signal Region\nchr15\t56311200\t56314600\tHigh Signal Region\nchr15\t72635200\t72687100\tHigh Signal Region\nchr15\t74068100\t74102000\tHigh Signal Region\nchr15\t75254100\t75299800\tHigh Signal Region\nchr15\t77698600\t77700600\tHigh Signal Region\nchr15\t82321000\t82374600\tHigh Signal Region\nchr15\t82421200\t82541700\tHigh Signal Region\nchr15\t84405300\t84524700\tHigh Signal Region\nchr15\t101752300\t101764800\tLow Mappability\nchr15\t101892700\t101991100\tHigh Signal Region\nchr16\t29430800\t29566900\tLow Mappability\nchr16\t34061400\t34121400\tHigh Signal Region\nchr16\t34272000\t34633100\tHigh Signal Region\nchr16\t34657200\t34672500\tHigh Signal Region\nchr16\t34694600\t34772000\tHigh Signal Region\nchr16\t34832600\t34922100\tHigh Signal Region\nchr16\t34945600\t35072500\tLow Mappability\nchr16\t36166300\t36202400\tHigh Signal Region\nchr16\t36225200\t46423000\tHigh Signal Region\nchr16\t46449700\t46467000\tHigh Signal Region\nchr16\t90100500\t90338300\tLow Mappability\nchr17\t0\t137600\tHigh Signal Region\nchr17\t294900\t317900\tHigh Signal Region\nchr17\t448200\t510900\tHigh Signal Region\nchr17\t1061500\t1066100\tHigh Signal Region\nchr17\t1307700\t1312000\tLow Mappability\nchr17\t19025700\t19237400\tHigh Signal Region\nchr17\t21783300\t22054000\tHigh Signal Region\nchr17\t22520400\t22527300\tHigh Signal Region\nchr17\t22745200\t26629800\tHigh Signal Region\nchr17\t26766800\t26987200\tHigh Signal Region\nchr17\t43227600\t43324300\tHigh Signal Region\nchr17\t45511500\t45641300\tLow Mappability\nchr17\t53104900\t53107300\tHigh Signal Region\nchr18\t0\t64600\tHigh Signal Region\nchr18\t105200\t113200\tHigh Signal Region\nchr18\t971000\t976500\tHigh Signal Region\nchr18\t2841300\t2861500\tHigh Signal Region\nchr18\t15367200\t20940300\tHigh Signal Region\nchr18\t46961600\t47031700\tHigh Signal Region\nchr18\t47852300\t47854300\tLow Mappability\nchr18\t52791800\t52793800\tHigh Signal Region\nchr18\t74615900\t74618100\tHigh Signal Region\nchr18\t76966200\t76968500\tHigh Signal Region\nchr18\t78436900\t78438700\tLow Mappability\nchr18\t79013800\t79040300\tHigh Signal Region\nchr18\t79617800\t79621500\tHigh Signal Region\nchr18\t80257400\t80373200\tHigh Signal Region\nchr19\t0\t271200\tHigh Signal Region\nchr19\t7019100\t7061300\tHigh Signal Region\nchr19\t7449400\t7452000\tHigh Signal Region\nchr19\t8740100\t8800500\tHigh Signal Region\nchr19\t24330100\t27274500\tHigh Signal Region\nchr19\t27337600\t27427400\tHigh Signal Region\nchr19\t34386800\t34393500\tHigh Signal Region\nchr19\t34860600\t34866200\tHigh Signal Region\nchr19\t36267900\t36313700\tHigh Signal Region\nchr19\t37264900\t37304300\tHigh Signal Region\nchr19\t44393300\t44416700\tHigh Signal Region\nchr19\t47903000\t47959700\tHigh Signal Region\nchr19\t50090500\t50140400\tHigh Signal Region\nchr19\t58538700\t58617600\tHigh Signal Region\nchr1\t0\t792500\tHigh Signal Region\nchr1\t91386300\t91388400\tLow Mappability\nchr1\t103594400\t103760600\tHigh Signal Region\nchr1\t121605200\t124938900\tHigh Signal Region\nchr1\t125067600\t125086000\tHigh Signal Region\nchr1\t125130200\t143562200\tHigh Signal Region\nchr1\t161423100\t161472400\tHigh Signal Region\nchr1\t168348600\t168349900\tHigh Signal Region\nchr1\t224010800\t224017000\tHigh Signal Region\nchr1\t236713000\t236715600\tLow Mappability\nchr1\t248932700\t248956400\tHigh Signal Region\nchr20\t0\t67900\tHigh Signal Region\nchr20\t26364200\t28916900\tHigh Signal Region\nchr20\t28939400\t29264700\tHigh Signal Region\nchr20\t30995400\t31246000\tHigh Signal Region\nchr20\t47893800\t47900200\tHigh Signal Region\nchr21\t0\t8679600\tHigh Signal Region\nchr21\t9159900\t9735300\tHigh Signal Region\nchr21\t10013900\t10069600\tHigh Signal Region\nchr21\t10094700\t10505100\tHigh Signal Region\nchr21\t10650900\t12965800\tHigh Signal Region\nchr21\t43212400\t43280900\tHigh Signal Region\nchr21\t46682700\t46709900\tHigh Signal Region\nchr22\t10687700\t11428100\tHigh Signal Region\nchr22\t11496900\t11873100\tHigh Signal Region\nchr22\t11976900\t15154400\tHigh Signal Region\nchr22\t16258000\t16385800\tHigh Signal Region\nchr22\t18175900\t18947300\tHigh Signal Region\nchr22\t20337400\t20343300\tHigh Signal Region\nchr22\t21113500\t21554000\tHigh Signal Region\nchr22\t49972700\t49975300\tHigh Signal Region\nchr22\t50642800\t50644900\tHigh Signal Region\nchr22\t50786600\t50818400\tHigh Signal Region\nchr2\t1221700\t1223900\tHigh Signal Region\nchr2\t1594700\t1605200\tHigh Signal Region\nchr2\t3179600\t3182100\tHigh Signal Region\nchr2\t4643800\t4648800\tHigh Signal Region\nchr2\t10952800\t10955000\tHigh Signal Region\nchr2\t13718700\t13737700\tHigh Signal Region\nchr2\t21903500\t21906400\tHigh Signal Region\nchr2\t32865900\t32869900\tHigh Signal Region\nchr2\t32915300\t32918400\tHigh Signal Region\nchr2\t33766500\t33768400\tHigh Signal Region\nchr2\t36183000\t36184500\tHigh Signal Region\nchr2\t49228700\t49230700\tHigh Signal Region\nchr2\t64359300\t64377000\tHigh Signal Region\nchr2\t86655300\t86661100\tHigh Signal Region\nchr2\t86900700\t87078100\tLow Mappability\nchr2\t87119300\t87189800\tLow Mappability\nchr2\t87217000\t87866200\tHigh Signal Region\nchr2\t88771000\t88806500\tHigh Signal Region\nchr2\t89235300\t89947100\tHigh Signal Region\nchr2\t90246300\t91735500\tHigh Signal Region\nchr2\t91783000\t91924800\tLow Mappability\nchr2\t91969000\t94569500\tHigh Signal Region\nchr2\t95849400\t96067900\tHigh Signal Region\nchr2\t97106300\t97615800\tHigh Signal Region\nchr2\t109198400\t109200700\tHigh Signal Region\nchr2\t109744600\t110095200\tHigh Signal Region\nchr2\t110229200\t110633400\tLow Mappability\nchr2\t111253600\t111500500\tLow Mappability\nchr2\t112346200\t112441300\tLow Mappability\nchr2\t113370100\t113662700\tHigh Signal Region\nchr2\t130496800\t130716400\tHigh Signal Region\nchr2\t132201000\t132288900\tHigh Signal Region\nchr2\t132353600\t132364500\tHigh Signal Region\nchr2\t148880800\t148882800\tHigh Signal Region\nchr2\t161277700\t161283400\tHigh Signal Region\nchr2\t181274800\t181276800\tHigh Signal Region\nchr2\t226108500\t226110400\tHigh Signal Region\nchr2\t234889800\t234894400\tHigh Signal Region\nchr2\t239642200\t239645600\tHigh Signal Region\nchr2\t240308100\t240310300\tHigh Signal Region\nchr2\t241589300\t241591800\tHigh Signal Region\nchr2\t242005900\t242011100\tHigh Signal Region\nchr2\t242110100\t242193500\tHigh Signal Region\nchr3\t0\t11600\tHigh Signal Region\nchr3\t3895200\t3896700\tHigh Signal Region\nchr3\t4916700\t4922500\tHigh Signal Region\nchr3\t14091000\t14092500\tHigh Signal Region\nchr3\t15187200\t15207800\tHigh Signal Region\nchr3\t15592100\t15603300\tHigh Signal Region\nchr3\t16176800\t16179200\tHigh Signal Region\nchr3\t16679700\t16682500\tHigh Signal Region\nchr3\t19499700\t19504000\tHigh Signal Region\nchr3\t19624000\t19627100\tHigh Signal Region\nchr3\t21983200\t21988100\tHigh Signal Region\nchr3\t24053500\t24054900\tHigh Signal Region\nchr3\t26384800\t26404100\tHigh Signal Region\nchr3\t29993900\t29999900\tHigh Signal Region\nchr3\t36987500\t36995000\tHigh Signal Region\nchr3\t38083400\t38085400\tHigh Signal Region\nchr3\t38406100\t38430900\tHigh Signal Region\nchr3\t39366700\t39386000\tHigh Signal Region\nchr3\t40219400\t40240500\tHigh Signal Region\nchr3\t49671000\t49696700\tHigh Signal Region\nchr3\t51457800\t51462000\tHigh Signal Region\nchr3\t57326800\t57328500\tHigh Signal Region\nchr3\t65124100\t65126100\tHigh Signal Region\nchr3\t65510000\t65513900\tHigh Signal Region\nchr3\t65697400\t65699300\tHigh Signal Region\nchr3\t66273800\t66275200\tHigh Signal Region\nchr3\t68076400\t68077800\tHigh Signal Region\nchr3\t69047300\t69053600\tHigh Signal Region\nchr3\t69475300\t69479700\tHigh Signal Region\nchr3\t75630100\t75707800\tHigh Signal Region\nchr3\t75736400\t75754600\tHigh Signal Region\nchr3\t78948800\t78950500\tHigh Signal Region\nchr3\t80876000\t80894000\tHigh Signal Region\nchr3\t89345600\t89370500\tHigh Signal Region\nchr3\t90156400\t90175500\tHigh Signal Region\nchr3\t90455400\t91297100\tHigh Signal Region\nchr3\t91516200\t93749200\tHigh Signal Region\nchr3\t96616300\t96619300\tHigh Signal Region\nchr3\t97905100\t97923200\tHigh Signal Region\nchr3\t101674800\t101698400\tHigh Signal Region\nchr3\t103224300\t103236500\tHigh Signal Region\nchr3\t106665700\t106669700\tHigh Signal Region\nchr3\t106975900\t106979600\tHigh Signal Region\nchr3\t108751100\t108755100\tHigh Signal Region\nchr3\t111019500\t111024600\tHigh Signal Region\nchr3\t121933800\t121936400\tHigh Signal Region\nchr3\t122414300\t122417500\tHigh Signal Region\nchr3\t122735500\t122796600\tHigh Signal Region\nchr3\t122837000\t122838700\tHigh Signal Region\nchr3\t133177100\t133179800\tHigh Signal Region\nchr3\t133551500\t133579500\tHigh Signal Region\nchr3\t135437200\t135439100\tHigh Signal Region\nchr3\t136954600\t136969200\tHigh Signal Region\nchr3\t137168400\t137169900\tHigh Signal Region\nchr3\t138575800\t138595900\tHigh Signal Region\nchr3\t139190800\t139194700\tHigh Signal Region\nchr3\t153236200\t153241300\tHigh Signal Region\nchr3\t155544100\t155546700\tHigh Signal Region\nchr3\t156279000\t156283500\tHigh Signal Region\nchr3\t157080800\t157093400\tHigh Signal Region\nchr3\t158511300\t158513100\tHigh Signal Region\nchr3\t160941200\t160948700\tHigh Signal Region\nchr3\t161001900\t161014100\tHigh Signal Region\nchr3\t165573100\t165591000\tHigh Signal Region\nchr3\t166228200\t166232400\tHigh Signal Region\nchr3\t168012100\t168016800\tHigh Signal Region\nchr3\t170567000\t170569900\tHigh Signal Region\nchr3\t170864300\t170881400\tHigh Signal Region\nchr3\t171626600\t171637700\tHigh Signal Region\nchr3\t174829200\t174831800\tHigh Signal Region\nchr3\t176828700\t176833000\tHigh Signal Region\nchr3\t177660600\t177664000\tHigh Signal Region\nchr3\t178926800\t178941300\tHigh Signal Region\nchr3\t183016900\t183019100\tHigh Signal Region\nchr3\t183955400\t183958700\tHigh Signal Region\nchr3\t187893900\t187896100\tHigh Signal Region\nchr3\t192739300\t192742700\tHigh Signal Region\nchr3\t194323600\t194334900\tHigh Signal Region\nchr3\t195477900\t195507300\tHigh Signal Region\nchr3\t195616000\t195750100\tHigh Signal Region\nchr3\t195775500\t195791400\tHigh Signal Region\nchr3\t195914100\t196028300\tHigh Signal Region\nchr3\t196249400\t196251900\tHigh Signal Region\nchr3\t196897800\t196899800\tHigh Signal Region\nchr3\t197030600\t197035800\tHigh Signal Region\nchr3\t197383400\t197428800\tHigh Signal Region\nchr3\t197454700\t197460800\tHigh Signal Region\nchr3\t197598400\t197680900\tHigh Signal Region\nchr3\t198099800\t198295500\tHigh Signal Region\nchr4\t0\t69200\tHigh Signal Region\nchr4\t554100\t556500\tHigh Signal Region\nchr4\t1427000\t1468900\tHigh Signal Region\nchr4\t6002700\t6005700\tHigh Signal Region\nchr4\t7863000\t7865000\tHigh Signal Region\nchr4\t9212700\t9369600\tHigh Signal Region\nchr4\t40291700\t40318200\tHigh Signal Region\nchr4\t49077200\t51816100\tHigh Signal Region\nchr4\t55327200\t55329200\tHigh Signal Region\nchr4\t77994000\t78009600\tHigh Signal Region\nchr4\t119274400\t119301700\tHigh Signal Region\nchr4\t146285100\t146305300\tHigh Signal Region\nchr4\t162420500\t162422400\tHigh Signal Region\nchr4\t166554300\t166581300\tLow Mappability\nchr4\t181238800\t181242300\tLow Mappability\nchr4\t189232500\t189236300\tHigh Signal Region\nchr4\t189834900\t189849700\tHigh Signal Region\nchr4\t189877500\t190023700\tHigh Signal Region\nchr4\t190048600\t190214500\tHigh Signal Region\nchr5\t0\t44100\tHigh Signal Region\nchr5\t548300\t564100\tHigh Signal Region\nchr5\t647600\t651700\tHigh Signal Region\nchr5\t1326100\t1334600\tHigh Signal Region\nchr5\t2144600\t2147800\tHigh Signal Region\nchr5\t2489800\t2491700\tHigh Signal Region\nchr5\t3322100\t3325100\tHigh Signal Region\nchr5\t6967700\t6971700\tHigh Signal Region\nchr5\t17516800\t17600200\tHigh Signal Region\nchr5\t21477600\t21497600\tHigh Signal Region\nchr5\t25381400\t25384300\tHigh Signal Region\nchr5\t34177900\t34244800\tHigh Signal Region\nchr5\t45522900\t45525200\tHigh Signal Region\nchr5\t45743000\t45744800\tHigh Signal Region\nchr5\t46433900\t46687700\tHigh Signal Region\nchr5\t46708100\t50165300\tHigh Signal Region\nchr5\t60759700\t60762500\tHigh Signal Region\nchr5\t63320900\t63335500\tHigh Signal Region\nchr5\t69540700\t71359500\tHigh Signal Region\nchr5\t71850000\t71852800\tHigh Signal Region\nchr5\t74685400\t74712400\tHigh Signal Region\nchr5\t78452400\t78457600\tHigh Signal Region\nchr5\t78848400\t78872800\tHigh Signal Region\nchr5\t80649100\t80653100\tHigh Signal Region\nchr5\t85641800\t85662700\tHigh Signal Region\nchr5\t93947500\t93948900\tHigh Signal Region\nchr5\t94567100\t94570400\tHigh Signal Region\nchr5\t100045500\t100076300\tHigh Signal Region\nchr5\t106425500\t106429500\tHigh Signal Region\nchr5\t109259500\t109265400\tHigh Signal Region\nchr5\t111302100\t111308300\tHigh Signal Region\nchr5\t114156700\t114158300\tHigh Signal Region\nchr5\t119904000\t119905600\tHigh Signal Region\nchr5\t123760300\t123762200\tHigh Signal Region\nchr5\t134922500\t134929400\tHigh Signal Region\nchr5\t139005500\t139011600\tHigh Signal Region\nchr5\t146610000\t146615500\tHigh Signal Region\nchr5\t153071100\t153077000\tHigh Signal Region\nchr5\t156658300\t156665400\tHigh Signal Region\nchr5\t161606000\t161611700\tHigh Signal Region\nchr5\t171083900\t171090200\tHigh Signal Region\nchr5\t175904500\t176118000\tHigh Signal Region\nchr5\t176590700\t176593000\tHigh Signal Region\nchr5\t177636700\t177684700\tHigh Signal Region\nchr5\t177960500\t177981400\tHigh Signal Region\nchr5\t178584600\t178586600\tHigh Signal Region\nchr5\t181172600\t181538200\tHigh Signal Region\nchr6\t256500\t382800\tHigh Signal Region\nchr6\t861500\t864200\tHigh Signal Region\nchr6\t1052800\t1054800\tHigh Signal Region\nchr6\t26669200\t26832300\tHigh Signal Region\nchr6\t33484600\t33486400\tHigh Signal Region\nchr6\t34070600\t34074000\tHigh Signal Region\nchr6\t38262000\t38301600\tHigh Signal Region\nchr6\t39455800\t39460500\tHigh Signal Region\nchr6\t44043600\t44080000\tHigh Signal Region\nchr6\t44180600\t44182900\tHigh Signal Region\nchr6\t51874900\t51901300\tHigh Signal Region\nchr6\t54961900\t54967400\tHigh Signal Region\nchr6\t58432200\t60242300\tHigh Signal Region\nchr6\t61321800\t61493000\tHigh Signal Region\nchr6\t61573200\t61575100\tLow Mappability\nchr6\t61661900\t61673400\tHigh Signal Region\nchr6\t103709000\t103715100\tHigh Signal Region\nchr6\t115254900\t115256800\tHigh Signal Region\nchr6\t143799900\t143801800\tHigh Signal Region\nchr6\t156035300\t156040100\tHigh Signal Region\nchr6\t157309500\t157324800\tHigh Signal Region\nchr6\t160611700\t160647400\tHigh Signal Region\nchr6\t170145300\t170147200\tHigh Signal Region\nchr6\t170376900\t170401000\tHigh Signal Region\nchr6\t170465400\t170468400\tHigh Signal Region\nchr7\t0\t49600\tHigh Signal Region\nchr7\t224500\t241300\tHigh Signal Region\nchr7\t904700\t907100\tLow Mappability\nchr7\t1271400\t1273500\tHigh Signal Region\nchr7\t45251000\t45253000\tHigh Signal Region\nchr7\t56369500\t56375600\tHigh Signal Region\nchr7\t57485300\t57497800\tHigh Signal Region\nchr7\t57611600\t57637700\tLow Mappability\nchr7\t58031800\t60997400\tHigh Signal Region\nchr7\t61017800\t61075200\tHigh Signal Region\nchr7\t61102900\t61725200\tLow Mappability\nchr7\t62265700\t62409500\tHigh Signal Region\nchr7\t62430000\t62520600\tHigh Signal Region\nchr7\t65488000\t65496500\tHigh Signal Region\nchr7\t100951400\t100968300\tHigh Signal Region\nchr7\t100991500\t101004600\tHigh Signal Region\nchr7\t102474700\t102686400\tHigh Signal Region\nchr7\t142665100\t142668500\tHigh Signal Region\nchr7\t144180800\t144377300\tLow Mappability\nchr7\t145996400\t146018600\tHigh Signal Region\nchr7\t152375800\t152435100\tHigh Signal Region\nchr7\t158131400\t158156200\tHigh Signal Region\nchr7\t158594300\t158596200\tHigh Signal Region\nchr7\t158893100\t158918100\tHigh Signal Region\nchr7\t159334900\t159345900\tHigh Signal Region\nchr8\t7209800\t7914700\tHigh Signal Region\nchr8\t7940500\t8075700\tHigh Signal Region\nchr8\t8128200\t8204600\tHigh Signal Region\nchr8\t12136900\t12614300\tHigh Signal Region\nchr8\t43236700\t43262600\tHigh Signal Region\nchr8\t43937900\t45969600\tHigh Signal Region\nchr8\t46829400\t46832000\tHigh Signal Region\nchr8\t57204900\t57216100\tHigh Signal Region\nchr8\t59168700\t59170400\tHigh Signal Region\nchr8\t67584500\t67592700\tHigh Signal Region\nchr8\t69688400\t69691100\tHigh Signal Region\nchr8\t71406700\t71412400\tHigh Signal Region\nchr8\t75444100\t75448200\tHigh Signal Region\nchr8\t81841500\t81851900\tHigh Signal Region\nchr8\t85642100\t85829300\tHigh Signal Region\nchr8\t88685900\t88691700\tHigh Signal Region\nchr8\t96171200\t96173100\tHigh Signal Region\nchr8\t99494900\t99496800\tHigh Signal Region\nchr8\t105789200\t105793800\tHigh Signal Region\nchr8\t141491400\t141493500\tHigh Signal Region\nchr8\t141871100\t141875200\tHigh Signal Region\nchr8\t143641400\t143670500\tHigh Signal Region\nchr8\t144124800\t144137600\tHigh Signal Region\nchr9\t319900\t322400\tHigh Signal Region\nchr9\t33656600\t33660000\tHigh Signal Region\nchr9\t35912600\t35915300\tHigh Signal Region\nchr9\t38824200\t39089400\tHigh Signal Region\nchr9\t39846200\t40771100\tHigh Signal Region\nchr9\t40792500\t41323100\tHigh Signal Region\nchr9\t41492300\t41635600\tHigh Signal Region\nchr9\t41661300\t42119600\tLow Mappability\nchr9\t42364000\t42410600\tHigh Signal Region\nchr9\t42899400\t42901300\tHigh Signal Region\nchr9\t43263100\t61518900\tHigh Signal Region\nchr9\t61735300\t63548000\tHigh Signal Region\nchr9\t63761400\t64027300\tHigh Signal Region\nchr9\t64135000\t65390600\tHigh Signal Region\nchr9\t65579400\t66874600\tHigh Signal Region\nchr9\t66959000\t68398100\tHigh Signal Region\nchr9\t70037200\t70039600\tHigh Signal Region\nchr9\t76174300\t76176200\tHigh Signal Region\nchr9\t83222900\t83226900\tHigh Signal Region\nchr9\t85071600\t85075100\tHigh Signal Region\nchr9\t85164800\t85166100\tHigh Signal Region\nchr9\t108502000\t108506600\tHigh Signal Region\nchr9\t134164500\t134185500\tHigh Signal Region\nchr9\t137326800\t137330600\tHigh Signal Region\nchr9\t137715200\t137722200\tLow Mappability\nchr9\t137841200\t137846800\tLow Mappability\nchr9\t138222000\t138394700\tHigh Signal Region\nchrX\t0\t329300\tHigh Signal Region\nchrX\t362400\t388500\tHigh Signal Region\nchrX\t456500\t531800\tHigh Signal Region\nchrX\t723800\t739500\tHigh Signal Region\nchrX\t864500\t930400\tHigh Signal Region\nchrX\t1049100\t1054300\tHigh Signal Region\nchrX\t1085100\t1175500\tHigh Signal Region\nchrX\t1200600\t1209400\tHigh Signal Region\nchrX\t1249200\t1269000\tHigh Signal Region\nchrX\t1289500\t1298900\tHigh Signal Region\nchrX\t1365300\t1458700\tHigh Signal Region\nchrX\t1480900\t1492800\tHigh Signal Region\nchrX\t1816200\t1820600\tHigh Signal Region\nchrX\t2223900\t2521900\tHigh Signal Region\nchrX\t2580600\t2751300\tHigh Signal Region\nchrX\t3966700\t3968700\tHigh Signal Region\nchrX\t5481200\t5486100\tHigh Signal Region\nchrX\t6933400\t6938700\tHigh Signal Region\nchrX\t7587600\t7591800\tHigh Signal Region\nchrX\t9403600\t9415100\tHigh Signal Region\nchrX\t10785000\t10809700\tHigh Signal Region\nchrX\t10966600\t10976800\tHigh Signal Region\nchrX\t11218800\t11221100\tLow Mappability\nchrX\t11840900\t11848000\tHigh Signal Region\nchrX\t14085100\t14109500\tHigh Signal Region\nchrX\t14286500\t14289300\tHigh Signal Region\nchrX\t16361200\t16366000\tHigh Signal Region\nchrX\t16498100\t16503400\tHigh Signal Region\nchrX\t19940200\t19946300\tHigh Signal Region\nchrX\t21340600\t21345700\tHigh Signal Region\nchrX\t25773300\t25776000\tHigh Signal Region\nchrX\t26176400\t26181400\tHigh Signal Region\nchrX\t30767800\t30772600\tHigh Signal Region\nchrX\t31077600\t31082600\tHigh Signal Region\nchrX\t31511400\t31535800\tHigh Signal Region\nchrX\t34416800\t34425900\tHigh Signal Region\nchrX\t36465200\t36471200\tHigh Signal Region\nchrX\t37628400\t37633500\tHigh Signal Region\nchrX\t42872300\t42910700\tHigh Signal Region\nchrX\t49317500\t49623500\tHigh Signal Region\nchrX\t50019400\t50033700\tHigh Signal Region\nchrX\t50056700\t50066100\tHigh Signal Region\nchrX\t51202300\t51268100\tHigh Signal Region\nchrX\t51427500\t51432400\tHigh Signal Region\nchrX\t52175000\t52228100\tHigh Signal Region\nchrX\t52442800\t52538100\tHigh Signal Region\nchrX\t53761700\t53789500\tHigh Signal Region\nchrX\t55180400\t55184500\tHigh Signal Region\nchrX\t56754900\t56781100\tLow Mappability\nchrX\t57712300\t57719700\tHigh Signal Region\nchrX\t58467900\t62522800\tHigh Signal Region\nchrX\t63129600\t63290600\tLow Mappability\nchrX\t67311800\t67323800\tHigh Signal Region\nchrX\t67626800\t67632300\tHigh Signal Region\nchrX\t68217300\t68230200\tHigh Signal Region\nchrX\t70600000\t70603800\tHigh Signal Region\nchrX\t70640600\t70645000\tHigh Signal Region\nchrX\t70963600\t70964900\tHigh Signal Region\nchrX\t71978800\t71980500\tHigh Signal Region\nchrX\t72489400\t72490800\tHigh Signal Region\nchrX\t72743200\t73035800\tHigh Signal Region\nchrX\t73381000\t73387000\tHigh Signal Region\nchrX\t73887000\t73891300\tHigh Signal Region\nchrX\t74660000\t74718100\tHigh Signal Region\nchrX\t74789000\t74794000\tHigh Signal Region\nchrX\t74952200\t74995200\tHigh Signal Region\nchrX\t78802400\t78804500\tHigh Signal Region\nchrX\t79765500\t79789600\tHigh Signal Region\nchrX\t80534100\t80537000\tHigh Signal Region\nchrX\t82849700\t82859300\tLow Mappability\nchrX\t83752100\t83756900\tHigh Signal Region\nchrX\t86046600\t86076600\tHigh Signal Region\nchrX\t86395500\t86398100\tHigh Signal Region\nchrX\t86970000\t86975600\tHigh Signal Region\nchrX\t87220500\t87222100\tHigh Signal Region\nchrX\t89060200\t89062700\tHigh Signal Region\nchrX\t89202500\t89208400\tHigh Signal Region\nchrX\t91332900\t91336600\tHigh Signal Region\nchrX\t93618000\t93633400\tHigh Signal Region\nchrX\t94863600\t94868300\tHigh Signal Region\nchrX\t97509600\t97515000\tHigh Signal Region\nchrX\t100135800\t100141000\tHigh Signal Region\nchrX\t100257100\t100261600\tHigh Signal Region\nchrX\t101471700\t101474900\tHigh Signal Region\nchrX\t102188700\t102489200\tHigh Signal Region\nchrX\t103851800\t103897800\tHigh Signal Region\nchrX\t106755500\t106769400\tHigh Signal Region\nchrX\t106813900\t106830900\tHigh Signal Region\nchrX\t107515800\t107517200\tHigh Signal Region\nchrX\t109034800\t109069100\tHigh Signal Region\nchrX\t109114900\t109119400\tHigh Signal Region\nchrX\t109520800\t109525700\tHigh Signal Region\nchrX\t109985900\t109987300\tHigh Signal Region\nchrX\t110816700\t110833400\tHigh Signal Region\nchrX\t111416100\t111418000\tHigh Signal Region\nchrX\t113141700\t113143600\tHigh Signal Region\nchrX\t114701600\t114724300\tHigh Signal Region\nchrX\t115725600\t115889600\tHigh Signal Region\nchrX\t116557600\t116595600\tHigh Signal Region\nchrX\t117874100\t117880000\tHigh Signal Region\nchrX\t118009000\t118037800\tHigh Signal Region\nchrX\t118070900\t118072700\tHigh Signal Region\nchrX\t121263700\t121268100\tHigh Signal Region\nchrX\t121299200\t121300600\tHigh Signal Region\nchrX\t122528400\t122550000\tHigh Signal Region\nchrX\t124584300\t124588400\tHigh Signal Region\nchrX\t125927600\t125937100\tHigh Signal Region\nchrX\t126463700\t126474200\tHigh Signal Region\nchrX\t127116700\t127122600\tHigh Signal Region\nchrX\t127362200\t127368300\tHigh Signal Region\nchrX\t128785000\t128788700\tHigh Signal Region\nchrX\t129337600\t129357900\tHigh Signal Region\nchrX\t129388400\t129408400\tHigh Signal Region\nchrX\t130567700\t130572000\tHigh Signal Region\nchrX\t131152200\t131157400\tHigh Signal Region\nchrX\t131378300\t131383300\tHigh Signal Region\nchrX\t131664300\t131670000\tHigh Signal Region\nchrX\t132284600\t132320400\tHigh Signal Region\nchrX\t133108600\t133116500\tHigh Signal Region\nchrX\t135718600\t135888700\tHigh Signal Region\nchrX\t137074700\t137079100\tHigh Signal Region\nchrX\t137436600\t137439300\tHigh Signal Region\nchrX\t138300600\t138302200\tHigh Signal Region\nchrX\t139437600\t139446800\tHigh Signal Region\nchrX\t139621500\t139622800\tHigh Signal Region\nchrX\t140722400\t140726100\tHigh Signal Region\nchrX\t141000400\t141108300\tHigh Signal Region\nchrX\t142478000\t142483800\tHigh Signal Region\nchrX\t142892300\t142911600\tHigh Signal Region\nchrX\t143352000\t143356500\tHigh Signal Region\nchrX\t144404500\t144475900\tLow Mappability\nchrX\t147281700\t147287100\tHigh Signal Region\nchrX\t147653800\t147659900\tHigh Signal Region\nchrX\t148123500\t148129000\tHigh Signal Region\nchrX\t148347100\t148378700\tHigh Signal Region\nchrX\t149437900\t149441900\tHigh Signal Region\nchrX\t150024800\t150026200\tHigh Signal Region\nchrX\t152173800\t152175100\tHigh Signal Region\nchrX\t153251200\t153316400\tHigh Signal Region\nchrX\t154870000\t154890200\tHigh Signal Region\nchrX\t154938900\t154945100\tHigh Signal Region\nchrX\t155299600\t155305100\tHigh Signal Region\nchrX\t155454000\t155522000\tHigh Signal Region\nchrX\t155700400\t155727500\tHigh Signal Region\nchrX\t155983500\t156040800\tHigh Signal Region\nchrY\t4343800\t4345800\tHigh Signal Region\nchrY\t10246200\t11041200\tHigh Signal Region\nchrY\t11072100\t11335300\tHigh Signal Region\nchrY\t11486600\t11757800\tHigh Signal Region\nchrY\t26637300\t57227400\tHigh Signal Region\n" }, { "path": "assets/blacklists/v2.0/mm10-blacklist.v2.bed", "content": "chr10\t0\t3135400\tHigh Signal Region\nchr10\t3218900\t3276600\tLow Mappability\nchr10\t3576900\t3627700\tLow Mappability\nchr10\t4191100\t4197600\tLow Mappability\nchr10\t4613500\t4615400\tHigh Signal Region\nchr10\t4761300\t4763900\tHigh Signal Region\nchr10\t5080800\t5096600\tLow Mappability\nchr10\t5580100\t5586600\tLow Mappability\nchr10\t6281200\t6286700\tHigh Signal Region\nchr10\t6740200\t6742100\tHigh Signal Region\nchr10\t7396300\t7429800\tHigh Signal Region\nchr10\t7633600\t7636600\tLow Mappability\nchr10\t7889700\t7897500\tHigh Signal Region\nchr10\t8144900\t8153000\tHigh Signal Region\nchr10\t8264000\t8269200\tHigh Signal Region\nchr10\t8382400\t8404400\tHigh Signal Region\nchr10\t8599200\t8606400\tLow Mappability\nchr10\t10012200\t10033400\tHigh Signal Region\nchr10\t10566900\t10593500\tHigh Signal Region\nchr10\t11218400\t11224800\tLow Mappability\nchr10\t11351800\t11406300\tLow Mappability\nchr10\t11491200\t11493100\tHigh Signal Region\nchr10\t11612300\t11642500\tHigh Signal Region\nchr10\t11692500\t11701300\tLow Mappability\nchr10\t12266500\t12273000\tHigh Signal Region\nchr10\t12385800\t12396000\tHigh Signal Region\nchr10\t13401200\t13403100\tHigh Signal Region\nchr10\t14559900\t14577100\tHigh Signal Region\nchr10\t14646300\t14664500\tLow Mappability\nchr10\t14923800\t14928300\tHigh Signal Region\nchr10\t15047600\t15083100\tHigh Signal Region\nchr10\t15528600\t15534200\tHigh Signal Region\nchr10\t15567000\t15641800\tHigh Signal Region\nchr10\t16967500\t16971600\tHigh Signal Region\nchr10\t17499600\t17501700\tHigh Signal Region\nchr10\t18555500\t18558100\tHigh Signal Region\nchr10\t19427600\t19429100\tHigh Signal Region\nchr10\t19538800\t19546100\tLow Mappability\nchr10\t19772200\t19801600\tHigh Signal Region\nchr10\t20458900\t20460800\tHigh Signal Region\nchr10\t21208600\t21216600\tLow Mappability\nchr10\t21278500\t21313500\tHigh Signal Region\nchr10\t21642200\t21649600\tLow Mappability\nchr10\t21727800\t21736400\tLow Mappability\nchr10\t22031300\t22063500\tHigh Signal Region\nchr10\t22127200\t22164500\tHigh Signal Region\nchr10\t22186700\t22290500\tHigh Signal Region\nchr10\t22369100\t22472300\tHigh Signal Region\nchr10\t22683100\t22690600\tLow Mappability\nchr10\t22935900\t22941800\tHigh Signal Region\nchr10\t24687500\t24691700\tLow Mappability\nchr10\t25091400\t25106900\tLow Mappability\nchr10\t25622900\t25629400\tLow Mappability\nchr10\t25968400\t25973400\tLow Mappability\nchr10\t26641500\t26662800\tLow Mappability\nchr10\t27403200\t27407600\tHigh Signal Region\nchr10\t27904000\t27909500\tHigh Signal Region\nchr10\t28908500\t28940600\tHigh Signal Region\nchr10\t29243900\t29249600\tHigh Signal Region\nchr10\t29924300\t29930700\tLow Mappability\nchr10\t29954000\t29971900\tHigh Signal Region\nchr10\t30553000\t30577100\tHigh Signal Region\nchr10\t31054900\t31095900\tLow Mappability\nchr10\t31406500\t31411100\tHigh Signal Region\nchr10\t31750000\t31757100\tLow Mappability\nchr10\t31878400\t31885800\tHigh Signal Region\nchr10\t31980100\t32000400\tLow Mappability\nchr10\t32039700\t32045000\tHigh Signal Region\nchr10\t32176100\t32182400\tHigh Signal Region\nchr10\t32499200\t32529900\tHigh Signal Region\nchr10\t32816400\t32857200\tHigh Signal Region\nchr10\t33315300\t33319800\tHigh Signal Region\nchr10\t33492300\t33508900\tHigh Signal Region\nchr10\t33886600\t33901100\tLow Mappability\nchr10\t34739400\t34749100\tLow Mappability\nchr10\t35669300\t35725500\tHigh Signal Region\nchr10\t36130200\t36135500\tHigh Signal Region\nchr10\t36160700\t36166700\tHigh Signal Region\nchr10\t36594500\t36597500\tLow Mappability\nchr10\t36942200\t36948800\tLow Mappability\nchr10\t37186500\t37189300\tHigh Signal Region\nchr10\t37799700\t37821400\tHigh Signal Region\nchr10\t37964600\t37970100\tHigh Signal Region\nchr10\t38590100\t38606100\tHigh Signal Region\nchr10\t38637900\t38644200\tHigh Signal Region\nchr10\t38729400\t38782700\tHigh Signal Region\nchr10\t38933500\t38956500\tHigh Signal Region\nchr10\t39126700\t39129400\tHigh Signal Region\nchr10\t39760700\t39764700\tHigh Signal Region\nchr10\t41185700\t41195800\tHigh Signal Region\nchr10\t41840500\t41859100\tLow Mappability\nchr10\t43769400\t43773800\tHigh Signal Region\nchr10\t44206300\t44254100\tHigh Signal Region\nchr10\t45515000\t45588000\tLow Mappability\nchr10\t45624800\t45628400\tHigh Signal Region\nchr10\t46136500\t46139300\tHigh Signal Region\nchr10\t46468300\t46472100\tHigh Signal Region\nchr10\t46500500\t46538800\tHigh Signal Region\nchr10\t46789300\t46812500\tHigh Signal Region\nchr10\t46966700\t47009000\tHigh Signal Region\nchr10\t47048600\t47074700\tLow Mappability\nchr10\t47663600\t47683500\tHigh Signal Region\nchr10\t47743600\t47758500\tHigh Signal Region\nchr10\t47875400\t47881600\tHigh Signal Region\nchr10\t48032400\t48058800\tHigh Signal Region\nchr10\t48677400\t48682800\tHigh Signal Region\nchr10\t49823500\t49842200\tHigh Signal Region\nchr10\t50029200\t50035300\tHigh Signal Region\nchr10\t50109900\t50115500\tHigh Signal Region\nchr10\t50178500\t50184800\tHigh Signal Region\nchr10\t50253700\t50296500\tHigh Signal Region\nchr10\t50333400\t50335300\tHigh Signal Region\nchr10\t50524000\t50553900\tHigh Signal Region\nchr10\t51126200\t51132900\tHigh Signal Region\nchr10\t51436800\t51448000\tHigh Signal Region\nchr10\t51470300\t51474900\tHigh Signal Region\nchr10\t51882900\t51888000\tLow Mappability\nchr10\t52052600\t52059000\tLow Mappability\nchr10\t52089600\t52148500\tHigh Signal Region\nchr10\t52522600\t52599800\tHigh Signal Region\nchr10\t53073900\t53081100\tHigh Signal Region\nchr10\t53569600\t53576000\tLow Mappability\nchr10\t54216200\t54222900\tHigh Signal Region\nchr10\t54588800\t54619900\tLow Mappability\nchr10\t55080400\t55090500\tHigh Signal Region\nchr10\t55654500\t55659600\tHigh Signal Region\nchr10\t55715600\t55751000\tHigh Signal Region\nchr10\t55841700\t55847900\tHigh Signal Region\nchr10\t56250200\t56293900\tHigh Signal Region\nchr10\t56701000\t56728000\tHigh Signal Region\nchr10\t56894100\t56897300\tHigh Signal Region\nchr10\t57099200\t57153200\tHigh Signal Region\nchr10\t57239100\t57245400\tHigh Signal Region\nchr10\t57326900\t57333900\tHigh Signal Region\nchr10\t57434000\t57456500\tHigh Signal Region\nchr10\t57678600\t57684900\tHigh Signal Region\nchr10\t57862800\t58240900\tHigh Signal Region\nchr10\t58566200\t58570900\tHigh Signal Region\nchr10\t59381400\t59396800\tLow Mappability\nchr10\t59850500\t59922300\tLow Mappability\nchr10\t60444900\t60446800\tHigh Signal Region\nchr10\t60546600\t60553100\tLow Mappability\nchr10\t61373100\t61375000\tHigh Signal Region\nchr10\t63103900\t63111200\tLow Mappability\nchr10\t63508800\t63519000\tHigh Signal Region\nchr10\t63833800\t63835000\tHigh Signal Region\nchr10\t64418600\t64420000\tHigh Signal Region\nchr10\t65166300\t65172600\tHigh Signal Region\nchr10\t65450400\t65477700\tHigh Signal Region\nchr10\t65638900\t65670200\tHigh Signal Region\nchr10\t65938900\t65956300\tLow Mappability\nchr10\t66422900\t66431000\tHigh Signal Region\nchr10\t66662400\t66678300\tHigh Signal Region\nchr10\t69030100\t69065800\tHigh Signal Region\nchr10\t70657500\t70668500\tHigh Signal Region\nchr10\t70785400\t70798600\tLow Mappability\nchr10\t71012700\t71019200\tLow Mappability\nchr10\t71111600\t71114200\tLow Mappability\nchr10\t71510600\t71637800\tHigh Signal Region\nchr10\t71691300\t71698600\tLow Mappability\nchr10\t72292400\t72314300\tHigh Signal Region\nchr10\t72359200\t72360700\tHigh Signal Region\nchr10\t72493500\t72499200\tHigh Signal Region\nchr10\t72590700\t72591900\tHigh Signal Region\nchr10\t72690900\t72709500\tHigh Signal Region\nchr10\t73378200\t73380100\tHigh Signal Region\nchr10\t73576400\t73601900\tHigh Signal Region\nchr10\t74433300\t74439500\tHigh Signal Region\nchr10\t74655700\t74672200\tHigh Signal Region\nchr10\t74715300\t74746600\tHigh Signal Region\nchr10\t74857500\t74888000\tHigh Signal Region\nchr10\t76835100\t76852400\tHigh Signal Region\nchr10\t77950600\t77979500\tLow Mappability\nchr10\t78008300\t78028800\tLow Mappability\nchr10\t78637000\t78696000\tHigh Signal Region\nchr10\t78731500\t78735800\tHigh Signal Region\nchr10\t78803500\t78823100\tLow Mappability\nchr10\t79207800\t79259400\tHigh Signal Region\nchr10\t79314000\t79354000\tLow Mappability\nchr10\t80102300\t80116000\tHigh Signal Region\nchr10\t80928600\t80996300\tLow Mappability\nchr10\t81167600\t81199400\tHigh Signal Region\nchr10\t81600900\t81997900\tHigh Signal Region\nchr10\t82517500\t82538800\tHigh Signal Region\nchr10\t82571100\t82575200\tHigh Signal Region\nchr10\t82939800\t82956300\tHigh Signal Region\nchr10\t83386600\t83392400\tLow Mappability\nchr10\t83670800\t83678100\tLow Mappability\nchr10\t83768200\t83792700\tLow Mappability\nchr10\t84155900\t84180800\tLow Mappability\nchr10\t84436900\t84473700\tLow Mappability\nchr10\t84744500\t84750100\tLow Mappability\nchr10\t85413200\t85419700\tLow Mappability\nchr10\t85696600\t85732800\tHigh Signal Region\nchr10\t85840200\t85872500\tHigh Signal Region\nchr10\t86561700\t86565700\tHigh Signal Region\nchr10\t88628700\t88658500\tLow Mappability\nchr10\t88963900\t88968200\tLow Mappability\nchr10\t89398700\t89400100\tHigh Signal Region\nchr10\t89949700\t89964500\tHigh Signal Region\nchr10\t90249000\t90255300\tHigh Signal Region\nchr10\t90324500\t90329800\tLow Mappability\nchr10\t90471200\t90474200\tLow Mappability\nchr10\t91252200\t91256900\tHigh Signal Region\nchr10\t91928900\t91944500\tHigh Signal Region\nchr10\t92909200\t92915800\tHigh Signal Region\nchr10\t94362500\t94369300\tLow Mappability\nchr10\t94591500\t94610000\tHigh Signal Region\nchr10\t94871200\t94873100\tHigh Signal Region\nchr10\t96068700\t96078800\tHigh Signal Region\nchr10\t96157200\t96162600\tLow Mappability\nchr10\t96192400\t96199800\tLow Mappability\nchr10\t97320500\t97329700\tHigh Signal Region\nchr10\t97525500\t97534200\tLow Mappability\nchr10\t97755000\t97761200\tHigh Signal Region\nchr10\t97896600\t97920300\tHigh Signal Region\nchr10\t98337800\t98343700\tHigh Signal Region\nchr10\t98433100\t98444100\tHigh Signal Region\nchr10\t100310500\t100395900\tHigh Signal Region\nchr10\t102667700\t102669600\tHigh Signal Region\nchr10\t102859800\t102861500\tHigh Signal Region\nchr10\t103500200\t103519100\tHigh Signal Region\nchr10\t103547000\t103548600\tHigh Signal Region\nchr10\t103569600\t103575200\tHigh Signal Region\nchr10\t103600400\t103684400\tHigh Signal Region\nchr10\t103936700\t103942500\tHigh Signal Region\nchr10\t104380700\t104382300\tHigh Signal Region\nchr10\t104493600\t104499800\tHigh Signal Region\nchr10\t104539700\t104562500\tLow Mappability\nchr10\t104748100\t104771500\tHigh Signal Region\nchr10\t104819400\t104862500\tLow Mappability\nchr10\t104966900\t105001700\tLow Mappability\nchr10\t105177000\t105181900\tLow Mappability\nchr10\t105672500\t105678000\tLow Mappability\nchr10\t106166900\t106235700\tHigh Signal Region\nchr10\t106382800\t106403000\tHigh Signal Region\nchr10\t106427100\t106453600\tHigh Signal Region\nchr10\t106529600\t106535200\tLow Mappability\nchr10\t107125500\t107136900\tLow Mappability\nchr10\t107551800\t107560700\tHigh Signal Region\nchr10\t107845300\t107863900\tHigh Signal Region\nchr10\t107978900\t108006700\tLow Mappability\nchr10\t109212600\t109216800\tHigh Signal Region\nchr10\t109315100\t109322400\tLow Mappability\nchr10\t109941600\t109948000\tHigh Signal Region\nchr10\t110104900\t110111300\tLow Mappability\nchr10\t110504500\t110516000\tHigh Signal Region\nchr10\t110667700\t110700900\tLow Mappability\nchr10\t111217500\t111219000\tHigh Signal Region\nchr10\t112013700\t112021700\tHigh Signal Region\nchr10\t112053500\t112058400\tLow Mappability\nchr10\t112540600\t112542100\tHigh Signal Region\nchr10\t112587000\t112611100\tHigh Signal Region\nchr10\t112682400\t112722100\tLow Mappability\nchr10\t113722600\t113729800\tLow Mappability\nchr10\t114167300\t114174900\tHigh Signal Region\nchr10\t114736400\t114738300\tHigh Signal Region\nchr10\t114860600\t114866900\tHigh Signal Region\nchr10\t115641300\t115643100\tHigh Signal Region\nchr10\t116606200\t116613400\tLow Mappability\nchr10\t116762000\t116764200\tHigh Signal Region\nchr10\t116878000\t116879900\tHigh Signal Region\nchr10\t117476200\t117491000\tHigh Signal Region\nchr10\t118014300\t118033200\tHigh Signal Region\nchr10\t118054000\t118076600\tHigh Signal Region\nchr10\t118199900\t118279700\tLow Mappability\nchr10\t118910200\t118917100\tHigh Signal Region\nchr10\t118937400\t118953000\tLow Mappability\nchr10\t119698800\t119701600\tLow Mappability\nchr10\t120974800\t120977500\tHigh Signal Region\nchr10\t121136000\t121143400\tLow Mappability\nchr10\t121164700\t121169300\tLow Mappability\nchr10\t121566100\t121580200\tHigh Signal Region\nchr10\t121707800\t121713500\tHigh Signal Region\nchr10\t121762300\t121769400\tHigh Signal Region\nchr10\t122141100\t122166000\tHigh Signal Region\nchr10\t122346900\t122371300\tLow Mappability\nchr10\t122632400\t122638000\tHigh Signal Region\nchr10\t122832900\t122839300\tHigh Signal Region\nchr10\t123792900\t123797100\tHigh Signal Region\nchr10\t124412900\t124433300\tHigh Signal Region\nchr10\t124576300\t124583500\tLow Mappability\nchr10\t124605700\t124611000\tLow Mappability\nchr10\t124680500\t124686200\tLow Mappability\nchr10\t124760500\t124788800\tHigh Signal Region\nchr10\t125819500\t125825700\tHigh Signal Region\nchr10\t125869000\t125871400\tHigh Signal Region\nchr10\t126262200\t126291600\tLow Mappability\nchr10\t127779500\t127797900\tHigh Signal Region\nchr10\t129189500\t129217200\tHigh Signal Region\nchr10\t129388700\t129419600\tLow Mappability\nchr10\t129443000\t129454800\tHigh Signal Region\nchr10\t129734500\t129736400\tHigh Signal Region\nchr10\t129925300\t129940600\tLow Mappability\nchr10\t130039500\t130052900\tHigh Signal Region\nchr10\t130396900\t130408000\tHigh Signal Region\nchr10\t130542000\t130694900\tHigh Signal Region\nchr11\t0\t3201000\tHigh Signal Region\nchr11\t5167600\t5182600\tHigh Signal Region\nchr11\t5361500\t5365400\tLow Mappability\nchr11\t5552700\t5558200\tLow Mappability\nchr11\t6141300\t6148700\tLow Mappability\nchr11\t7489400\t7492300\tHigh Signal Region\nchr11\t7752300\t7774500\tLow Mappability\nchr11\t8058600\t8083100\tLow Mappability\nchr11\t8354900\t8370700\tHigh Signal Region\nchr11\t8907200\t8936100\tLow Mappability\nchr11\t9707900\t9715100\tLow Mappability\nchr11\t9807600\t9814200\tLow Mappability\nchr11\t10252000\t10266800\tHigh Signal Region\nchr11\t10760200\t10770800\tLow Mappability\nchr11\t11287200\t11295100\tHigh Signal Region\nchr11\t12129400\t12163100\tHigh Signal Region\nchr11\t12507200\t12512700\tLow Mappability\nchr11\t12561900\t12569100\tLow Mappability\nchr11\t12750500\t12802700\tHigh Signal Region\nchr11\t12856200\t12863700\tHigh Signal Region\nchr11\t12953900\t12960700\tLow Mappability\nchr11\t14896500\t14922100\tHigh Signal Region\nchr11\t15227600\t15235000\tLow Mappability\nchr11\t16022400\t16029000\tHigh Signal Region\nchr11\t16326500\t16331700\tHigh Signal Region\nchr11\t16418200\t16419600\tHigh Signal Region\nchr11\t16567100\t16573100\tHigh Signal Region\nchr11\t17401400\t17407800\tHigh Signal Region\nchr11\t18330900\t18342700\tHigh Signal Region\nchr11\t18773800\t18780100\tHigh Signal Region\nchr11\t19566100\t19570600\tLow Mappability\nchr11\t19788600\t19809400\tLow Mappability\nchr11\t20310000\t20312000\tHigh Signal Region\nchr11\t20377900\t20380400\tHigh Signal Region\nchr11\t22322000\t22340700\tLow Mappability\nchr11\t22395200\t22432900\tLow Mappability\nchr11\t22534700\t22537000\tLow Mappability\nchr11\t23218500\t23258100\tLow Mappability\nchr11\t23522600\t23552900\tHigh Signal Region\nchr11\t24527400\t24529500\tLow Mappability\nchr11\t25196800\t25217300\tHigh Signal Region\nchr11\t25796400\t25802200\tLow Mappability\nchr11\t26898500\t26900500\tHigh Signal Region\nchr11\t27525200\t27541400\tHigh Signal Region\nchr11\t28097200\t28104500\tLow Mappability\nchr11\t29064100\t29129900\tLow Mappability\nchr11\t29259900\t29291300\tHigh Signal Region\nchr11\t29586000\t29592400\tLow Mappability\nchr11\t30511100\t30535400\tHigh Signal Region\nchr11\t31343800\t31345700\tLow Mappability\nchr11\t33062300\t33068800\tLow Mappability\nchr11\t34541000\t34683100\tHigh Signal Region\nchr11\t37482400\t37484900\tHigh Signal Region\nchr11\t40230800\t40248400\tHigh Signal Region\nchr11\t40625500\t40640300\tLow Mappability\nchr11\t40796600\t40860600\tHigh Signal Region\nchr11\t40887700\t40915600\tHigh Signal Region\nchr11\t41631700\t41633600\tHigh Signal Region\nchr11\t43237300\t43239300\tLow Mappability\nchr11\t43286400\t43329800\tHigh Signal Region\nchr11\t43454800\t43462300\tLow Mappability\nchr11\t43659700\t43682100\tLow Mappability\nchr11\t45584200\t45655700\tLow Mappability\nchr11\t46412300\t46415000\tLow Mappability\nchr11\t46492800\t46514400\tLow Mappability\nchr11\t47847500\t47860600\tHigh Signal Region\nchr11\t48451800\t48536100\tHigh Signal Region\nchr11\t48929800\t49060400\tLow Mappability\nchr11\t50445100\t50469600\tHigh Signal Region\nchr11\t51437600\t51456700\tHigh Signal Region\nchr11\t51664900\t51690400\tLow Mappability\nchr11\t54135500\t54141600\tHigh Signal Region\nchr11\t54576500\t54583300\tLow Mappability\nchr11\t55240500\t55248100\tLow Mappability\nchr11\t56588500\t56594500\tHigh Signal Region\nchr11\t57301700\t57303600\tHigh Signal Region\nchr11\t60558900\t60699000\tLow Mappability\nchr11\t61407400\t61427800\tLow Mappability\nchr11\t61593700\t61596500\tLow Mappability\nchr11\t62879300\t62901500\tHigh Signal Region\nchr11\t63467600\t63475000\tLow Mappability\nchr11\t64568100\t64574200\tHigh Signal Region\nchr11\t64681700\t64683600\tLow Mappability\nchr11\t64791900\t64827100\tLow Mappability\nchr11\t65451700\t65458800\tLow Mappability\nchr11\t66629900\t66634100\tHigh Signal Region\nchr11\t66947700\t66958600\tLow Mappability\nchr11\t67866400\t67872800\tLow Mappability\nchr11\t70155800\t70162400\tLow Mappability\nchr11\t71505700\t71512100\tLow Mappability\nchr11\t71875200\t71881700\tLow Mappability\nchr11\t73436900\t73439100\tLow Mappability\nchr11\t74128800\t74136200\tLow Mappability\nchr11\t74199900\t74226800\tLow Mappability\nchr11\t74301700\t74319600\tHigh Signal Region\nchr11\t74540000\t74548400\tLow Mappability\nchr11\t74884300\t74899000\tLow Mappability\nchr11\t76828100\t76868600\tLow Mappability\nchr11\t77255000\t77257100\tLow Mappability\nchr11\t79845100\t79847300\tLow Mappability\nchr11\t79872400\t79877100\tLow Mappability\nchr11\t79917300\t79920800\tLow Mappability\nchr11\t81545400\t81552800\tLow Mappability\nchr11\t82123300\t82144400\tHigh Signal Region\nchr11\t82333900\t82338400\tLow Mappability\nchr11\t83050300\t83093600\tHigh Signal Region\nchr11\t83126000\t83172300\tLow Mappability\nchr11\t85046500\t85067800\tHigh Signal Region\nchr11\t85285400\t85292700\tHigh Signal Region\nchr11\t88910900\t88917600\tLow Mappability\nchr11\t88965900\t88971900\tHigh Signal Region\nchr11\t89080800\t89101300\tHigh Signal Region\nchr11\t90504000\t90510500\tHigh Signal Region\nchr11\t90829400\t90835000\tLow Mappability\nchr11\t90901700\t90908400\tLow Mappability\nchr11\t90958500\t91026800\tLow Mappability\nchr11\t91047200\t91049300\tLow Mappability\nchr11\t92099000\t92108200\tHigh Signal Region\nchr11\t93409300\t93428900\tHigh Signal Region\nchr11\t94622900\t94629900\tLow Mappability\nchr11\t96065000\t96093900\tHigh Signal Region\nchr11\t98586900\t98673900\tLow Mappability\nchr11\t99712600\t99717300\tHigh Signal Region\nchr11\t100662800\t100669700\tLow Mappability\nchr11\t101731800\t101741400\tHigh Signal Region\nchr11\t102992300\t103049900\tLow Mappability\nchr11\t104239000\t104242600\tLow Mappability\nchr11\t106028100\t106037400\tHigh Signal Region\nchr11\t106254800\t106297600\tHigh Signal Region\nchr11\t106943500\t106950100\tLow Mappability\nchr11\t107188200\t107200400\tHigh Signal Region\nchr11\t107281300\t107283200\tHigh Signal Region\nchr11\t108377600\t108404500\tLow Mappability\nchr11\t108649800\t108655400\tLow Mappability\nchr11\t109010700\t109024400\tHigh Signal Region\nchr11\t109998500\t110024600\tLow Mappability\nchr11\t110421300\t110423200\tHigh Signal Region\nchr11\t111182400\t111189800\tLow Mappability\nchr11\t111215500\t111234900\tLow Mappability\nchr11\t111353300\t111360000\tLow Mappability\nchr11\t111855400\t111857100\tHigh Signal Region\nchr11\t112010600\t112016400\tHigh Signal Region\nchr11\t114456300\t114462800\tLow Mappability\nchr11\t115014300\t115046900\tLow Mappability\nchr11\t115611200\t115665700\tHigh Signal Region\nchr11\t115754800\t115766900\tLow Mappability\nchr11\t116389300\t116395200\tLow Mappability\nchr11\t116742700\t116792800\tLow Mappability\nchr11\t117499800\t117505100\tLow Mappability\nchr11\t119299800\t119340300\tLow Mappability\nchr11\t120305300\t120357300\tLow Mappability\nchr11\t120515100\t120644700\tHigh Signal Region\nchr11\t121069800\t121075100\tHigh Signal Region\nchr11\t121203000\t121207500\tLow Mappability\nchr11\t121396100\t121422700\tLow Mappability\nchr11\t121611900\t121614000\tLow Mappability\nchr11\t121981400\t122082500\tHigh Signal Region\nchr12\t0\t3070900\tHigh Signal Region\nchr12\t3102800\t3111000\tHigh Signal Region\nchr12\t4110500\t4112400\tHigh Signal Region\nchr12\t4218500\t4235300\tHigh Signal Region\nchr12\t4751600\t4790100\tHigh Signal Region\nchr12\t5050300\t5065400\tHigh Signal Region\nchr12\t6514000\t6525100\tHigh Signal Region\nchr12\t6606500\t6612600\tHigh Signal Region\nchr12\t7447300\t7449900\tHigh Signal Region\nchr12\t7801900\t7808600\tHigh Signal Region\nchr12\t7925300\t7939600\tHigh Signal Region\nchr12\t8572000\t8640600\tHigh Signal Region\nchr12\t10693000\t10704200\tHigh Signal Region\nchr12\t10961300\t11004600\tHigh Signal Region\nchr12\t11187600\t11194100\tHigh Signal Region\nchr12\t11642900\t11658000\tHigh Signal Region\nchr12\t12092500\t12097600\tHigh Signal Region\nchr12\t14844600\t14848200\tHigh Signal Region\nchr12\t15026600\t15032400\tHigh Signal Region\nchr12\t15252700\t15259600\tHigh Signal Region\nchr12\t15866100\t15871800\tHigh Signal Region\nchr12\t16746900\t16748800\tHigh Signal Region\nchr12\t17116400\t17129400\tHigh Signal Region\nchr12\t17243500\t17248500\tHigh Signal Region\nchr12\t18340700\t18354800\tHigh Signal Region\nchr12\t18856500\t18909700\tHigh Signal Region\nchr12\t19312600\t19413500\tHigh Signal Region\nchr12\t19442600\t19590100\tHigh Signal Region\nchr12\t19627700\t19633600\tHigh Signal Region\nchr12\t19777500\t19781600\tHigh Signal Region\nchr12\t19879300\t19901200\tHigh Signal Region\nchr12\t19931800\t19948600\tHigh Signal Region\nchr12\t20031900\t20205100\tHigh Signal Region\nchr12\t20225600\t20298300\tHigh Signal Region\nchr12\t21914300\t21916000\tLow Mappability\nchr12\t21972100\t21987900\tHigh Signal Region\nchr12\t22021600\t22680500\tLow Mappability\nchr12\t22896100\t22902300\tHigh Signal Region\nchr12\t23140700\t23225200\tHigh Signal Region\nchr12\t23283500\t24030600\tHigh Signal Region\nchr12\t24295300\t24365100\tLow Mappability\nchr12\t24692300\t24727100\tHigh Signal Region\nchr12\t25591800\t25595300\tLow Mappability\nchr12\t25840400\t25842100\tHigh Signal Region\nchr12\t27556800\t27592000\tHigh Signal Region\nchr12\t28491400\t28494000\tHigh Signal Region\nchr12\t28954800\t28964000\tHigh Signal Region\nchr12\t29379500\t29400800\tHigh Signal Region\nchr12\t30965100\t31016300\tHigh Signal Region\nchr12\t32020400\t32032500\tLow Mappability\nchr12\t32217700\t32219200\tHigh Signal Region\nchr12\t33388100\t33410100\tLow Mappability\nchr12\t33748900\t33771800\tHigh Signal Region\nchr12\t33869500\t33880600\tHigh Signal Region\nchr12\t34056800\t34074100\tHigh Signal Region\nchr12\t34128700\t34139700\tHigh Signal Region\nchr12\t34623000\t34629000\tLow Mappability\nchr12\t35783900\t35814400\tHigh Signal Region\nchr12\t36099400\t36107200\tHigh Signal Region\nchr12\t36679100\t36700200\tLow Mappability\nchr12\t36952200\t36957900\tHigh Signal Region\nchr12\t38746900\t38749300\tHigh Signal Region\nchr12\t41363500\t41385500\tHigh Signal Region\nchr12\t41502600\t41516100\tHigh Signal Region\nchr12\t41860000\t41870200\tHigh Signal Region\nchr12\t42124500\t42126300\tHigh Signal Region\nchr12\t42437900\t42443400\tHigh Signal Region\nchr12\t42666800\t42690800\tHigh Signal Region\nchr12\t43335600\t43349300\tHigh Signal Region\nchr12\t43659100\t43675300\tHigh Signal Region\nchr12\t43953900\t43986900\tHigh Signal Region\nchr12\t44064500\t44070600\tHigh Signal Region\nchr12\t44765600\t44795900\tLow Mappability\nchr12\t45768700\t45773700\tHigh Signal Region\nchr12\t45949200\t45962200\tHigh Signal Region\nchr12\t46707000\t46709200\tHigh Signal Region\nchr12\t47027300\t47039300\tHigh Signal Region\nchr12\t47280500\t47286800\tHigh Signal Region\nchr12\t47328600\t47331300\tHigh Signal Region\nchr12\t47646800\t47648300\tHigh Signal Region\nchr12\t47833000\t47834900\tHigh Signal Region\nchr12\t47995600\t47997600\tHigh Signal Region\nchr12\t48842900\t48849500\tHigh Signal Region\nchr12\t49124800\t49155700\tHigh Signal Region\nchr12\t49245200\t49272100\tHigh Signal Region\nchr12\t49606200\t49612000\tHigh Signal Region\nchr12\t50784600\t50789900\tHigh Signal Region\nchr12\t51486000\t51492000\tHigh Signal Region\nchr12\t52157900\t52176400\tHigh Signal Region\nchr12\t52200400\t52223200\tHigh Signal Region\nchr12\t52579600\t52581200\tHigh Signal Region\nchr12\t52730000\t52735400\tLow Mappability\nchr12\t52906200\t52952300\tHigh Signal Region\nchr12\t54358500\t54369200\tHigh Signal Region\nchr12\t54705400\t54743600\tHigh Signal Region\nchr12\t55079600\t55267300\tLow Mappability\nchr12\t56104100\t56110600\tLow Mappability\nchr12\t56423700\t56425000\tHigh Signal Region\nchr12\t56747800\t56752200\tHigh Signal Region\nchr12\t56911000\t56914000\tHigh Signal Region\nchr12\t58294800\t58339800\tHigh Signal Region\nchr12\t58659000\t58692900\tHigh Signal Region\nchr12\t58858800\t58867600\tHigh Signal Region\nchr12\t59034800\t59039300\tLow Mappability\nchr12\t59112800\t59124700\tHigh Signal Region\nchr12\t59270000\t59276700\tHigh Signal Region\nchr12\t59297800\t59323200\tHigh Signal Region\nchr12\t59601000\t59605800\tHigh Signal Region\nchr12\t60069500\t60084400\tHigh Signal Region\nchr12\t60501200\t60506200\tHigh Signal Region\nchr12\t61044200\t61045300\tHigh Signal Region\nchr12\t61289100\t61293700\tHigh Signal Region\nchr12\t61892600\t61896100\tHigh Signal Region\nchr12\t61964500\t61971300\tHigh Signal Region\nchr12\t62035300\t62090200\tHigh Signal Region\nchr12\t62959800\t62999500\tHigh Signal Region\nchr12\t63041800\t63048200\tHigh Signal Region\nchr12\t63289500\t63322400\tHigh Signal Region\nchr12\t63728400\t63745100\tHigh Signal Region\nchr12\t63838200\t63840100\tHigh Signal Region\nchr12\t65260100\t65292400\tHigh Signal Region\nchr12\t65784500\t65808300\tHigh Signal Region\nchr12\t66103800\t66127200\tHigh Signal Region\nchr12\t67058200\t67060800\tHigh Signal Region\nchr12\t67433500\t67459300\tHigh Signal Region\nchr12\t67519200\t67571500\tHigh Signal Region\nchr12\t67828900\t67836600\tHigh Signal Region\nchr12\t68696500\t68711800\tHigh Signal Region\nchr12\t68745100\t68750600\tLow Mappability\nchr12\t69059900\t69061300\tHigh Signal Region\nchr12\t69653100\t69657800\tHigh Signal Region\nchr12\t70641800\t70668400\tLow Mappability\nchr12\t71077100\t71093600\tLow Mappability\nchr12\t71589600\t71596000\tHigh Signal Region\nchr12\t72203000\t72209300\tHigh Signal Region\nchr12\t72634700\t72641300\tHigh Signal Region\nchr12\t74620800\t74642100\tHigh Signal Region\nchr12\t74775800\t74778200\tHigh Signal Region\nchr12\t74803000\t74805400\tHigh Signal Region\nchr12\t74857200\t74862700\tHigh Signal Region\nchr12\t75241800\t75248400\tHigh Signal Region\nchr12\t77160700\t77166000\tHigh Signal Region\nchr12\t77383500\t77411300\tHigh Signal Region\nchr12\t77547200\t77553900\tHigh Signal Region\nchr12\t78260000\t78373200\tHigh Signal Region\nchr12\t78462400\t78468500\tHigh Signal Region\nchr12\t80417200\t80449700\tHigh Signal Region\nchr12\t80894500\t80916600\tHigh Signal Region\nchr12\t81550400\t81555100\tHigh Signal Region\nchr12\t81985400\t82064000\tLow Mappability\nchr12\t83093000\t83094900\tHigh Signal Region\nchr12\t85401000\t85408600\tHigh Signal Region\nchr12\t87585600\t87771500\tLow Mappability\nchr12\t87802800\t88006400\tHigh Signal Region\nchr12\t88119800\t88169700\tLow Mappability\nchr12\t88229600\t88312400\tHigh Signal Region\nchr12\t88493200\t88516700\tLow Mappability\nchr12\t91221400\t91256000\tHigh Signal Region\nchr12\t91439200\t91475500\tHigh Signal Region\nchr12\t92393800\t92395800\tLow Mappability\nchr12\t92839700\t92892700\tHigh Signal Region\nchr12\t93233800\t93265600\tHigh Signal Region\nchr12\t93564200\t93590500\tHigh Signal Region\nchr12\t93915400\t93951600\tHigh Signal Region\nchr12\t94268500\t94273900\tHigh Signal Region\nchr12\t94550200\t94556100\tHigh Signal Region\nchr12\t94694300\t94713700\tHigh Signal Region\nchr12\t95976100\t96021400\tHigh Signal Region\nchr12\t97038100\t97062700\tHigh Signal Region\nchr12\t97616600\t97622400\tHigh Signal Region\nchr12\t98173700\t98176600\tHigh Signal Region\nchr12\t99644200\t99649400\tHigh Signal Region\nchr12\t100490600\t100492300\tHigh Signal Region\nchr12\t100766900\t100825300\tHigh Signal Region\nchr12\t101427900\t101453500\tHigh Signal Region\nchr12\t101839700\t101849500\tHigh Signal Region\nchr12\t102892000\t102893900\tHigh Signal Region\nchr12\t103458100\t103472900\tHigh Signal Region\nchr12\t103776900\t103813700\tHigh Signal Region\nchr12\t105300300\t105307000\tHigh Signal Region\nchr12\t105435200\t105437100\tHigh Signal Region\nchr12\t105523800\t105525700\tHigh Signal Region\nchr12\t105628200\t105631400\tHigh Signal Region\nchr12\t108078800\t108084400\tHigh Signal Region\nchr12\t109901900\t109909200\tLow Mappability\nchr12\t110011800\t110013700\tHigh Signal Region\nchr12\t111388200\t111417100\tHigh Signal Region\nchr12\t112542200\t112548700\tHigh Signal Region\nchr12\t112775700\t112830900\tLow Mappability\nchr12\t113423500\t113461500\tHigh Signal Region\nchr12\t114584600\t114597100\tHigh Signal Region\nchr12\t114941500\t114943900\tHigh Signal Region\nchr12\t115725800\t115748700\tHigh Signal Region\nchr12\t116796500\t116853000\tHigh Signal Region\nchr12\t118341100\t118358400\tHigh Signal Region\nchr12\t118794900\t118797400\tHigh Signal Region\nchr12\t119013600\t119018100\tHigh Signal Region\nchr12\t119554500\t119598100\tHigh Signal Region\nchr12\t119659100\t119670900\tHigh Signal Region\nchr12\t120023800\t120129000\tHigh Signal Region\nchr13\t0\t3038200\tHigh Signal Region\nchr13\t3350900\t3378900\tHigh Signal Region\nchr13\t3404500\t3438200\tHigh Signal Region\nchr13\t3901100\t3903100\tLow Mappability\nchr13\t4762900\t4770300\tHigh Signal Region\nchr13\t5171400\t5178400\tHigh Signal Region\nchr13\t7601300\t7604100\tHigh Signal Region\nchr13\t7806100\t7810900\tHigh Signal Region\nchr13\t7893500\t7899700\tHigh Signal Region\nchr13\t9828900\t9855900\tHigh Signal Region\nchr13\t10174800\t10181100\tLow Mappability\nchr13\t12684400\t13073000\tHigh Signal Region\nchr13\t13752100\t13774000\tHigh Signal Region\nchr13\t13859900\t13907900\tHigh Signal Region\nchr13\t13981000\t13983000\tHigh Signal Region\nchr13\t14690600\t14777500\tLow Mappability\nchr13\t18932700\t18963600\tLow Mappability\nchr13\t21753300\t21847200\tLow Mappability\nchr13\t23620800\t23647900\tLow Mappability\nchr13\t25006900\t25051500\tHigh Signal Region\nchr13\t26440600\t26448200\tHigh Signal Region\nchr13\t27164600\t27169100\tHigh Signal Region\nchr13\t27875800\t27888500\tHigh Signal Region\nchr13\t29880700\t29886800\tLow Mappability\nchr13\t32889400\t32895200\tHigh Signal Region\nchr13\t33280200\t33319400\tHigh Signal Region\nchr13\t33350500\t33491800\tHigh Signal Region\nchr13\t35687400\t35695700\tHigh Signal Region\nchr13\t36794200\t36797400\tHigh Signal Region\nchr13\t37036700\t37043900\tHigh Signal Region\nchr13\t38633900\t38659300\tLow Mappability\nchr13\t42435800\t42437700\tHigh Signal Region\nchr13\t44868600\t44870900\tHigh Signal Region\nchr13\t46316600\t46324000\tHigh Signal Region\nchr13\t50633400\t50741800\tHigh Signal Region\nchr13\t53269000\t53270900\tHigh Signal Region\nchr13\t60675600\t60682600\tHigh Signal Region\nchr13\t62291600\t62346800\tLow Mappability\nchr13\t62409800\t62426300\tHigh Signal Region\nchr13\t63142500\t63184600\tHigh Signal Region\nchr13\t64878100\t64885300\tHigh Signal Region\nchr13\t65352900\t66254300\tLow Mappability\nchr13\t71381400\t71387500\tHigh Signal Region\nchr13\t74521500\t74565200\tHigh Signal Region\nchr13\t74684000\t74712200\tHigh Signal Region\nchr13\t76472300\t76501300\tHigh Signal Region\nchr13\t77304000\t77305900\tHigh Signal Region\nchr13\t77430600\t77440000\tHigh Signal Region\nchr13\t79563400\t79570800\tHigh Signal Region\nchr13\t80276300\t80279400\tHigh Signal Region\nchr13\t80489100\t80491400\tHigh Signal Region\nchr13\t83419000\t83444300\tHigh Signal Region\nchr13\t85125800\t85145900\tHigh Signal Region\nchr13\t86149500\t86190600\tHigh Signal Region\nchr13\t86502700\t86511700\tHigh Signal Region\nchr13\t88324900\t88345400\tHigh Signal Region\nchr13\t92599100\t92625400\tLow Mappability\nchr13\t93279200\t93294800\tHigh Signal Region\nchr13\t93650100\t93651500\tHigh Signal Region\nchr13\t93940300\t93955300\tHigh Signal Region\nchr13\t94016300\t94020800\tHigh Signal Region\nchr13\t97189600\t97206100\tHigh Signal Region\nchr13\t98418200\t98420500\tLow Mappability\nchr13\t99774000\t99792100\tHigh Signal Region\nchr13\t102381900\t102387900\tHigh Signal Region\nchr13\t105123500\t105128600\tLow Mappability\nchr13\t107839000\t107860300\tLow Mappability\nchr13\t110602100\t110615800\tHigh Signal Region\nchr13\t110729600\t110745400\tHigh Signal Region\nchr13\t111187700\t111189500\tHigh Signal Region\nchr13\t111499700\t111515900\tLow Mappability\nchr13\t112577200\t112595200\tHigh Signal Region\nchr13\t113171200\t113173100\tHigh Signal Region\nchr13\t113272600\t113310700\tHigh Signal Region\nchr13\t115498200\t115504200\tHigh Signal Region\nchr13\t115741300\t115743200\tLow Mappability\nchr13\t116191900\t116193900\tHigh Signal Region\nchr13\t119188100\t119230700\tHigh Signal Region\nchr13\t119486800\t119618500\tHigh Signal Region\nchr13\t119660800\t119674100\tHigh Signal Region\nchr13\t119899200\t120147600\tLow Mappability\nchr13\t120320500\t120421600\tHigh Signal Region\nchr14\t0\t4323000\tHigh Signal Region\nchr14\t4372100\t4741400\tHigh Signal Region\nchr14\t4762800\t5839200\tHigh Signal Region\nchr14\t5959700\t6479300\tHigh Signal Region\nchr14\t6500100\t6791800\tHigh Signal Region\nchr14\t6993800\t7734200\tHigh Signal Region\nchr14\t7869900\t7872200\tHigh Signal Region\nchr14\t8005200\t8018900\tHigh Signal Region\nchr14\t8285700\t8287800\tHigh Signal Region\nchr14\t8652200\t8658800\tLow Mappability\nchr14\t10086500\t10118400\tHigh Signal Region\nchr14\t10178800\t10198700\tLow Mappability\nchr14\t11046200\t11050200\tHigh Signal Region\nchr14\t12536700\t12538700\tHigh Signal Region\nchr14\t14333600\t14340200\tHigh Signal Region\nchr14\t15460700\t15467200\tHigh Signal Region\nchr14\t16907800\t16914000\tHigh Signal Region\nchr14\t16937900\t16941100\tHigh Signal Region\nchr14\t18487900\t18494100\tHigh Signal Region\nchr14\t19251900\t19255700\tHigh Signal Region\nchr14\t19277200\t19279100\tHigh Signal Region\nchr14\t19414800\t19633500\tHigh Signal Region\nchr14\t21360400\t21366100\tHigh Signal Region\nchr14\t21878600\t21884500\tHigh Signal Region\nchr14\t22542900\t22570000\tHigh Signal Region\nchr14\t22902100\t22934800\tHigh Signal Region\nchr14\t25875200\t26292200\tHigh Signal Region\nchr14\t26946900\t26948800\tHigh Signal Region\nchr14\t29001300\t29003200\tLow Mappability\nchr14\t29343900\t29345700\tLow Mappability\nchr14\t30748800\t30754700\tHigh Signal Region\nchr14\t31919300\t31923900\tHigh Signal Region\nchr14\t32115300\t32120500\tLow Mappability\nchr14\t33667700\t33670000\tLow Mappability\nchr14\t33981000\t33987500\tLow Mappability\nchr14\t35275300\t35281500\tHigh Signal Region\nchr14\t35709400\t35722200\tHigh Signal Region\nchr14\t36429100\t36440100\tHigh Signal Region\nchr14\t37229100\t37260800\tLow Mappability\nchr14\t37619400\t37635200\tLow Mappability\nchr14\t38086800\t38116800\tHigh Signal Region\nchr14\t38280800\t38283100\tHigh Signal Region\nchr14\t38455100\t38462200\tLow Mappability\nchr14\t39580800\t39607200\tHigh Signal Region\nchr14\t39731900\t39737200\tHigh Signal Region\nchr14\t39905500\t39911100\tHigh Signal Region\nchr14\t41053200\t41061900\tLow Mappability\nchr14\t41326900\t43109000\tHigh Signal Region\nchr14\t43132400\t43668900\tHigh Signal Region\nchr14\t43803900\t43850200\tHigh Signal Region\nchr14\t44149300\t44152100\tHigh Signal Region\nchr14\t44273800\t44343500\tHigh Signal Region\nchr14\t44514200\t44516000\tLow Mappability\nchr14\t45726200\t45753500\tHigh Signal Region\nchr14\t45811900\t45813800\tHigh Signal Region\nchr14\t46269900\t46274300\tHigh Signal Region\nchr14\t47609500\t47630400\tHigh Signal Region\nchr14\t50538900\t50606000\tHigh Signal Region\nchr14\t50626200\t50638500\tHigh Signal Region\nchr14\t51472000\t51515400\tHigh Signal Region\nchr14\t51730700\t51768100\tHigh Signal Region\nchr14\t51814200\t51837200\tHigh Signal Region\nchr14\t52821200\t53035800\tLow Mappability\nchr14\t53146700\t53340000\tHigh Signal Region\nchr14\t53475200\t53479600\tHigh Signal Region\nchr14\t53515600\t53530500\tLow Mappability\nchr14\t56447800\t56455700\tHigh Signal Region\nchr14\t56693100\t56695000\tHigh Signal Region\nchr14\t58052600\t58059800\tLow Mappability\nchr14\t58462700\t58464600\tLow Mappability\nchr14\t58657800\t58659700\tHigh Signal Region\nchr14\t58831400\t58833300\tHigh Signal Region\nchr14\t59250300\t59270000\tHigh Signal Region\nchr14\t59488900\t59490800\tHigh Signal Region\nchr14\t59980800\t59995700\tHigh Signal Region\nchr14\t60328300\t60357300\tHigh Signal Region\nchr14\t60960000\t60961900\tLow Mappability\nchr14\t61580500\t61586700\tHigh Signal Region\nchr14\t61855000\t61856300\tHigh Signal Region\nchr14\t62107300\t62126200\tHigh Signal Region\nchr14\t64290100\t64292500\tHigh Signal Region\nchr14\t64463300\t64478500\tLow Mappability\nchr14\t65128900\t65135300\tLow Mappability\nchr14\t66427000\t66428400\tHigh Signal Region\nchr14\t68232600\t68278200\tHigh Signal Region\nchr14\t69161000\t69163400\tHigh Signal Region\nchr14\t70974500\t70975600\tHigh Signal Region\nchr14\t71121300\t71126700\tHigh Signal Region\nchr14\t71449700\t71453700\tHigh Signal Region\nchr14\t71783600\t71804000\tHigh Signal Region\nchr14\t72900100\t72921400\tHigh Signal Region\nchr14\t73644600\t73679900\tHigh Signal Region\nchr14\t73847900\t73861200\tHigh Signal Region\nchr14\t74039300\t74066900\tHigh Signal Region\nchr14\t74124400\t74138500\tHigh Signal Region\nchr14\t74435600\t74447800\tHigh Signal Region\nchr14\t75425300\t75440500\tHigh Signal Region\nchr14\t78162300\t78168200\tHigh Signal Region\nchr14\t78401700\t78403200\tHigh Signal Region\nchr14\t79145300\t79196400\tHigh Signal Region\nchr14\t80148100\t80150800\tHigh Signal Region\nchr14\t80422800\t80439400\tHigh Signal Region\nchr14\t80622600\t80627700\tHigh Signal Region\nchr14\t81333200\t81337500\tHigh Signal Region\nchr14\t81495300\t81519300\tHigh Signal Region\nchr14\t82077600\t82084900\tHigh Signal Region\nchr14\t82846900\t82867200\tHigh Signal Region\nchr14\t82958700\t82964100\tHigh Signal Region\nchr14\t83292900\t83306500\tHigh Signal Region\nchr14\t83507000\t83512600\tHigh Signal Region\nchr14\t84354700\t84409800\tHigh Signal Region\nchr14\t84855100\t84881600\tLow Mappability\nchr14\t85177800\t85203300\tLow Mappability\nchr14\t85521200\t85535200\tLow Mappability\nchr14\t86198000\t86200000\tHigh Signal Region\nchr14\t86590500\t86614400\tHigh Signal Region\nchr14\t87354600\t87373000\tHigh Signal Region\nchr14\t87671400\t87677500\tHigh Signal Region\nchr14\t87790500\t87852200\tHigh Signal Region\nchr14\t88450200\t88453600\tHigh Signal Region\nchr14\t88478400\t88480300\tHigh Signal Region\nchr14\t90018300\t90019500\tHigh Signal Region\nchr14\t90294700\t90301800\tHigh Signal Region\nchr14\t90910200\t90912200\tHigh Signal Region\nchr14\t91415900\t91418400\tHigh Signal Region\nchr14\t91510800\t91514900\tHigh Signal Region\nchr14\t91672700\t91694800\tHigh Signal Region\nchr14\t91951700\t91976400\tHigh Signal Region\nchr14\t92032500\t92040900\tHigh Signal Region\nchr14\t92383600\t92389900\tHigh Signal Region\nchr14\t92411600\t92432900\tHigh Signal Region\nchr14\t92792600\t92798500\tHigh Signal Region\nchr14\t92921100\t92953200\tHigh Signal Region\nchr14\t93017600\t93020400\tHigh Signal Region\nchr14\t93355600\t93360200\tHigh Signal Region\nchr14\t94319700\t94327000\tHigh Signal Region\nchr14\t95561600\t95567600\tHigh Signal Region\nchr14\t96048000\t96054300\tHigh Signal Region\nchr14\t96093600\t96116100\tHigh Signal Region\nchr14\t97323800\t97326500\tHigh Signal Region\nchr14\t98226800\t98237000\tHigh Signal Region\nchr14\t98731900\t98757200\tHigh Signal Region\nchr14\t99207100\t99208200\tHigh Signal Region\nchr14\t99649700\t99655500\tHigh Signal Region\nchr14\t101076400\t101098900\tLow Mappability\nchr14\t101404800\t101414800\tHigh Signal Region\nchr14\t102548900\t102565300\tHigh Signal Region\nchr14\t102755800\t102762600\tHigh Signal Region\nchr14\t103300300\t103302400\tHigh Signal Region\nchr14\t103858600\t103872900\tHigh Signal Region\nchr14\t103999500\t104025500\tHigh Signal Region\nchr14\t104104800\t104128100\tLow Mappability\nchr14\t104704500\t104716800\tHigh Signal Region\nchr14\t105758200\t105764900\tLow Mappability\nchr14\t105911400\t105978300\tHigh Signal Region\nchr14\t106002700\t106005700\tLow Mappability\nchr14\t106301000\t106352700\tHigh Signal Region\nchr14\t106444800\t106483100\tLow Mappability\nchr14\t106722600\t106728700\tHigh Signal Region\nchr14\t106895300\t106897000\tLow Mappability\nchr14\t108115100\t108174900\tLow Mappability\nchr14\t108283900\t108303500\tHigh Signal Region\nchr14\t109675300\t109681200\tHigh Signal Region\nchr14\t109911500\t109917800\tHigh Signal Region\nchr14\t110057000\t110108200\tLow Mappability\nchr14\t110356200\t110373800\tHigh Signal Region\nchr14\t110492000\t110495700\tLow Mappability\nchr14\t110906100\t110908200\tHigh Signal Region\nchr14\t110992800\t110994500\tHigh Signal Region\nchr14\t111903200\t111909800\tHigh Signal Region\nchr14\t112074600\t112092300\tHigh Signal Region\nchr14\t112210500\t112215800\tHigh Signal Region\nchr14\t112285400\t112291900\tHigh Signal Region\nchr14\t112332800\t112340000\tLow Mappability\nchr14\t112517900\t112519900\tHigh Signal Region\nchr14\t112627800\t112663100\tLow Mappability\nchr14\t114505900\t114512900\tHigh Signal Region\nchr14\t114822000\t114823900\tLow Mappability\nchr14\t115109700\t115117400\tHigh Signal Region\nchr14\t115272500\t115280200\tHigh Signal Region\nchr14\t115379200\t115385600\tHigh Signal Region\nchr14\t115911100\t115912900\tHigh Signal Region\nchr14\t115958100\t115965000\tHigh Signal Region\nchr14\t116402700\t116407700\tHigh Signal Region\nchr14\t116817000\t116822900\tHigh Signal Region\nchr14\t117285800\t117292800\tHigh Signal Region\nchr14\t118144700\t118168500\tLow Mappability\nchr14\t119286000\t119287900\tHigh Signal Region\nchr14\t120180000\t120202600\tHigh Signal Region\nchr14\t120742600\t120749700\tHigh Signal Region\nchr14\t120777500\t120802300\tHigh Signal Region\nchr14\t121007000\t121010900\tLow Mappability\nchr14\t122502500\t122534800\tHigh Signal Region\nchr14\t123349400\t123351300\tLow Mappability\nchr14\t123412000\t123452600\tHigh Signal Region\nchr14\t123674600\t123695600\tHigh Signal Region\nchr14\t124334000\t124340200\tHigh Signal Region\nchr14\t124415600\t124436400\tHigh Signal Region\nchr14\t124491600\t124497700\tHigh Signal Region\nchr14\t124739500\t124902200\tHigh Signal Region\nchr15\t0\t3125600\tHigh Signal Region\nchr15\t3150900\t3170400\tHigh Signal Region\nchr15\t3313900\t3336200\tHigh Signal Region\nchr15\t3360500\t3363700\tHigh Signal Region\nchr15\t3538600\t3551000\tHigh Signal Region\nchr15\t3712200\t3732700\tHigh Signal Region\nchr15\t3793500\t3823000\tHigh Signal Region\nchr15\t4155900\t4160900\tHigh Signal Region\nchr15\t4278500\t4284100\tHigh Signal Region\nchr15\t4852000\t4894600\tLow Mappability\nchr15\t4980200\t4987600\tLow Mappability\nchr15\t5369000\t5385500\tHigh Signal Region\nchr15\t5681700\t5690400\tHigh Signal Region\nchr15\t5910000\t5911700\tHigh Signal Region\nchr15\t5993500\t5995400\tHigh Signal Region\nchr15\t6074100\t6087100\tLow Mappability\nchr15\t6192800\t6200000\tLow Mappability\nchr15\t6316000\t6317900\tHigh Signal Region\nchr15\t6510500\t6539100\tHigh Signal Region\nchr15\t6674800\t6701400\tHigh Signal Region\nchr15\t6801200\t6808300\tHigh Signal Region\nchr15\t7539900\t7548600\tLow Mappability\nchr15\t7800800\t7803000\tLow Mappability\nchr15\t7849400\t7855600\tHigh Signal Region\nchr15\t7904400\t7929500\tLow Mappability\nchr15\t8517500\t8520400\tHigh Signal Region\nchr15\t8548000\t8576100\tLow Mappability\nchr15\t8800200\t8808700\tHigh Signal Region\nchr15\t8985200\t9054800\tHigh Signal Region\nchr15\t9219000\t9224900\tLow Mappability\nchr15\t9293200\t9333300\tHigh Signal Region\nchr15\t9379300\t9409100\tHigh Signal Region\nchr15\t9437100\t9443600\tHigh Signal Region\nchr15\t9536500\t9554100\tHigh Signal Region\nchr15\t9992700\t10045700\tHigh Signal Region\nchr15\t10579600\t10591500\tLow Mappability\nchr15\t10753400\t10810200\tHigh Signal Region\nchr15\t10835200\t10854700\tLow Mappability\nchr15\t11921000\t11933300\tHigh Signal Region\nchr15\t12055800\t12063200\tLow Mappability\nchr15\t12526800\t12531900\tLow Mappability\nchr15\t12872000\t12873900\tHigh Signal Region\nchr15\t12932300\t12934200\tLow Mappability\nchr15\t13919500\t13948300\tHigh Signal Region\nchr15\t14414600\t14439100\tLow Mappability\nchr15\t14722200\t14732900\tHigh Signal Region\nchr15\t14873900\t14902400\tHigh Signal Region\nchr15\t15043600\t15059700\tHigh Signal Region\nchr15\t15525500\t15551900\tHigh Signal Region\nchr15\t16168200\t16186400\tHigh Signal Region\nchr15\t16303700\t16309500\tHigh Signal Region\nchr15\t16716400\t16717500\tHigh Signal Region\nchr15\t16901300\t16907100\tHigh Signal Region\nchr15\t16939800\t16955100\tLow Mappability\nchr15\t17139000\t17169100\tHigh Signal Region\nchr15\t17562100\t17581400\tHigh Signal Region\nchr15\t18314600\t18325000\tHigh Signal Region\nchr15\t19038400\t19063800\tLow Mappability\nchr15\t19402600\t19405500\tHigh Signal Region\nchr15\t19448100\t19453900\tHigh Signal Region\nchr15\t19557200\t19578000\tHigh Signal Region\nchr15\t19626800\t19631800\tHigh Signal Region\nchr15\t19678400\t19685800\tHigh Signal Region\nchr15\t20063000\t20067500\tHigh Signal Region\nchr15\t20155100\t20170700\tLow Mappability\nchr15\t20474900\t20510100\tHigh Signal Region\nchr15\t20531400\t20537100\tHigh Signal Region\nchr15\t20821500\t20826700\tHigh Signal Region\nchr15\t20972700\t20978300\tLow Mappability\nchr15\t21114000\t21115900\tHigh Signal Region\nchr15\t21262100\t21268500\tLow Mappability\nchr15\t21423200\t21487200\tHigh Signal Region\nchr15\t21655500\t21657500\tHigh Signal Region\nchr15\t21815500\t21820800\tHigh Signal Region\nchr15\t21853700\t21892400\tHigh Signal Region\nchr15\t22268700\t22293500\tHigh Signal Region\nchr15\t22751400\t22756700\tLow Mappability\nchr15\t22799300\t22809700\tLow Mappability\nchr15\t23240200\t23255600\tLow Mappability\nchr15\t23465300\t23467800\tHigh Signal Region\nchr15\t23886000\t23887900\tLow Mappability\nchr15\t23926900\t23939700\tHigh Signal Region\nchr15\t24309300\t24325700\tLow Mappability\nchr15\t24761100\t24766700\tHigh Signal Region\nchr15\t24801600\t24837300\tHigh Signal Region\nchr15\t24880900\t24898600\tLow Mappability\nchr15\t25051400\t25065200\tLow Mappability\nchr15\t26112700\t26118900\tHigh Signal Region\nchr15\t26905000\t26919300\tLow Mappability\nchr15\t27286100\t27326800\tHigh Signal Region\nchr15\t27384100\t27390300\tLow Mappability\nchr15\t27638200\t27640500\tHigh Signal Region\nchr15\t28564400\t28578800\tHigh Signal Region\nchr15\t29285200\t29291500\tLow Mappability\nchr15\t29347600\t29395600\tHigh Signal Region\nchr15\t29463900\t29470200\tHigh Signal Region\nchr15\t29969800\t30001400\tHigh Signal Region\nchr15\t30117700\t30126200\tHigh Signal Region\nchr15\t30441400\t30448200\tLow Mappability\nchr15\t30747900\t30755000\tHigh Signal Region\nchr15\t30996700\t31016300\tHigh Signal Region\nchr15\t31066700\t31083700\tHigh Signal Region\nchr15\t32783900\t32806700\tHigh Signal Region\nchr15\t32832800\t32880300\tHigh Signal Region\nchr15\t33138700\t33140800\tLow Mappability\nchr15\t33308700\t33310800\tLow Mappability\nchr15\t33444200\t33454100\tHigh Signal Region\nchr15\t33710200\t33745700\tHigh Signal Region\nchr15\t33781400\t33849400\tHigh Signal Region\nchr15\t33869800\t33884700\tHigh Signal Region\nchr15\t34494500\t34502100\tLow Mappability\nchr15\t34763100\t34769400\tHigh Signal Region\nchr15\t34987600\t34992800\tHigh Signal Region\nchr15\t35013200\t35015400\tHigh Signal Region\nchr15\t35366800\t35406000\tHigh Signal Region\nchr15\t36715200\t36737400\tHigh Signal Region\nchr15\t36966700\t36997400\tLow Mappability\nchr15\t37072900\t37150800\tLow Mappability\nchr15\t38462300\t38484300\tLow Mappability\nchr15\t39172900\t39178300\tLow Mappability\nchr15\t39335600\t39348800\tLow Mappability\nchr15\t39496100\t39499100\tHigh Signal Region\nchr15\t39695600\t39718600\tLow Mappability\nchr15\t40049600\t40056000\tHigh Signal Region\nchr15\t40086800\t40101400\tHigh Signal Region\nchr15\t41531400\t41533200\tHigh Signal Region\nchr15\t41890400\t41896900\tLow Mappability\nchr15\t42354900\t42361100\tHigh Signal Region\nchr15\t42925300\t42942800\tHigh Signal Region\nchr15\t43287300\t43346300\tHigh Signal Region\nchr15\t44469100\t44476400\tHigh Signal Region\nchr15\t44649000\t44659600\tLow Mappability\nchr15\t44723200\t44728200\tLow Mappability\nchr15\t44769700\t44796100\tHigh Signal Region\nchr15\t45005100\t45009300\tHigh Signal Region\nchr15\t45194600\t45197100\tHigh Signal Region\nchr15\t45577500\t45590900\tHigh Signal Region\nchr15\t45635600\t45650500\tHigh Signal Region\nchr15\t45774400\t45779700\tHigh Signal Region\nchr15\t45890700\t45932500\tHigh Signal Region\nchr15\t46255700\t46257800\tLow Mappability\nchr15\t46355600\t46368400\tHigh Signal Region\nchr15\t46502200\t46506800\tLow Mappability\nchr15\t46562500\t46566200\tLow Mappability\nchr15\t47232800\t47256000\tHigh Signal Region\nchr15\t47356500\t47363700\tLow Mappability\nchr15\t47539000\t47555300\tHigh Signal Region\nchr15\t48666900\t48671000\tHigh Signal Region\nchr15\t49283300\t49299700\tHigh Signal Region\nchr15\t49322600\t49327300\tLow Mappability\nchr15\t50426100\t50442800\tHigh Signal Region\nchr15\t50557700\t50642600\tHigh Signal Region\nchr15\t51113200\t51117800\tHigh Signal Region\nchr15\t51531900\t51533900\tLow Mappability\nchr15\t52125800\t52131200\tHigh Signal Region\nchr15\t52329800\t52353100\tHigh Signal Region\nchr15\t53039200\t53044200\tLow Mappability\nchr15\t53831000\t53834900\tHigh Signal Region\nchr15\t53870700\t53872700\tHigh Signal Region\nchr15\t53918300\t53929500\tHigh Signal Region\nchr15\t54180700\t54211500\tLow Mappability\nchr15\t56032900\t56038200\tHigh Signal Region\nchr15\t56175800\t56183100\tLow Mappability\nchr15\t56363800\t56367900\tHigh Signal Region\nchr15\t56400500\t56402200\tHigh Signal Region\nchr15\t56941600\t56993500\tHigh Signal Region\nchr15\t57279500\t57285000\tHigh Signal Region\nchr15\t57412200\t57433600\tHigh Signal Region\nchr15\t57889500\t57913700\tLow Mappability\nchr15\t58437200\t58441100\tHigh Signal Region\nchr15\t59421400\t59435400\tLow Mappability\nchr15\t59850100\t59875200\tLow Mappability\nchr15\t60153100\t60203900\tHigh Signal Region\nchr15\t60592000\t60594300\tLow Mappability\nchr15\t60931800\t60986500\tHigh Signal Region\nchr15\t61148600\t61150700\tHigh Signal Region\nchr15\t61903100\t61915500\tHigh Signal Region\nchr15\t62367600\t62370100\tHigh Signal Region\nchr15\t62553200\t62555200\tHigh Signal Region\nchr15\t62686500\t62693700\tHigh Signal Region\nchr15\t63329400\t63346600\tLow Mappability\nchr15\t63626000\t63627900\tHigh Signal Region\nchr15\t63791700\t63796000\tHigh Signal Region\nchr15\t63837600\t63922800\tHigh Signal Region\nchr15\t64591700\t64598200\tLow Mappability\nchr15\t64673500\t64681900\tHigh Signal Region\nchr15\t65115600\t65123500\tLow Mappability\nchr15\t65598500\t65604500\tHigh Signal Region\nchr15\t65666600\t65673800\tHigh Signal Region\nchr15\t65714400\t65753500\tHigh Signal Region\nchr15\t66045100\t66065700\tHigh Signal Region\nchr15\t66208300\t66210200\tHigh Signal Region\nchr15\t68136300\t68137800\tLow Mappability\nchr15\t68980000\t68986500\tHigh Signal Region\nchr15\t69122300\t69164500\tHigh Signal Region\nchr15\t69264900\t69268800\tHigh Signal Region\nchr15\t69390300\t69409400\tHigh Signal Region\nchr15\t69642000\t69646000\tHigh Signal Region\nchr15\t70083000\t70088800\tHigh Signal Region\nchr15\t70609300\t70611100\tHigh Signal Region\nchr15\t70896600\t70914000\tHigh Signal Region\nchr15\t71104600\t71112200\tHigh Signal Region\nchr15\t71206600\t71237500\tLow Mappability\nchr15\t73060200\t73087900\tLow Mappability\nchr15\t73373200\t73378200\tLow Mappability\nchr15\t73873000\t73880400\tLow Mappability\nchr15\t74360700\t74368000\tLow Mappability\nchr15\t74814300\t74826700\tLow Mappability\nchr15\t74992000\t75104600\tHigh Signal Region\nchr15\t75205600\t75212800\tLow Mappability\nchr15\t75298000\t75299500\tHigh Signal Region\nchr15\t75437000\t75440500\tHigh Signal Region\nchr15\t75523600\t75529700\tHigh Signal Region\nchr15\t76102000\t76106500\tHigh Signal Region\nchr15\t76559900\t76577900\tLow Mappability\nchr15\t76964600\t76971400\tLow Mappability\nchr15\t77336200\t77439100\tHigh Signal Region\nchr15\t77718300\t77735600\tLow Mappability\nchr15\t77895000\t77934800\tLow Mappability\nchr15\t79685000\t79775700\tLow Mappability\nchr15\t79869700\t79892600\tLow Mappability\nchr15\t79974400\t79978400\tLow Mappability\nchr15\t80232400\t80267100\tHigh Signal Region\nchr15\t81145400\t81152000\tLow Mappability\nchr15\t81492300\t81523600\tHigh Signal Region\nchr15\t82338000\t82368000\tLow Mappability\nchr15\t82590700\t82608900\tLow Mappability\nchr15\t82675500\t82677200\tHigh Signal Region\nchr15\t83172100\t83202200\tLow Mappability\nchr15\t84746600\t84753000\tLow Mappability\nchr15\t85176800\t85196600\tLow Mappability\nchr15\t85541200\t85543100\tHigh Signal Region\nchr15\t86193800\t86196100\tHigh Signal Region\nchr15\t86312100\t86326400\tLow Mappability\nchr15\t87293900\t87301200\tLow Mappability\nchr15\t87967000\t87969000\tHigh Signal Region\nchr15\t88779400\t88783900\tLow Mappability\nchr15\t88974800\t88976800\tHigh Signal Region\nchr15\t89597900\t89621300\tHigh Signal Region\nchr15\t89808500\t89809700\tHigh Signal Region\nchr15\t89943000\t89982000\tLow Mappability\nchr15\t90636400\t90643600\tLow Mappability\nchr15\t91115900\t91134800\tLow Mappability\nchr15\t91419400\t91422200\tHigh Signal Region\nchr15\t91720600\t91723200\tLow Mappability\nchr15\t91905900\t91911200\tHigh Signal Region\nchr15\t92470100\t92475100\tLow Mappability\nchr15\t92613700\t92618300\tLow Mappability\nchr15\t92722600\t92730100\tLow Mappability\nchr15\t92796100\t92820000\tLow Mappability\nchr15\t93044100\t93062000\tHigh Signal Region\nchr15\t93467800\t93469500\tLow Mappability\nchr15\t93867100\t93873600\tHigh Signal Region\nchr15\t94088400\t94124100\tHigh Signal Region\nchr15\t94150500\t94156800\tHigh Signal Region\nchr15\t94373000\t94379600\tHigh Signal Region\nchr15\t95087600\t95092100\tHigh Signal Region\nchr15\t95306000\t95312300\tHigh Signal Region\nchr15\t95729500\t95756400\tHigh Signal Region\nchr15\t96551700\t96559500\tLow Mappability\nchr15\t96977900\t96983600\tLow Mappability\nchr15\t97082100\t97084300\tHigh Signal Region\nchr15\t97472900\t97487400\tLow Mappability\nchr15\t99168800\t99171900\tHigh Signal Region\nchr15\t99552100\t99553900\tLow Mappability\nchr15\t100331500\t100339800\tLow Mappability\nchr15\t100360000\t100379700\tLow Mappability\nchr15\t100541700\t100617400\tLow Mappability\nchr15\t101655700\t101662100\tHigh Signal Region\nchr15\t102596800\t102603200\tHigh Signal Region\nchr15\t103271900\t103277100\tHigh Signal Region\nchr15\t103406700\t103418500\tHigh Signal Region\nchr15\t103606700\t103611400\tHigh Signal Region\nchr15\t103814500\t104043600\tHigh Signal Region\nchr16\t0\t3427800\tHigh Signal Region\nchr16\t3450300\t3519700\tLow Mappability\nchr16\t4300400\t4366800\tLow Mappability\nchr16\t4585000\t4591300\tHigh Signal Region\nchr16\t5708200\t5710200\tHigh Signal Region\nchr16\t7460800\t7463600\tHigh Signal Region\nchr16\t7937100\t7958400\tLow Mappability\nchr16\t8256700\t8286200\tHigh Signal Region\nchr16\t9577100\t9579600\tLow Mappability\nchr16\t10631200\t10633200\tLow Mappability\nchr16\t10974100\t11013900\tHigh Signal Region\nchr16\t11134600\t11145200\tHigh Signal Region\nchr16\t11248000\t11249900\tLow Mappability\nchr16\t11679900\t11687500\tLow Mappability\nchr16\t12327300\t12345900\tLow Mappability\nchr16\t12417900\t12423400\tHigh Signal Region\nchr16\t12829200\t12831000\tHigh Signal Region\nchr16\t12976200\t12981700\tLow Mappability\nchr16\t13087700\t13107000\tLow Mappability\nchr16\t13903200\t13925900\tLow Mappability\nchr16\t14316200\t14341200\tLow Mappability\nchr16\t15502700\t15510100\tLow Mappability\nchr16\t15741400\t15757700\tLow Mappability\nchr16\t17199900\t17236000\tHigh Signal Region\nchr16\t17751400\t17761300\tHigh Signal Region\nchr16\t17910400\t17955500\tHigh Signal Region\nchr16\t18532200\t18534200\tHigh Signal Region\nchr16\t18957500\t18979200\tHigh Signal Region\nchr16\t19334200\t19375100\tHigh Signal Region\nchr16\t19581200\t19602400\tLow Mappability\nchr16\t19711900\t19748700\tHigh Signal Region\nchr16\t19928600\t19946300\tLow Mappability\nchr16\t22923300\t22929100\tHigh Signal Region\nchr16\t26419300\t26421200\tHigh Signal Region\nchr16\t26808500\t26814800\tHigh Signal Region\nchr16\t27071900\t27087600\tHigh Signal Region\nchr16\t27212200\t27218300\tHigh Signal Region\nchr16\t28170600\t28197500\tHigh Signal Region\nchr16\t30828600\t30830500\tHigh Signal Region\nchr16\t31223800\t31234300\tLow Mappability\nchr16\t31339100\t31358900\tHigh Signal Region\nchr16\t31818700\t31825200\tLow Mappability\nchr16\t32147700\t32153500\tLow Mappability\nchr16\t32489700\t32520100\tLow Mappability\nchr16\t32579100\t32598800\tLow Mappability\nchr16\t33847200\t33852600\tLow Mappability\nchr16\t34581100\t34591200\tLow Mappability\nchr16\t34742000\t34744000\tHigh Signal Region\nchr16\t35980600\t35983300\tHigh Signal Region\nchr16\t36764900\t36770500\tLow Mappability\nchr16\t38714200\t38721600\tLow Mappability\nchr16\t39563700\t39568200\tHigh Signal Region\nchr16\t41270700\t41273100\tHigh Signal Region\nchr16\t42657300\t42661200\tHigh Signal Region\nchr16\t42773100\t42779900\tHigh Signal Region\nchr16\t42931600\t42950000\tHigh Signal Region\nchr16\t43764000\t43771600\tLow Mappability\nchr16\t44040400\t44063900\tLow Mappability\nchr16\t44709800\t44726400\tLow Mappability\nchr16\t44920200\t44950700\tLow Mappability\nchr16\t45292600\t45293900\tHigh Signal Region\nchr16\t45352100\t45354000\tHigh Signal Region\nchr16\t46364600\t46369100\tHigh Signal Region\nchr16\t47099100\t47147300\tHigh Signal Region\nchr16\t47552300\t47564100\tLow Mappability\nchr16\t48579900\t48581300\tLow Mappability\nchr16\t49024900\t49031400\tLow Mappability\nchr16\t49148400\t49150300\tLow Mappability\nchr16\t49447700\t49489300\tHigh Signal Region\nchr16\t50084900\t50101400\tLow Mappability\nchr16\t50909100\t50926800\tLow Mappability\nchr16\t51087100\t51094300\tLow Mappability\nchr16\t51945800\t51980200\tHigh Signal Region\nchr16\t53412000\t53428900\tHigh Signal Region\nchr16\t53571500\t53595400\tLow Mappability\nchr16\t54298300\t54307600\tLow Mappability\nchr16\t54861600\t54869000\tHigh Signal Region\nchr16\t54959000\t54965200\tHigh Signal Region\nchr16\t55647800\t55681600\tLow Mappability\nchr16\t56038100\t56065100\tLow Mappability\nchr16\t56988400\t57008400\tHigh Signal Region\nchr16\t57085500\t57095800\tHigh Signal Region\nchr16\t57390200\t57392600\tHigh Signal Region\nchr16\t57792800\t57811700\tLow Mappability\nchr16\t58310800\t58343000\tHigh Signal Region\nchr16\t58632300\t58670400\tLow Mappability\nchr16\t59121800\t59129100\tLow Mappability\nchr16\t59310100\t59378100\tHigh Signal Region\nchr16\t60921200\t60970900\tHigh Signal Region\nchr16\t61312500\t61325200\tLow Mappability\nchr16\t62564300\t62599200\tHigh Signal Region\nchr16\t62875900\t62880400\tLow Mappability\nchr16\t63114300\t63151200\tHigh Signal Region\nchr16\t63301300\t63313600\tHigh Signal Region\nchr16\t64384600\t64425600\tHigh Signal Region\nchr16\t65176900\t65181400\tLow Mappability\nchr16\t66229300\t66247600\tLow Mappability\nchr16\t67328200\t67334700\tHigh Signal Region\nchr16\t68272300\t68274300\tHigh Signal Region\nchr16\t70542300\t70558300\tLow Mappability\nchr16\t70633900\t70639700\tLow Mappability\nchr16\t70892400\t70898400\tHigh Signal Region\nchr16\t70976900\t70982900\tHigh Signal Region\nchr16\t71687000\t71691500\tLow Mappability\nchr16\t72019300\t72023900\tLow Mappability\nchr16\t72056200\t72062100\tHigh Signal Region\nchr16\t72724800\t72730900\tLow Mappability\nchr16\t73656700\t73688600\tHigh Signal Region\nchr16\t74771800\t74781500\tLow Mappability\nchr16\t76057000\t76065000\tLow Mappability\nchr16\t76487100\t76519600\tHigh Signal Region\nchr16\t76988700\t76991600\tHigh Signal Region\nchr16\t77116900\t77121900\tLow Mappability\nchr16\t78977100\t79013600\tHigh Signal Region\nchr16\t79368600\t79376000\tLow Mappability\nchr16\t79782000\t79786700\tHigh Signal Region\nchr16\t79943000\t79948600\tLow Mappability\nchr16\t80269400\t80309700\tLow Mappability\nchr16\t81071700\t81079200\tLow Mappability\nchr16\t81779900\t81782000\tHigh Signal Region\nchr16\t81859300\t81865600\tHigh Signal Region\nchr16\t82079700\t82099600\tHigh Signal Region\nchr16\t82237800\t82243200\tLow Mappability\nchr16\t82828200\t82845600\tHigh Signal Region\nchr16\t83077300\t83081800\tHigh Signal Region\nchr16\t83360600\t83368000\tLow Mappability\nchr16\t84260500\t84283300\tHigh Signal Region\nchr16\t84380600\t84407600\tHigh Signal Region\nchr16\t84440100\t84446000\tHigh Signal Region\nchr16\t85671600\t85673000\tHigh Signal Region\nchr16\t85713500\t85720100\tHigh Signal Region\nchr16\t86333000\t86354300\tHigh Signal Region\nchr16\t86539500\t86570300\tHigh Signal Region\nchr16\t86819800\t86822100\tHigh Signal Region\nchr16\t87055400\t87060300\tHigh Signal Region\nchr16\t87287400\t87302500\tLow Mappability\nchr16\t87372300\t87391700\tLow Mappability\nchr16\t88022900\t88029900\tHigh Signal Region\nchr16\t88790600\t88797900\tLow Mappability\nchr16\t88957900\t88967800\tHigh Signal Region\nchr16\t89145200\t89196100\tLow Mappability\nchr16\t89431800\t89448400\tLow Mappability\nchr16\t89636000\t89642900\tHigh Signal Region\nchr16\t89877500\t89879700\tHigh Signal Region\nchr16\t90056200\t90072300\tLow Mappability\nchr16\t90341200\t90350100\tLow Mappability\nchr16\t91533700\t91551800\tHigh Signal Region\nchr16\t92254500\t92259400\tLow Mappability\nchr16\t93581500\t93622800\tHigh Signal Region\nchr16\t93685800\t93711200\tHigh Signal Region\nchr16\t93785700\t93790200\tHigh Signal Region\nchr16\t93991400\t93997900\tHigh Signal Region\nchr16\t94258100\t94282000\tLow Mappability\nchr16\t95782000\t95788900\tHigh Signal Region\nchr16\t95991000\t96010400\tLow Mappability\nchr16\t97996400\t98207700\tHigh Signal Region\nchr17\t0\t3039300\tHigh Signal Region\nchr17\t3075400\t3085400\tHigh Signal Region\nchr17\t3378900\t3380800\tHigh Signal Region\nchr17\t5863900\t5885100\tHigh Signal Region\nchr17\t6219100\t6717500\tHigh Signal Region\nchr17\t6877300\t7037900\tHigh Signal Region\nchr17\t7302300\t7430200\tHigh Signal Region\nchr17\t7615300\t7617200\tHigh Signal Region\nchr17\t7950200\t8052300\tHigh Signal Region\nchr17\t11097900\t11105100\tHigh Signal Region\nchr17\t13018500\t13469100\tHigh Signal Region\nchr17\t13492200\t13555800\tHigh Signal Region\nchr17\t13584800\t13656200\tHigh Signal Region\nchr17\t14961200\t15054300\tLow Mappability\nchr17\t20859400\t20865200\tHigh Signal Region\nchr17\t23426600\t23537000\tHigh Signal Region\nchr17\t23730600\t23732500\tHigh Signal Region\nchr17\t24095300\t24097300\tHigh Signal Region\nchr17\t29101000\t29109600\tHigh Signal Region\nchr17\t31569500\t31571400\tHigh Signal Region\nchr17\t35367400\t35480300\tLow Mappability\nchr17\t36230300\t36232500\tHigh Signal Region\nchr17\t38498200\t38500800\tHigh Signal Region\nchr17\t39842000\t39849700\tHigh Signal Region\nchr17\t40422500\t40427000\tHigh Signal Region\nchr17\t50569500\t50571400\tHigh Signal Region\nchr17\t53034300\t53056100\tHigh Signal Region\nchr17\t53151500\t53153500\tHigh Signal Region\nchr17\t53807400\t53820300\tHigh Signal Region\nchr17\t54112300\t54134200\tHigh Signal Region\nchr17\t57368400\t57399900\tHigh Signal Region\nchr17\t62736600\t62738500\tHigh Signal Region\nchr17\t66798500\t66800400\tHigh Signal Region\nchr17\t67740400\t67742500\tHigh Signal Region\nchr17\t70962200\t70964800\tHigh Signal Region\nchr17\t82975900\t82991600\tHigh Signal Region\nchr17\t84458800\t84464500\tLow Mappability\nchr17\t85264100\t85266000\tHigh Signal Region\nchr17\t93017000\t93047400\tHigh Signal Region\nchr17\t93623500\t93646700\tHigh Signal Region\nchr17\t94886200\t94987200\tHigh Signal Region\nchr18\t0\t3063700\tHigh Signal Region\nchr18\t3085500\t3142600\tHigh Signal Region\nchr18\t3568100\t3570100\tLow Mappability\nchr18\t3619800\t3652100\tLow Mappability\nchr18\t3779700\t3785600\tHigh Signal Region\nchr18\t3815100\t3819300\tHigh Signal Region\nchr18\t3873200\t3889000\tHigh Signal Region\nchr18\t4194700\t4199900\tHigh Signal Region\nchr18\t4456700\t4504600\tHigh Signal Region\nchr18\t4658000\t4664400\tLow Mappability\nchr18\t4695200\t4701800\tLow Mappability\nchr18\t5499400\t5502000\tLow Mappability\nchr18\t5895900\t5900400\tLow Mappability\nchr18\t6043700\t6046600\tLow Mappability\nchr18\t6343100\t6376400\tLow Mappability\nchr18\t6663800\t6669200\tHigh Signal Region\nchr18\t6796200\t6803600\tLow Mappability\nchr18\t6853600\t6868500\tLow Mappability\nchr18\t7032800\t7035500\tHigh Signal Region\nchr18\t7527500\t7534800\tHigh Signal Region\nchr18\t7782300\t7798400\tHigh Signal Region\nchr18\t7998000\t8018800\tLow Mappability\nchr18\t8164900\t8183000\tHigh Signal Region\nchr18\t8243000\t8271800\tHigh Signal Region\nchr18\t8292000\t8294000\tLow Mappability\nchr18\t8721900\t8747000\tHigh Signal Region\nchr18\t9095200\t9127300\tHigh Signal Region\nchr18\t9248500\t9269200\tLow Mappability\nchr18\t9420000\t9426100\tHigh Signal Region\nchr18\t9890700\t9915900\tHigh Signal Region\nchr18\t11168900\t11192100\tHigh Signal Region\nchr18\t11247700\t11293200\tHigh Signal Region\nchr18\t11626000\t11648000\tLow Mappability\nchr18\t12945100\t12956300\tHigh Signal Region\nchr18\t13030000\t13041900\tHigh Signal Region\nchr18\t13161400\t13180500\tHigh Signal Region\nchr18\t13241200\t13251100\tLow Mappability\nchr18\t13296400\t13300000\tHigh Signal Region\nchr18\t13513200\t13517200\tHigh Signal Region\nchr18\t14732900\t14739600\tLow Mappability\nchr18\t15225500\t15232800\tHigh Signal Region\nchr18\t15366900\t15382100\tHigh Signal Region\nchr18\t15695100\t15737600\tHigh Signal Region\nchr18\t16283100\t16288900\tHigh Signal Region\nchr18\t16988600\t17013600\tLow Mappability\nchr18\t17116100\t17119600\tHigh Signal Region\nchr18\t17346100\t17352400\tHigh Signal Region\nchr18\t17425100\t17480600\tHigh Signal Region\nchr18\t17513300\t17517900\tHigh Signal Region\nchr18\t17541300\t17559000\tHigh Signal Region\nchr18\t17593300\t17598500\tHigh Signal Region\nchr18\t17938300\t17951600\tLow Mappability\nchr18\t18816600\t18823800\tHigh Signal Region\nchr18\t18916300\t18917900\tHigh Signal Region\nchr18\t18976900\t18992400\tHigh Signal Region\nchr18\t19240600\t19289100\tHigh Signal Region\nchr18\t19345800\t19352600\tLow Mappability\nchr18\t19430400\t19448100\tHigh Signal Region\nchr18\t19679600\t19681600\tLow Mappability\nchr18\t19812100\t19836500\tHigh Signal Region\nchr18\t20352500\t20369800\tHigh Signal Region\nchr18\t20896200\t20910000\tLow Mappability\nchr18\t21261800\t21268900\tLow Mappability\nchr18\t21528200\t21541600\tHigh Signal Region\nchr18\t21943200\t21945200\tLow Mappability\nchr18\t22297400\t22304000\tHigh Signal Region\nchr18\t23186200\t23215300\tHigh Signal Region\nchr18\t25045100\t25047300\tHigh Signal Region\nchr18\t25253000\t25259500\tHigh Signal Region\nchr18\t25905600\t25928600\tHigh Signal Region\nchr18\t26003000\t26008100\tLow Mappability\nchr18\t26829800\t26837100\tLow Mappability\nchr18\t26998200\t27005600\tLow Mappability\nchr18\t27062000\t27068200\tHigh Signal Region\nchr18\t28151300\t28167300\tHigh Signal Region\nchr18\t28441700\t28446600\tLow Mappability\nchr18\t28482900\t28484900\tHigh Signal Region\nchr18\t28814100\t28816900\tHigh Signal Region\nchr18\t28960100\t28966000\tLow Mappability\nchr18\t29014700\t29022000\tHigh Signal Region\nchr18\t29557800\t29559800\tHigh Signal Region\nchr18\t29713000\t29719200\tHigh Signal Region\nchr18\t31281100\t31294300\tHigh Signal Region\nchr18\t32758400\t32793400\tHigh Signal Region\nchr18\t33212800\t33221500\tLow Mappability\nchr18\t33275100\t33331000\tHigh Signal Region\nchr18\t33697400\t33722600\tLow Mappability\nchr18\t34083600\t34087300\tLow Mappability\nchr18\t34397100\t34409800\tLow Mappability\nchr18\t35318500\t35320400\tLow Mappability\nchr18\t36454200\t36494600\tLow Mappability\nchr18\t36981500\t36988700\tLow Mappability\nchr18\t37031800\t37045800\tHigh Signal Region\nchr18\t37364600\t37398900\tLow Mappability\nchr18\t37545500\t37645000\tHigh Signal Region\nchr18\t39598600\t39604900\tHigh Signal Region\nchr18\t40306300\t40309300\tHigh Signal Region\nchr18\t40708500\t40713600\tLow Mappability\nchr18\t41381600\t41387500\tHigh Signal Region\nchr18\t41465300\t41471500\tHigh Signal Region\nchr18\t41820100\t41826100\tHigh Signal Region\nchr18\t41960600\t41966100\tHigh Signal Region\nchr18\t42556800\t42559800\tHigh Signal Region\nchr18\t42913000\t42914900\tHigh Signal Region\nchr18\t43335500\t43337900\tHigh Signal Region\nchr18\t43889500\t43900400\tHigh Signal Region\nchr18\t44033600\t44050200\tHigh Signal Region\nchr18\t44228000\t44263100\tHigh Signal Region\nchr18\t44291600\t44295600\tHigh Signal Region\nchr18\t44361600\t44380500\tHigh Signal Region\nchr18\t44873100\t44875100\tLow Mappability\nchr18\t44981000\t45032700\tHigh Signal Region\nchr18\t45131400\t45133400\tHigh Signal Region\nchr18\t45291700\t45314300\tLow Mappability\nchr18\t45357300\t45364700\tLow Mappability\nchr18\t45392200\t45397700\tHigh Signal Region\nchr18\t45506800\t45513400\tHigh Signal Region\nchr18\t45998300\t46038000\tLow Mappability\nchr18\t46082000\t46101400\tHigh Signal Region\nchr18\t46439100\t46444100\tLow Mappability\nchr18\t46791400\t46793400\tLow Mappability\nchr18\t47648600\t47654100\tLow Mappability\nchr18\t47769900\t47783100\tLow Mappability\nchr18\t48009500\t48011400\tHigh Signal Region\nchr18\t48208100\t48220300\tHigh Signal Region\nchr18\t48705800\t48713100\tLow Mappability\nchr18\t48831300\t48836100\tHigh Signal Region\nchr18\t49387700\t49397800\tHigh Signal Region\nchr18\t49669200\t49695600\tHigh Signal Region\nchr18\t50253400\t50268700\tHigh Signal Region\nchr18\t50632100\t50700200\tLow Mappability\nchr18\t51072000\t51077600\tLow Mappability\nchr18\t51658600\t51698300\tHigh Signal Region\nchr18\t52020200\t52059300\tHigh Signal Region\nchr18\t52256200\t52262200\tHigh Signal Region\nchr18\t52378900\t52395000\tLow Mappability\nchr18\t52876200\t52883200\tHigh Signal Region\nchr18\t53828800\t53839900\tLow Mappability\nchr18\t53869300\t53876600\tLow Mappability\nchr18\t54023900\t54030000\tHigh Signal Region\nchr18\t54288100\t54335900\tLow Mappability\nchr18\t54698000\t54707800\tHigh Signal Region\nchr18\t55222400\t55224400\tLow Mappability\nchr18\t55311000\t55321100\tLow Mappability\nchr18\t55414800\t55436200\tLow Mappability\nchr18\t55899800\t55901700\tHigh Signal Region\nchr18\t55938500\t55954100\tHigh Signal Region\nchr18\t56273000\t56276900\tHigh Signal Region\nchr18\t56302600\t56304500\tHigh Signal Region\nchr18\t56341200\t56346000\tHigh Signal Region\nchr18\t56826900\t56830200\tLow Mappability\nchr18\t57560400\t57562500\tLow Mappability\nchr18\t58992700\t58999300\tLow Mappability\nchr18\t59496300\t59511000\tHigh Signal Region\nchr18\t59929900\t59955000\tHigh Signal Region\nchr18\t60042400\t60044400\tLow Mappability\nchr18\t60206100\t60238100\tHigh Signal Region\nchr18\t60525200\t60533800\tLow Mappability\nchr18\t62237400\t62247700\tHigh Signal Region\nchr18\t62273700\t62292800\tLow Mappability\nchr18\t62752700\t62755100\tHigh Signal Region\nchr18\t64131300\t64132600\tHigh Signal Region\nchr18\t64448400\t64454900\tLow Mappability\nchr18\t65103100\t65105000\tHigh Signal Region\nchr18\t65385700\t65405100\tLow Mappability\nchr18\t65492400\t65494700\tLow Mappability\nchr18\t65716300\t65719400\tLow Mappability\nchr18\t66543200\t66548900\tHigh Signal Region\nchr18\t66750000\t66759900\tLow Mappability\nchr18\t66881200\t66887200\tHigh Signal Region\nchr18\t68381300\t68387800\tHigh Signal Region\nchr18\t68412100\t68425800\tLow Mappability\nchr18\t68461300\t68489000\tHigh Signal Region\nchr18\t68691100\t68693200\tHigh Signal Region\nchr18\t69759300\t69761300\tLow Mappability\nchr18\t70489500\t70515400\tHigh Signal Region\nchr18\t70775600\t70791900\tHigh Signal Region\nchr18\t70842100\t70849200\tLow Mappability\nchr18\t71032500\t71038800\tHigh Signal Region\nchr18\t71139200\t71145200\tHigh Signal Region\nchr18\t71208200\t71211300\tLow Mappability\nchr18\t71267000\t71273300\tLow Mappability\nchr18\t71630400\t71641100\tLow Mappability\nchr18\t72753900\t72794900\tHigh Signal Region\nchr18\t72987900\t72991000\tHigh Signal Region\nchr18\t73259600\t73264100\tLow Mappability\nchr18\t74553100\t74566400\tHigh Signal Region\nchr18\t74745500\t74758500\tLow Mappability\nchr18\t74880300\t74882000\tHigh Signal Region\nchr18\t76177900\t76184300\tLow Mappability\nchr18\t76579700\t76586300\tLow Mappability\nchr18\t77264400\t77271000\tHigh Signal Region\nchr18\t78197300\t78199300\tHigh Signal Region\nchr18\t78407800\t78428500\tLow Mappability\nchr18\t78861400\t78867900\tHigh Signal Region\nchr18\t80021700\t80028900\tLow Mappability\nchr18\t80307500\t80309600\tLow Mappability\nchr18\t80455500\t80518400\tLow Mappability\nchr18\t81299700\t81306200\tLow Mappability\nchr18\t82052100\t82058200\tHigh Signal Region\nchr18\t82160100\t82227800\tHigh Signal Region\nchr18\t82319500\t82339900\tHigh Signal Region\nchr18\t82692900\t82717900\tLow Mappability\nchr18\t83171100\t83178400\tLow Mappability\nchr18\t83700500\t83707900\tLow Mappability\nchr18\t84828700\t84833000\tHigh Signal Region\nchr18\t85035000\t85080600\tHigh Signal Region\nchr18\t85105800\t85112200\tHigh Signal Region\nchr18\t85169900\t85175900\tHigh Signal Region\nchr18\t85377800\t85382800\tLow Mappability\nchr18\t85697000\t85699200\tHigh Signal Region\nchr18\t85783600\t85789900\tHigh Signal Region\nchr18\t86508300\t86510200\tHigh Signal Region\nchr18\t86560600\t86586100\tHigh Signal Region\nchr18\t86828500\t86849500\tHigh Signal Region\nchr18\t87006300\t87009800\tHigh Signal Region\nchr18\t87141500\t87161200\tHigh Signal Region\nchr18\t87568300\t87574300\tHigh Signal Region\nchr18\t88149300\t88155400\tHigh Signal Region\nchr18\t89030400\t89036400\tHigh Signal Region\nchr18\t89615900\t89650500\tLow Mappability\nchr18\t89983200\t89989700\tLow Mappability\nchr18\t90055500\t90092500\tHigh Signal Region\nchr18\t90113400\t90125400\tLow Mappability\nchr18\t90464100\t90501300\tHigh Signal Region\nchr18\t90601200\t90702600\tHigh Signal Region\nchr19\t0\t3140800\tHigh Signal Region\nchr19\t3161400\t3248600\tHigh Signal Region\nchr19\t4061100\t4066400\tLow Mappability\nchr19\t6581000\t6594300\tHigh Signal Region\nchr19\t7713600\t7774800\tHigh Signal Region\nchr19\t7810700\t7843900\tLow Mappability\nchr19\t8203200\t8285500\tLow Mappability\nchr19\t9250500\t9357700\tHigh Signal Region\nchr19\t9502000\t9565000\tLow Mappability\nchr19\t9745800\t9803300\tHigh Signal Region\nchr19\t9823500\t9837700\tHigh Signal Region\nchr19\t10507900\t10510300\tHigh Signal Region\nchr19\t10954500\t10960300\tLow Mappability\nchr19\t11199700\t11239800\tHigh Signal Region\nchr19\t12447200\t12454600\tLow Mappability\nchr19\t13203500\t13216400\tHigh Signal Region\nchr19\t13330600\t13357100\tHigh Signal Region\nchr19\t13685000\t13693300\tHigh Signal Region\nchr19\t13760500\t13777200\tHigh Signal Region\nchr19\t15256700\t15263000\tHigh Signal Region\nchr19\t15433400\t15438100\tHigh Signal Region\nchr19\t15711800\t15719800\tHigh Signal Region\nchr19\t15839200\t15846600\tHigh Signal Region\nchr19\t15956500\t15958500\tLow Mappability\nchr19\t16670500\t16673100\tHigh Signal Region\nchr19\t18358000\t18364200\tHigh Signal Region\nchr19\t18532700\t18535600\tHigh Signal Region\nchr19\t19132200\t19161200\tHigh Signal Region\nchr19\t19509000\t19514900\tHigh Signal Region\nchr19\t19870300\t19876900\tLow Mappability\nchr19\t20080700\t20081800\tHigh Signal Region\nchr19\t20140700\t20144100\tLow Mappability\nchr19\t20288200\t20297900\tLow Mappability\nchr19\t20455400\t20462700\tLow Mappability\nchr19\t20839700\t20843900\tLow Mappability\nchr19\t21218200\t21243800\tHigh Signal Region\nchr19\t21532400\t21534400\tLow Mappability\nchr19\t22644100\t22651700\tHigh Signal Region\nchr19\t22722400\t22728400\tLow Mappability\nchr19\t23356500\t23358400\tHigh Signal Region\nchr19\t23739200\t23754000\tHigh Signal Region\nchr19\t24040300\t24042300\tLow Mappability\nchr19\t24911900\t24919200\tHigh Signal Region\nchr19\t25741800\t25770100\tHigh Signal Region\nchr19\t25917500\t25920000\tHigh Signal Region\nchr19\t27751400\t27758100\tHigh Signal Region\nchr19\t28149600\t28156600\tHigh Signal Region\nchr19\t30907400\t30908700\tHigh Signal Region\nchr19\t30963600\t30968000\tLow Mappability\nchr19\t31722800\t31735800\tHigh Signal Region\nchr19\t32203200\t32211600\tLow Mappability\nchr19\t32441800\t32449100\tLow Mappability\nchr19\t32822000\t32824000\tLow Mappability\nchr19\t33439100\t33446100\tLow Mappability\nchr19\t33864200\t33877900\tHigh Signal Region\nchr19\t33949100\t33958200\tHigh Signal Region\nchr19\t34131200\t34161200\tLow Mappability\nchr19\t34581900\t34613000\tHigh Signal Region\nchr19\t35076400\t35079800\tHigh Signal Region\nchr19\t35650200\t35673500\tHigh Signal Region\nchr19\t36702500\t36723400\tHigh Signal Region\nchr19\t37298800\t37301800\tLow Mappability\nchr19\t37617300\t37624600\tLow Mappability\nchr19\t38490200\t38495300\tLow Mappability\nchr19\t39078100\t39079500\tHigh Signal Region\nchr19\t39106700\t39156300\tHigh Signal Region\nchr19\t39244700\t39270400\tHigh Signal Region\nchr19\t39331700\t39424100\tHigh Signal Region\nchr19\t39599900\t39607200\tLow Mappability\nchr19\t39658700\t39695100\tLow Mappability\nchr19\t40020400\t40026800\tLow Mappability\nchr19\t40094100\t40153300\tHigh Signal Region\nchr19\t40328500\t40330000\tLow Mappability\nchr19\t41142700\t41150000\tLow Mappability\nchr19\t41424200\t41473100\tLow Mappability\nchr19\t42346000\t42350500\tLow Mappability\nchr19\t42647600\t42649700\tLow Mappability\nchr19\t43118800\t43124600\tHigh Signal Region\nchr19\t43236000\t43238000\tLow Mappability\nchr19\t43321500\t43323700\tHigh Signal Region\nchr19\t44145700\t44171700\tLow Mappability\nchr19\t44218500\t44225000\tLow Mappability\nchr19\t44862100\t44864300\tHigh Signal Region\nchr19\t45004900\t45096500\tLow Mappability\nchr19\t45182300\t45190200\tHigh Signal Region\nchr19\t45649000\t45661500\tHigh Signal Region\nchr19\t45699400\t45706300\tLow Mappability\nchr19\t47590300\t47602700\tLow Mappability\nchr19\t48484600\t48496700\tHigh Signal Region\nchr19\t48743800\t48746300\tHigh Signal Region\nchr19\t50107900\t50114400\tLow Mappability\nchr19\t50309700\t50311600\tHigh Signal Region\nchr19\t50754100\t50755900\tLow Mappability\nchr19\t50828900\t50835600\tHigh Signal Region\nchr19\t51649700\t51655800\tHigh Signal Region\nchr19\t51949000\t51955700\tLow Mappability\nchr19\t52303100\t52309700\tLow Mappability\nchr19\t52927900\t52932300\tLow Mappability\nchr19\t52967800\t52991100\tLow Mappability\nchr19\t53522200\t53527100\tHigh Signal Region\nchr19\t53767900\t53777800\tHigh Signal Region\nchr19\t54235200\t54236600\tHigh Signal Region\nchr19\t54884700\t54936800\tHigh Signal Region\nchr19\t54994900\t55001700\tLow Mappability\nchr19\t55976700\t55984000\tLow Mappability\nchr19\t56248700\t56259000\tLow Mappability\nchr19\t56846600\t56849100\tHigh Signal Region\nchr19\t57514200\t57520700\tLow Mappability\nchr19\t57634000\t57635600\tLow Mappability\nchr19\t57827000\t57832700\tLow Mappability\nchr19\t58012500\t58014600\tLow Mappability\nchr19\t58112400\t58114500\tHigh Signal Region\nchr19\t58481300\t58483200\tHigh Signal Region\nchr19\t59221800\t59240400\tHigh Signal Region\nchr19\t59763100\t59779900\tHigh Signal Region\nchr19\t60082500\t60089900\tHigh Signal Region\nchr19\t60906900\t60934000\tHigh Signal Region\nchr19\t61162600\t61174300\tLow Mappability\nchr19\t61197700\t61268100\tHigh Signal Region\nchr19\t61330300\t61431500\tHigh Signal Region\nchr1\t8628600\t8719100\tHigh Signal Region\nchr1\t12038300\t12041400\tHigh Signal Region\nchr1\t14958600\t14992600\tHigh Signal Region\nchr1\t17466800\t17479900\tHigh Signal Region\nchr1\t18872500\t18901300\tHigh Signal Region\nchr1\t19175300\t19177200\tHigh Signal Region\nchr1\t22555000\t22556900\tHigh Signal Region\nchr1\t24610600\t24617100\tHigh Signal Region\nchr1\t24683100\t24685100\tHigh Signal Region\nchr1\t26685100\t26689200\tHigh Signal Region\nchr1\t43776800\t43779800\tHigh Signal Region\nchr1\t44198000\t44202200\tHigh Signal Region\nchr1\t46701700\t46756600\tHigh Signal Region\nchr1\t48880600\t48882500\tHigh Signal Region\nchr1\t56119600\t56143500\tHigh Signal Region\nchr1\t56772200\t56783300\tHigh Signal Region\nchr1\t58613000\t58614900\tHigh Signal Region\nchr1\t63629100\t63631600\tHigh Signal Region\nchr1\t69455800\t69457800\tHigh Signal Region\nchr1\t71078400\t71085500\tHigh Signal Region\nchr1\t71250600\t71256700\tHigh Signal Region\nchr1\t73549100\t73555300\tHigh Signal Region\nchr1\t73832600\t73902400\tHigh Signal Region\nchr1\t78572900\t78575400\tHigh Signal Region\nchr1\t84953500\t85663200\tHigh Signal Region\nchr1\t88209400\t88311700\tHigh Signal Region\nchr1\t94093800\t94109400\tHigh Signal Region\nchr1\t95451000\t95452900\tHigh Signal Region\nchr1\t95783900\t95789700\tHigh Signal Region\nchr1\t95810200\t95851700\tHigh Signal Region\nchr1\t100737900\t100760500\tHigh Signal Region\nchr1\t101040100\t101046300\tHigh Signal Region\nchr1\t102627300\t102644300\tHigh Signal Region\nchr1\t105226800\t105230700\tHigh Signal Region\nchr1\t110170400\t110188300\tHigh Signal Region\nchr1\t113602700\t113604800\tHigh Signal Region\nchr1\t114557300\t114579100\tHigh Signal Region\nchr1\t114643300\t114660500\tHigh Signal Region\nchr1\t115447500\t115482800\tHigh Signal Region\nchr1\t122356200\t122358200\tHigh Signal Region\nchr1\t133593600\t133611300\tHigh Signal Region\nchr1\t142651800\t142672300\tHigh Signal Region\nchr1\t145444500\t145449100\tHigh Signal Region\nchr1\t146120600\t146128200\tHigh Signal Region\nchr1\t151181600\t151212000\tHigh Signal Region\nchr1\t165862800\t165864700\tLow Mappability\nchr1\t171033000\t171112400\tHigh Signal Region\nchr1\t172716800\t172738200\tHigh Signal Region\nchr1\t172878700\t172885100\tHigh Signal Region\nchr1\t178538700\t178540700\tHigh Signal Region\nchr1\t181742100\t181752400\tHigh Signal Region\nchr1\t182628900\t182630800\tHigh Signal Region\nchr1\t183298200\t183300500\tHigh Signal Region\nchr1\t190299400\t190304600\tHigh Signal Region\nchr1\t192453100\t192471800\tHigh Signal Region\nchr1\t193226900\t193228800\tHigh Signal Region\nchr1\t195239800\t195257400\tHigh Signal Region\nchr1\t195278100\t195280200\tHigh Signal Region\nchr1\t195320700\t195471900\tHigh Signal Region\nchr2\t0\t3086300\tHigh Signal Region\nchr2\t3474900\t3488800\tHigh Signal Region\nchr2\t3932700\t3939100\tLow Mappability\nchr2\t3963500\t3986100\tHigh Signal Region\nchr2\t4515100\t4518600\tHigh Signal Region\nchr2\t4600600\t4620300\tHigh Signal Region\nchr2\t5378100\t5394600\tHigh Signal Region\nchr2\t5545900\t5561600\tHigh Signal Region\nchr2\t6078200\t6095300\tHigh Signal Region\nchr2\t6773100\t6777500\tLow Mappability\nchr2\t6832200\t6846700\tHigh Signal Region\nchr2\t7137500\t7139600\tHigh Signal Region\nchr2\t7404000\t7458100\tHigh Signal Region\nchr2\t7571700\t7609800\tHigh Signal Region\nchr2\t7656300\t7669700\tLow Mappability\nchr2\t7752800\t7758500\tHigh Signal Region\nchr2\t8034600\t8042900\tHigh Signal Region\nchr2\t8266200\t8275600\tHigh Signal Region\nchr2\t8528400\t8535700\tHigh Signal Region\nchr2\t8938000\t8940500\tHigh Signal Region\nchr2\t9212600\t9219300\tHigh Signal Region\nchr2\t10177100\t10183400\tLow Mappability\nchr2\t10483200\t10501500\tLow Mappability\nchr2\t10677000\t10697600\tLow Mappability\nchr2\t12605500\t12668600\tHigh Signal Region\nchr2\t13824000\t13869200\tHigh Signal Region\nchr2\t13946300\t13948900\tHigh Signal Region\nchr2\t14014100\t14035300\tHigh Signal Region\nchr2\t14359100\t14386600\tHigh Signal Region\nchr2\t14919000\t14924500\tHigh Signal Region\nchr2\t15301300\t15334700\tHigh Signal Region\nchr2\t15430100\t15435500\tLow Mappability\nchr2\t15575900\t15602800\tHigh Signal Region\nchr2\t15716700\t15721100\tHigh Signal Region\nchr2\t15768300\t15770500\tHigh Signal Region\nchr2\t16192400\t16198500\tHigh Signal Region\nchr2\t16320200\t16326500\tLow Mappability\nchr2\t16762800\t16787000\tHigh Signal Region\nchr2\t17383200\t17385100\tHigh Signal Region\nchr2\t17612500\t17654500\tLow Mappability\nchr2\t17747200\t17753000\tHigh Signal Region\nchr2\t19209900\t19212900\tHigh Signal Region\nchr2\t19498400\t19510300\tHigh Signal Region\nchr2\t19707900\t19712200\tHigh Signal Region\nchr2\t20038500\t20067400\tLow Mappability\nchr2\t20426800\t20433300\tLow Mappability\nchr2\t20898900\t20901100\tHigh Signal Region\nchr2\t21062600\t21082200\tLow Mappability\nchr2\t22049700\t22087700\tHigh Signal Region\nchr2\t22137300\t22165500\tHigh Signal Region\nchr2\t22389900\t22608700\tHigh Signal Region\nchr2\t22737300\t22745800\tHigh Signal Region\nchr2\t23009600\t23015000\tLow Mappability\nchr2\t23274600\t23304900\tHigh Signal Region\nchr2\t23693700\t23707900\tHigh Signal Region\nchr2\t24193300\t24199000\tHigh Signal Region\nchr2\t26333100\t26351900\tLow Mappability\nchr2\t26759100\t26763600\tHigh Signal Region\nchr2\t26998200\t27004400\tLow Mappability\nchr2\t28183200\t28205000\tHigh Signal Region\nchr2\t30204600\t30239600\tLow Mappability\nchr2\t32381300\t32488200\tLow Mappability\nchr2\t33933000\t33935300\tHigh Signal Region\nchr2\t34049900\t34051800\tHigh Signal Region\nchr2\t34903900\t34935900\tLow Mappability\nchr2\t35090800\t35109900\tHigh Signal Region\nchr2\t35505000\t35526700\tLow Mappability\nchr2\t36008600\t36019300\tLow Mappability\nchr2\t36401900\t36413100\tHigh Signal Region\nchr2\t36508600\t36515200\tHigh Signal Region\nchr2\t36542800\t36549100\tHigh Signal Region\nchr2\t36761000\t36766500\tHigh Signal Region\nchr2\t36951900\t36970700\tHigh Signal Region\nchr2\t37156900\t37185900\tHigh Signal Region\nchr2\t37339700\t37359400\tLow Mappability\nchr2\t38564700\t38566600\tLow Mappability\nchr2\t39225400\t39293200\tHigh Signal Region\nchr2\t39360600\t39367900\tLow Mappability\nchr2\t39517800\t39534800\tHigh Signal Region\nchr2\t39778500\t39785700\tLow Mappability\nchr2\t39887500\t39915800\tHigh Signal Region\nchr2\t40131200\t40240800\tHigh Signal Region\nchr2\t40262500\t40268600\tHigh Signal Region\nchr2\t40766400\t40794000\tHigh Signal Region\nchr2\t41059500\t41070200\tLow Mappability\nchr2\t41168700\t41171400\tHigh Signal Region\nchr2\t41692800\t41694800\tHigh Signal Region\nchr2\t41744300\t41751600\tLow Mappability\nchr2\t41775100\t41781500\tHigh Signal Region\nchr2\t41895300\t41897200\tHigh Signal Region\nchr2\t42044500\t42051600\tHigh Signal Region\nchr2\t42200300\t42240700\tHigh Signal Region\nchr2\t42950100\t42956600\tHigh Signal Region\nchr2\t43347900\t43356400\tHigh Signal Region\nchr2\t44936600\t44942400\tHigh Signal Region\nchr2\t46224800\t46226700\tHigh Signal Region\nchr2\t46343100\t46348100\tLow Mappability\nchr2\t46574200\t46579600\tLow Mappability\nchr2\t47008600\t47023500\tHigh Signal Region\nchr2\t47196300\t47199300\tHigh Signal Region\nchr2\t47533600\t47642600\tHigh Signal Region\nchr2\t47942200\t47943800\tHigh Signal Region\nchr2\t48483000\t48491000\tLow Mappability\nchr2\t50543200\t50545500\tHigh Signal Region\nchr2\t50679600\t50686800\tLow Mappability\nchr2\t51552600\t51555600\tHigh Signal Region\nchr2\t51750900\t51756000\tHigh Signal Region\nchr2\t51881600\t51890600\tLow Mappability\nchr2\t51945900\t51948400\tHigh Signal Region\nchr2\t52695900\t52718600\tHigh Signal Region\nchr2\t52786800\t52796300\tHigh Signal Region\nchr2\t53317700\t53321600\tLow Mappability\nchr2\t53347800\t53367000\tHigh Signal Region\nchr2\t53633400\t53642900\tHigh Signal Region\nchr2\t53745700\t53799800\tHigh Signal Region\nchr2\t54252600\t54258500\tHigh Signal Region\nchr2\t54698000\t54747900\tHigh Signal Region\nchr2\t54862600\t54895300\tHigh Signal Region\nchr2\t55197500\t55216400\tHigh Signal Region\nchr2\t55308300\t55353700\tHigh Signal Region\nchr2\t55823800\t55829000\tHigh Signal Region\nchr2\t55860200\t55874300\tLow Mappability\nchr2\t55942000\t55947800\tHigh Signal Region\nchr2\t56192800\t56194600\tHigh Signal Region\nchr2\t56298700\t56304900\tHigh Signal Region\nchr2\t56465200\t56471900\tHigh Signal Region\nchr2\t56834300\t56879100\tHigh Signal Region\nchr2\t56988500\t56990600\tLow Mappability\nchr2\t57166400\t57172900\tLow Mappability\nchr2\t57214400\t57223500\tLow Mappability\nchr2\t57417400\t57446500\tHigh Signal Region\nchr2\t57628500\t57633800\tHigh Signal Region\nchr2\t57726600\t57728500\tHigh Signal Region\nchr2\t58212900\t58263100\tHigh Signal Region\nchr2\t58648300\t58691900\tHigh Signal Region\nchr2\t58881200\t58902500\tHigh Signal Region\nchr2\t59971300\t59972800\tLow Mappability\nchr2\t61038200\t61042700\tHigh Signal Region\nchr2\t61959600\t61965300\tHigh Signal Region\nchr2\t62022900\t62040100\tHigh Signal Region\nchr2\t62861100\t62867200\tHigh Signal Region\nchr2\t63297300\t63302700\tLow Mappability\nchr2\t63368100\t63403900\tHigh Signal Region\nchr2\t63462300\t63483800\tHigh Signal Region\nchr2\t63641200\t63654600\tHigh Signal Region\nchr2\t63718200\t63725400\tHigh Signal Region\nchr2\t63838100\t63845300\tLow Mappability\nchr2\t64309200\t64319600\tHigh Signal Region\nchr2\t64608400\t64633400\tLow Mappability\nchr2\t64698700\t64703300\tHigh Signal Region\nchr2\t65592500\t65602200\tHigh Signal Region\nchr2\t65737700\t65781500\tLow Mappability\nchr2\t66721600\t66750400\tHigh Signal Region\nchr2\t66845100\t66852300\tHigh Signal Region\nchr2\t67408400\t67414500\tHigh Signal Region\nchr2\t67939700\t67946000\tHigh Signal Region\nchr2\t68770400\t68776700\tHigh Signal Region\nchr2\t68917800\t68924100\tLow Mappability\nchr2\t69353900\t69356600\tHigh Signal Region\nchr2\t70263100\t70270000\tLow Mappability\nchr2\t70880100\t70892900\tHigh Signal Region\nchr2\t71054700\t71071300\tLow Mappability\nchr2\t71942000\t71949500\tLow Mappability\nchr2\t72270200\t72275700\tLow Mappability\nchr2\t73867000\t73868900\tHigh Signal Region\nchr2\t74364300\t74402600\tLow Mappability\nchr2\t74437600\t74444900\tLow Mappability\nchr2\t75499500\t75504600\tHigh Signal Region\nchr2\t77224000\t77230500\tLow Mappability\nchr2\t78318000\t78339500\tHigh Signal Region\nchr2\t79437700\t79441900\tHigh Signal Region\nchr2\t79936500\t79943700\tHigh Signal Region\nchr2\t80119000\t80121500\tHigh Signal Region\nchr2\t80220600\t80257700\tLow Mappability\nchr2\t80795600\t80838700\tHigh Signal Region\nchr2\t80879000\t80880200\tHigh Signal Region\nchr2\t80956500\t81006000\tHigh Signal Region\nchr2\t81069000\t81075100\tHigh Signal Region\nchr2\t81639400\t81644800\tHigh Signal Region\nchr2\t81750800\t81756800\tHigh Signal Region\nchr2\t81790000\t81795900\tHigh Signal Region\nchr2\t82329800\t82340100\tHigh Signal Region\nchr2\t82673800\t82679900\tHigh Signal Region\nchr2\t82714300\t82728500\tHigh Signal Region\nchr2\t82783900\t82789500\tHigh Signal Region\nchr2\t82868800\t82887900\tHigh Signal Region\nchr2\t82916300\t82936800\tHigh Signal Region\nchr2\t83120100\t83146100\tHigh Signal Region\nchr2\t83185100\t83193200\tHigh Signal Region\nchr2\t83325900\t83328200\tHigh Signal Region\nchr2\t83413500\t83587500\tHigh Signal Region\nchr2\t83865600\t83893100\tHigh Signal Region\nchr2\t83931600\t83995800\tLow Mappability\nchr2\t84080900\t84085600\tHigh Signal Region\nchr2\t84505000\t84510500\tLow Mappability\nchr2\t84532500\t84534600\tLow Mappability\nchr2\t84564800\t84576000\tLow Mappability\nchr2\t85685600\t85701800\tLow Mappability\nchr2\t85874000\t85896300\tHigh Signal Region\nchr2\t86018200\t86021700\tLow Mappability\nchr2\t86303400\t86317700\tHigh Signal Region\nchr2\t86339600\t86346900\tLow Mappability\nchr2\t86612700\t86617500\tHigh Signal Region\nchr2\t87381000\t87382800\tHigh Signal Region\nchr2\t87875700\t87941300\tHigh Signal Region\nchr2\t88167400\t88212600\tHigh Signal Region\nchr2\t88776200\t88780800\tHigh Signal Region\nchr2\t89206600\t89277100\tLow Mappability\nchr2\t89345700\t89350400\tHigh Signal Region\nchr2\t89761200\t89775100\tHigh Signal Region\nchr2\t89856400\t89920100\tHigh Signal Region\nchr2\t90127200\t90132700\tHigh Signal Region\nchr2\t90157100\t90249100\tHigh Signal Region\nchr2\t90273200\t90279100\tHigh Signal Region\nchr2\t90309300\t90396100\tHigh Signal Region\nchr2\t92092600\t92094700\tHigh Signal Region\nchr2\t92167200\t92169100\tHigh Signal Region\nchr2\t93824700\t93850200\tHigh Signal Region\nchr2\t94602800\t94607800\tLow Mappability\nchr2\t94633900\t94656500\tHigh Signal Region\nchr2\t94801000\t94809400\tLow Mappability\nchr2\t94852800\t94891200\tHigh Signal Region\nchr2\t95064700\t95093500\tLow Mappability\nchr2\t95148000\t95167800\tHigh Signal Region\nchr2\t95215900\t95320600\tHigh Signal Region\nchr2\t95414700\t95420600\tHigh Signal Region\nchr2\t95536400\t95538400\tLow Mappability\nchr2\t95647900\t95654300\tHigh Signal Region\nchr2\t95794500\t95799200\tHigh Signal Region\nchr2\t95929300\t95934400\tHigh Signal Region\nchr2\t96191400\t96208900\tHigh Signal Region\nchr2\t96547800\t96566800\tLow Mappability\nchr2\t96954700\t96977300\tHigh Signal Region\nchr2\t97021000\t97034600\tHigh Signal Region\nchr2\t97308000\t97327600\tHigh Signal Region\nchr2\t97671600\t97686300\tHigh Signal Region\nchr2\t97760700\t97765800\tHigh Signal Region\nchr2\t97872400\t97958200\tHigh Signal Region\nchr2\t98361700\t98449600\tHigh Signal Region\nchr2\t98659400\t98668200\tHigh Signal Region\nchr2\t98796500\t98801900\tHigh Signal Region\nchr2\t99020000\t99057500\tHigh Signal Region\nchr2\t99300200\t99320300\tHigh Signal Region\nchr2\t99944600\t99970200\tHigh Signal Region\nchr2\t100112000\t100114300\tHigh Signal Region\nchr2\t100223900\t100238300\tHigh Signal Region\nchr2\t100418400\t100777900\tLow Mappability\nchr2\t101127200\t101153600\tLow Mappability\nchr2\t101313100\t101350600\tHigh Signal Region\nchr2\t102828400\t102830400\tHigh Signal Region\nchr2\t103231300\t103232300\tHigh Signal Region\nchr2\t103852300\t103872800\tHigh Signal Region\nchr2\t104684900\t104697300\tHigh Signal Region\nchr2\t105249300\t105259000\tHigh Signal Region\nchr2\t105539300\t105563200\tLow Mappability\nchr2\t105825900\t105865100\tHigh Signal Region\nchr2\t106555100\t106569300\tHigh Signal Region\nchr2\t107134100\t107140900\tHigh Signal Region\nchr2\t107593900\t107601200\tLow Mappability\nchr2\t107710100\t107712400\tHigh Signal Region\nchr2\t108608600\t108614000\tHigh Signal Region\nchr2\t108945100\t108972800\tHigh Signal Region\nchr2\t109629400\t109636000\tHigh Signal Region\nchr2\t110016800\t110025500\tHigh Signal Region\nchr2\t110091100\t110128700\tHigh Signal Region\nchr2\t110157100\t110163300\tHigh Signal Region\nchr2\t110292700\t110294600\tHigh Signal Region\nchr2\t110545800\t110583400\tHigh Signal Region\nchr2\t110752400\t110780100\tHigh Signal Region\nchr2\t111007400\t111018600\tHigh Signal Region\nchr2\t111042000\t111046600\tHigh Signal Region\nchr2\t111172700\t111179800\tHigh Signal Region\nchr2\t111281500\t111287900\tLow Mappability\nchr2\t111545600\t111553300\tLow Mappability\nchr2\t111716900\t111722900\tHigh Signal Region\nchr2\t111844900\t111866400\tHigh Signal Region\nchr2\t111890900\t111898900\tHigh Signal Region\nchr2\t112053900\t112086000\tHigh Signal Region\nchr2\t112319700\t112326200\tLow Mappability\nchr2\t112522900\t112570500\tHigh Signal Region\nchr2\t112602800\t112605100\tHigh Signal Region\nchr2\t112701400\t112707900\tHigh Signal Region\nchr2\t113095800\t113102400\tLow Mappability\nchr2\t113330900\t113333000\tLow Mappability\nchr2\t113518400\t113524900\tLow Mappability\nchr2\t113564300\t113565700\tHigh Signal Region\nchr2\t113659300\t113673200\tHigh Signal Region\nchr2\t114180800\t114187400\tLow Mappability\nchr2\t114242400\t114244000\tHigh Signal Region\nchr2\t114469200\t114504000\tHigh Signal Region\nchr2\t116454300\t116524000\tHigh Signal Region\nchr2\t117829600\t117835500\tHigh Signal Region\nchr2\t118017700\t118020200\tHigh Signal Region\nchr2\t120608600\t120650200\tHigh Signal Region\nchr2\t120810300\t120821000\tHigh Signal Region\nchr2\t121435600\t121523600\tHigh Signal Region\nchr2\t121938800\t121957600\tHigh Signal Region\nchr2\t122680400\t122683200\tHigh Signal Region\nchr2\t123288000\t123294300\tLow Mappability\nchr2\t123496800\t123525300\tHigh Signal Region\nchr2\t123785200\t123790700\tHigh Signal Region\nchr2\t124002700\t124004600\tHigh Signal Region\nchr2\t124798800\t124835800\tHigh Signal Region\nchr2\t125625000\t125635900\tLow Mappability\nchr2\t126217400\t126263800\tHigh Signal Region\nchr2\t126445400\t126447400\tLow Mappability\nchr2\t126964900\t126972100\tLow Mappability\nchr2\t127720400\t127734000\tLow Mappability\nchr2\t128050800\t128053200\tHigh Signal Region\nchr2\t128480400\t128486900\tLow Mappability\nchr2\t128772500\t128774500\tLow Mappability\nchr2\t129499400\t129523400\tHigh Signal Region\nchr2\t129602700\t129613700\tLow Mappability\nchr2\t131791800\t131793800\tHigh Signal Region\nchr2\t131908300\t131931100\tLow Mappability\nchr2\t131963900\t131983700\tHigh Signal Region\nchr2\t132885700\t132890400\tHigh Signal Region\nchr2\t132952400\t132954500\tLow Mappability\nchr2\t133053200\t133083400\tHigh Signal Region\nchr2\t133239300\t133261800\tHigh Signal Region\nchr2\t133934000\t133937500\tHigh Signal Region\nchr2\t134560100\t134577900\tHigh Signal Region\nchr2\t134661800\t134673000\tHigh Signal Region\nchr2\t134746600\t134751100\tHigh Signal Region\nchr2\t135146800\t135151900\tHigh Signal Region\nchr2\t135987600\t135989700\tHigh Signal Region\nchr2\t136234300\t136286800\tLow Mappability\nchr2\t137028200\t137037000\tHigh Signal Region\nchr2\t137345900\t137369900\tHigh Signal Region\nchr2\t137394500\t137405600\tHigh Signal Region\nchr2\t137640000\t137642300\tHigh Signal Region\nchr2\t137890200\t137895000\tHigh Signal Region\nchr2\t138035000\t138056400\tLow Mappability\nchr2\t138573700\t138580400\tHigh Signal Region\nchr2\t138621500\t138624200\tHigh Signal Region\nchr2\t138833600\t138853100\tHigh Signal Region\nchr2\t138904300\t138935000\tHigh Signal Region\nchr2\t139433200\t139476200\tHigh Signal Region\nchr2\t140345800\t140352400\tLow Mappability\nchr2\t142197000\t142204400\tLow Mappability\nchr2\t142464200\t142483300\tLow Mappability\nchr2\t142789100\t142795600\tLow Mappability\nchr2\t143275500\t143290300\tHigh Signal Region\nchr2\t143725900\t143764700\tHigh Signal Region\nchr2\t144627800\t144636700\tLow Mappability\nchr2\t144975200\t144977100\tHigh Signal Region\nchr2\t145001300\t145003200\tHigh Signal Region\nchr2\t145118300\t145146300\tLow Mappability\nchr2\t145236800\t145242600\tLow Mappability\nchr2\t145625100\t145630800\tLow Mappability\nchr2\t145732700\t145734600\tHigh Signal Region\nchr2\t146135700\t146176900\tHigh Signal Region\nchr2\t146995700\t147013200\tLow Mappability\nchr2\t147675300\t147677500\tHigh Signal Region\nchr2\t147864800\t147871300\tHigh Signal Region\nchr2\t147918800\t147925100\tLow Mappability\nchr2\t148410500\t148416000\tLow Mappability\nchr2\t148459900\t148473800\tHigh Signal Region\nchr2\t148612700\t148620200\tLow Mappability\nchr2\t148939300\t148984200\tHigh Signal Region\nchr2\t149049800\t149056000\tHigh Signal Region\nchr2\t149269400\t149292700\tHigh Signal Region\nchr2\t150413500\t150452500\tHigh Signal Region\nchr2\t150728300\t150749700\tLow Mappability\nchr2\t151029700\t151385300\tHigh Signal Region\nchr2\t151408800\t151496700\tHigh Signal Region\nchr2\t152157000\t152159000\tLow Mappability\nchr2\t152206800\t152227500\tHigh Signal Region\nchr2\t152263400\t152269900\tLow Mappability\nchr2\t153674800\t153693100\tLow Mappability\nchr2\t154174200\t154180000\tHigh Signal Region\nchr2\t154353800\t154359700\tLow Mappability\nchr2\t155016300\t155051500\tHigh Signal Region\nchr2\t155235400\t155258100\tHigh Signal Region\nchr2\t156185100\t156214400\tLow Mappability\nchr2\t157566000\t157655300\tLow Mappability\nchr2\t157833200\t157835600\tHigh Signal Region\nchr2\t158286300\t158292800\tHigh Signal Region\nchr2\t159455200\t159469500\tHigh Signal Region\nchr2\t160620300\t160638500\tHigh Signal Region\nchr2\t161368800\t161376200\tHigh Signal Region\nchr2\t161984900\t161990900\tHigh Signal Region\nchr2\t162369100\t162376700\tHigh Signal Region\nchr2\t162594500\t162602700\tHigh Signal Region\nchr2\t162843800\t162847600\tHigh Signal Region\nchr2\t163519100\t163533100\tLow Mappability\nchr2\t163644500\t163655100\tHigh Signal Region\nchr2\t163788900\t163796100\tLow Mappability\nchr2\t163833800\t163849200\tLow Mappability\nchr2\t163958100\t163963000\tLow Mappability\nchr2\t164201000\t164202700\tHigh Signal Region\nchr2\t165477300\t165529900\tLow Mappability\nchr2\t165675100\t165679500\tLow Mappability\nchr2\t165848700\t165953000\tLow Mappability\nchr2\t166530600\t166535100\tLow Mappability\nchr2\t166780500\t166832200\tLow Mappability\nchr2\t167269400\t167291100\tHigh Signal Region\nchr2\t167407900\t167423000\tLow Mappability\nchr2\t170315100\t170320000\tHigh Signal Region\nchr2\t170503800\t170509800\tHigh Signal Region\nchr2\t171814300\t171816700\tHigh Signal Region\nchr2\t171912800\t171932200\tLow Mappability\nchr2\t172007100\t172014300\tHigh Signal Region\nchr2\t172743600\t172751100\tLow Mappability\nchr2\t173098700\t173101000\tLow Mappability\nchr2\t173706700\t173708800\tHigh Signal Region\nchr2\t174961800\t176745500\tHigh Signal Region\nchr2\t176767100\t177166600\tHigh Signal Region\nchr2\t177232400\t177490200\tHigh Signal Region\nchr2\t177526700\t177841000\tHigh Signal Region\nchr2\t178775000\t178794400\tHigh Signal Region\nchr2\t180025600\t180093500\tLow Mappability\nchr2\t181169900\t181188000\tLow Mappability\nchr2\t181285900\t181298800\tHigh Signal Region\nchr2\t181739800\t181745800\tHigh Signal Region\nchr2\t181885000\t181933400\tHigh Signal Region\nchr2\t182003800\t182113200\tHigh Signal Region\nchr3\t0\t3052500\tHigh Signal Region\nchr3\t3084100\t3098300\tHigh Signal Region\nchr3\t3123200\t3150800\tHigh Signal Region\nchr3\t3443300\t3493700\tHigh Signal Region\nchr3\t4698100\t4725500\tHigh Signal Region\nchr3\t5517700\t5525000\tLow Mappability\nchr3\t5859400\t5863500\tHigh Signal Region\nchr3\t6115100\t6117100\tHigh Signal Region\nchr3\t6601900\t6627400\tHigh Signal Region\nchr3\t6900700\t6916400\tHigh Signal Region\nchr3\t6941100\t6946600\tHigh Signal Region\nchr3\t7178300\t7223900\tHigh Signal Region\nchr3\t7477600\t7482500\tHigh Signal Region\nchr3\t7910300\t7916600\tHigh Signal Region\nchr3\t8225200\t8247500\tHigh Signal Region\nchr3\t8574000\t8589900\tHigh Signal Region\nchr3\t8815300\t8838700\tHigh Signal Region\nchr3\t9091900\t9096900\tLow Mappability\nchr3\t9777500\t9778500\tHigh Signal Region\nchr3\t9904100\t9910700\tHigh Signal Region\nchr3\t9952100\t9967100\tHigh Signal Region\nchr3\t10453800\t10464500\tHigh Signal Region\nchr3\t10961700\t10971700\tHigh Signal Region\nchr3\t11050200\t11070500\tHigh Signal Region\nchr3\t11120700\t11143300\tHigh Signal Region\nchr3\t11518700\t11524700\tHigh Signal Region\nchr3\t11779200\t11806000\tHigh Signal Region\nchr3\t11933500\t11938400\tHigh Signal Region\nchr3\t11961500\t11973100\tHigh Signal Region\nchr3\t12107500\t12131400\tHigh Signal Region\nchr3\t12221200\t12262000\tHigh Signal Region\nchr3\t12336000\t12339700\tHigh Signal Region\nchr3\t12814500\t12857800\tLow Mappability\nchr3\t12906200\t12907300\tHigh Signal Region\nchr3\t13219400\t13222800\tHigh Signal Region\nchr3\t13821100\t13826600\tLow Mappability\nchr3\t13965800\t13972000\tHigh Signal Region\nchr3\t14272100\t14336300\tHigh Signal Region\nchr3\t14449600\t14478500\tHigh Signal Region\nchr3\t14593200\t14597400\tHigh Signal Region\nchr3\t14668900\t14744700\tHigh Signal Region\nchr3\t15028800\t15045100\tHigh Signal Region\nchr3\t15079500\t15087400\tHigh Signal Region\nchr3\t15451600\t15872400\tHigh Signal Region\nchr3\t15964200\t15967200\tHigh Signal Region\nchr3\t16351400\t16357100\tHigh Signal Region\nchr3\t16626000\t16633700\tHigh Signal Region\nchr3\t16995700\t17021400\tHigh Signal Region\nchr3\t17419700\t17447600\tHigh Signal Region\nchr3\t17679600\t17682100\tHigh Signal Region\nchr3\t17954200\t17997400\tHigh Signal Region\nchr3\t18379800\t18395100\tHigh Signal Region\nchr3\t18432100\t18437500\tHigh Signal Region\nchr3\t18966900\t18983600\tHigh Signal Region\nchr3\t19357600\t19359300\tHigh Signal Region\nchr3\t19594900\t19601100\tHigh Signal Region\nchr3\t19917700\t19940300\tHigh Signal Region\nchr3\t21247500\t21250200\tHigh Signal Region\nchr3\t21317800\t21324600\tHigh Signal Region\nchr3\t21383700\t21389000\tHigh Signal Region\nchr3\t21512900\t21519300\tHigh Signal Region\nchr3\t21661800\t21663700\tLow Mappability\nchr3\t21685300\t21709500\tHigh Signal Region\nchr3\t22069200\t22070500\tHigh Signal Region\nchr3\t22240800\t22250100\tHigh Signal Region\nchr3\t22362000\t22377000\tHigh Signal Region\nchr3\t22517600\t22521100\tHigh Signal Region\nchr3\t22612100\t22759200\tHigh Signal Region\nchr3\t22933800\t23015000\tHigh Signal Region\nchr3\t23077300\t23099800\tHigh Signal Region\nchr3\t23173700\t23180900\tLow Mappability\nchr3\t23302200\t23321100\tHigh Signal Region\nchr3\t23353500\t23360000\tHigh Signal Region\nchr3\t23463300\t23468200\tHigh Signal Region\nchr3\t23579500\t23584900\tHigh Signal Region\nchr3\t23841700\t23843800\tLow Mappability\nchr3\t24624400\t24627900\tHigh Signal Region\nchr3\t24655200\t24661300\tHigh Signal Region\nchr3\t25210800\t25228800\tLow Mappability\nchr3\t25277500\t25310400\tHigh Signal Region\nchr3\t25416900\t25421600\tLow Mappability\nchr3\t25472900\t25478900\tHigh Signal Region\nchr3\t26089400\t26113400\tHigh Signal Region\nchr3\t26346800\t26369700\tHigh Signal Region\nchr3\t26724600\t26737000\tHigh Signal Region\nchr3\t26944500\t26950800\tHigh Signal Region\nchr3\t27010100\t27023300\tHigh Signal Region\nchr3\t27309300\t27319800\tLow Mappability\nchr3\t28198300\t28201300\tLow Mappability\nchr3\t28513900\t28535500\tHigh Signal Region\nchr3\t28983500\t29014200\tHigh Signal Region\nchr3\t29461500\t29492300\tHigh Signal Region\nchr3\t29675900\t29680600\tHigh Signal Region\nchr3\t31176300\t31188900\tLow Mappability\nchr3\t31340700\t31364500\tLow Mappability\nchr3\t31651800\t31680100\tHigh Signal Region\nchr3\t31819800\t31826900\tHigh Signal Region\nchr3\t33696500\t33708400\tHigh Signal Region\nchr3\t33768300\t33798500\tHigh Signal Region\nchr3\t33930000\t33948800\tLow Mappability\nchr3\t34516200\t34518200\tHigh Signal Region\nchr3\t35285400\t35292700\tHigh Signal Region\nchr3\t35707000\t35713500\tLow Mappability\nchr3\t35743300\t35744600\tHigh Signal Region\nchr3\t36106500\t36109400\tHigh Signal Region\nchr3\t36285400\t36291100\tHigh Signal Region\nchr3\t36847300\t36853900\tHigh Signal Region\nchr3\t39026800\t39030900\tHigh Signal Region\nchr3\t39183300\t39189800\tHigh Signal Region\nchr3\t40151300\t40157700\tHigh Signal Region\nchr3\t40347600\t40352600\tHigh Signal Region\nchr3\t40549300\t40651700\tHigh Signal Region\nchr3\t41871900\t41887800\tHigh Signal Region\nchr3\t41993500\t41999500\tHigh Signal Region\nchr3\t42170000\t42187300\tHigh Signal Region\nchr3\t42682100\t42722800\tHigh Signal Region\nchr3\t42820200\t42827400\tHigh Signal Region\nchr3\t43108100\t43197200\tHigh Signal Region\nchr3\t43466400\t43492100\tHigh Signal Region\nchr3\t43538900\t43557700\tHigh Signal Region\nchr3\t44185900\t44191600\tHigh Signal Region\nchr3\t44241200\t44260000\tHigh Signal Region\nchr3\t44401500\t44407500\tHigh Signal Region\nchr3\t44559600\t44565200\tHigh Signal Region\nchr3\t44884400\t44890700\tHigh Signal Region\nchr3\t45579200\t45591900\tHigh Signal Region\nchr3\t45848500\t45863400\tLow Mappability\nchr3\t45986000\t45990700\tHigh Signal Region\nchr3\t46141000\t46148200\tHigh Signal Region\nchr3\t46338200\t46340300\tLow Mappability\nchr3\t46735000\t46741900\tHigh Signal Region\nchr3\t46795400\t46805400\tHigh Signal Region\nchr3\t46910900\t46936200\tHigh Signal Region\nchr3\t47592800\t47598000\tHigh Signal Region\nchr3\t47798300\t47799600\tHigh Signal Region\nchr3\t47966600\t47968700\tHigh Signal Region\nchr3\t48437800\t48462000\tHigh Signal Region\nchr3\t49443600\t49482800\tHigh Signal Region\nchr3\t49727200\t49734400\tHigh Signal Region\nchr3\t50464900\t50474400\tHigh Signal Region\nchr3\t50763700\t50814900\tHigh Signal Region\nchr3\t50957300\t50963000\tHigh Signal Region\nchr3\t51233600\t51245400\tLow Mappability\nchr3\t51616000\t51623700\tLow Mappability\nchr3\t51765300\t51784900\tHigh Signal Region\nchr3\t52230000\t52233400\tHigh Signal Region\nchr3\t53426900\t53431000\tHigh Signal Region\nchr3\t54849100\t54874300\tLow Mappability\nchr3\t56069700\t56075200\tHigh Signal Region\nchr3\t56210900\t56215900\tHigh Signal Region\nchr3\t56513600\t56576700\tHigh Signal Region\nchr3\t56903800\t56943000\tHigh Signal Region\nchr3\t57059400\t57070200\tHigh Signal Region\nchr3\t57349800\t57379400\tHigh Signal Region\nchr3\t58051100\t58081600\tLow Mappability\nchr3\t59370700\t59412200\tHigh Signal Region\nchr3\t59565300\t59632700\tHigh Signal Region\nchr3\t59684600\t59689200\tHigh Signal Region\nchr3\t59791800\t59804200\tLow Mappability\nchr3\t59887400\t59889300\tHigh Signal Region\nchr3\t59919200\t59921100\tHigh Signal Region\nchr3\t60044300\t60046800\tHigh Signal Region\nchr3\t60489700\t60495200\tLow Mappability\nchr3\t61150800\t61177900\tHigh Signal Region\nchr3\t61260700\t61275000\tLow Mappability\nchr3\t61495400\t61499700\tHigh Signal Region\nchr3\t61672300\t61678300\tHigh Signal Region\nchr3\t61707600\t61726600\tLow Mappability\nchr3\t61853900\t61858900\tHigh Signal Region\nchr3\t62032400\t62038600\tHigh Signal Region\nchr3\t62108300\t62160100\tHigh Signal Region\nchr3\t62356900\t62367700\tHigh Signal Region\nchr3\t62543000\t62549200\tHigh Signal Region\nchr3\t62873000\t62879300\tHigh Signal Region\nchr3\t63515500\t63530100\tHigh Signal Region\nchr3\t63590100\t63591500\tHigh Signal Region\nchr3\t64171000\t64172900\tHigh Signal Region\nchr3\t64237900\t64245700\tHigh Signal Region\nchr3\t64453100\t64512800\tHigh Signal Region\nchr3\t64609600\t64665300\tLow Mappability\nchr3\t64697900\t64730500\tHigh Signal Region\nchr3\t67027900\t67054100\tHigh Signal Region\nchr3\t67262400\t67264000\tHigh Signal Region\nchr3\t67411100\t67419400\tHigh Signal Region\nchr3\t67747300\t67752800\tHigh Signal Region\nchr3\t67786800\t67793600\tHigh Signal Region\nchr3\t68114300\t68119700\tLow Mappability\nchr3\t68519400\t68525100\tHigh Signal Region\nchr3\t69228600\t69230500\tHigh Signal Region\nchr3\t69848400\t69854900\tHigh Signal Region\nchr3\t69944400\t69949800\tHigh Signal Region\nchr3\t71117300\t71122800\tHigh Signal Region\nchr3\t71369600\t71447800\tHigh Signal Region\nchr3\t72273600\t72293700\tHigh Signal Region\nchr3\t72698100\t72704800\tHigh Signal Region\nchr3\t73088300\t73098500\tHigh Signal Region\nchr3\t73733100\t73738500\tLow Mappability\nchr3\t74583300\t74598400\tLow Mappability\nchr3\t74865000\t74881800\tHigh Signal Region\nchr3\t75348300\t75378700\tLow Mappability\nchr3\t75409000\t75424100\tHigh Signal Region\nchr3\t76598800\t76604700\tHigh Signal Region\nchr3\t76886600\t76892900\tLow Mappability\nchr3\t77597400\t77604300\tLow Mappability\nchr3\t77667400\t77711400\tHigh Signal Region\nchr3\t77926800\t77931400\tHigh Signal Region\nchr3\t78281900\t78283900\tLow Mappability\nchr3\t79012700\t79014900\tHigh Signal Region\nchr3\t79046300\t79052800\tLow Mappability\nchr3\t79763800\t79780000\tHigh Signal Region\nchr3\t79959500\t79965700\tHigh Signal Region\nchr3\t80465400\t80472000\tHigh Signal Region\nchr3\t82283300\t82288700\tLow Mappability\nchr3\t82462100\t82508600\tLow Mappability\nchr3\t82589000\t82616700\tLow Mappability\nchr3\t82921400\t82924800\tHigh Signal Region\nchr3\t83123200\t83125100\tHigh Signal Region\nchr3\t83330900\t83343400\tHigh Signal Region\nchr3\t83845100\t83867000\tHigh Signal Region\nchr3\t84142200\t84149700\tLow Mappability\nchr3\t84359000\t84366300\tLow Mappability\nchr3\t85305200\t85326800\tLow Mappability\nchr3\t85622200\t85629500\tLow Mappability\nchr3\t87424200\t87426100\tHigh Signal Region\nchr3\t87469300\t87474600\tHigh Signal Region\nchr3\t88044000\t88066500\tHigh Signal Region\nchr3\t88666500\t88673500\tLow Mappability\nchr3\t88716700\t88873000\tLow Mappability\nchr3\t90761500\t90810400\tHigh Signal Region\nchr3\t90991100\t90996800\tLow Mappability\nchr3\t91856700\t91898200\tHigh Signal Region\nchr3\t92185400\t92291300\tHigh Signal Region\nchr3\t93059200\t93107000\tHigh Signal Region\nchr3\t93168500\t93172800\tHigh Signal Region\nchr3\t93203900\t93229100\tHigh Signal Region\nchr3\t93323700\t93331700\tLow Mappability\nchr3\t93860300\t94093700\tHigh Signal Region\nchr3\t94136200\t94152300\tHigh Signal Region\nchr3\t94658300\t94665700\tLow Mappability\nchr3\t94690000\t94730800\tHigh Signal Region\nchr3\t94757600\t94765200\tLow Mappability\nchr3\t96043600\t96058900\tHigh Signal Region\nchr3\t96196200\t96288300\tHigh Signal Region\nchr3\t96313200\t96388900\tLow Mappability\nchr3\t96446800\t96463800\tLow Mappability\nchr3\t96485600\t96514300\tHigh Signal Region\nchr3\t96840000\t96863800\tHigh Signal Region\nchr3\t97245200\t97251500\tHigh Signal Region\nchr3\t98396100\t98411400\tHigh Signal Region\nchr3\t98443100\t98597600\tLow Mappability\nchr3\t98709300\t98778900\tHigh Signal Region\nchr3\t98986000\t99034100\tHigh Signal Region\nchr3\t99406000\t99434100\tHigh Signal Region\nchr3\t99882900\t99908100\tHigh Signal Region\nchr3\t99980200\t99982200\tHigh Signal Region\nchr3\t100315500\t100330900\tHigh Signal Region\nchr3\t100484400\t100486300\tHigh Signal Region\nchr3\t102813400\t102839300\tHigh Signal Region\nchr3\t102983600\t102989900\tHigh Signal Region\nchr3\t103134600\t103136000\tHigh Signal Region\nchr3\t103427600\t103447900\tHigh Signal Region\nchr3\t103555000\t103557000\tLow Mappability\nchr3\t104116800\t104123100\tHigh Signal Region\nchr3\t104194200\t104198800\tHigh Signal Region\nchr3\t104588100\t104595500\tLow Mappability\nchr3\t105028200\t105030500\tHigh Signal Region\nchr3\t106118500\t106311800\tHigh Signal Region\nchr3\t106777900\t106779700\tHigh Signal Region\nchr3\t109258500\t109277300\tHigh Signal Region\nchr3\t109458000\t109462700\tHigh Signal Region\nchr3\t110319800\t110325700\tHigh Signal Region\nchr3\t110416300\t110421800\tHigh Signal Region\nchr3\t111256100\t111268600\tHigh Signal Region\nchr3\t111578400\t111605200\tLow Mappability\nchr3\t111794100\t111799000\tLow Mappability\nchr3\t111830400\t111836300\tHigh Signal Region\nchr3\t112274500\t112287300\tHigh Signal Region\nchr3\t112315500\t112337400\tHigh Signal Region\nchr3\t112561900\t112586900\tHigh Signal Region\nchr3\t112863500\t112869300\tHigh Signal Region\nchr3\t112913800\t112918000\tHigh Signal Region\nchr3\t113186300\t113189100\tHigh Signal Region\nchr3\t113250900\t113527800\tHigh Signal Region\nchr3\t113709900\t113719000\tHigh Signal Region\nchr3\t113742300\t113748300\tHigh Signal Region\nchr3\t114272600\t114279400\tHigh Signal Region\nchr3\t114472100\t114499300\tLow Mappability\nchr3\t114587900\t114595900\tHigh Signal Region\nchr3\t114976700\t114982800\tHigh Signal Region\nchr3\t115020700\t115027100\tLow Mappability\nchr3\t115367700\t115372200\tLow Mappability\nchr3\t115905900\t115922900\tHigh Signal Region\nchr3\t116817400\t116843900\tLow Mappability\nchr3\t117267200\t117292400\tHigh Signal Region\nchr3\t117379100\t117386400\tLow Mappability\nchr3\t118055100\t118060000\tHigh Signal Region\nchr3\t119211800\t119212900\tHigh Signal Region\nchr3\t120735000\t120742200\tHigh Signal Region\nchr3\t120825200\t120851500\tHigh Signal Region\nchr3\t121248900\t121250900\tHigh Signal Region\nchr3\t121694400\t121696100\tHigh Signal Region\nchr3\t122294000\t122329300\tHigh Signal Region\nchr3\t122654100\t122657300\tHigh Signal Region\nchr3\t122804300\t122806600\tHigh Signal Region\nchr3\t123471600\t123476200\tLow Mappability\nchr3\t123729200\t123743200\tHigh Signal Region\nchr3\t123924800\t123957700\tHigh Signal Region\nchr3\t124282300\t124288300\tHigh Signal Region\nchr3\t125902800\t125908900\tHigh Signal Region\nchr3\t126127300\t126136000\tLow Mappability\nchr3\t126905300\t126910600\tHigh Signal Region\nchr3\t127522400\t127523700\tLow Mappability\nchr3\t127771600\t127780600\tHigh Signal Region\nchr3\t128203600\t128211000\tHigh Signal Region\nchr3\t128440100\t128446100\tHigh Signal Region\nchr3\t128935800\t128937700\tHigh Signal Region\nchr3\t129020900\t129032100\tHigh Signal Region\nchr3\t129393000\t129394900\tHigh Signal Region\nchr3\t133123600\t133130800\tLow Mappability\nchr3\t133566400\t133568700\tHigh Signal Region\nchr3\t133636000\t133642800\tHigh Signal Region\nchr3\t133837100\t133859400\tHigh Signal Region\nchr3\t134007400\t134026700\tLow Mappability\nchr3\t134685700\t134690700\tHigh Signal Region\nchr3\t134862500\t134888400\tHigh Signal Region\nchr3\t135148300\t135163000\tHigh Signal Region\nchr3\t136173700\t136181000\tLow Mappability\nchr3\t137407500\t137413500\tHigh Signal Region\nchr3\t137469200\t137470300\tHigh Signal Region\nchr3\t138200900\t138207900\tHigh Signal Region\nchr3\t139365700\t139417700\tHigh Signal Region\nchr3\t140376900\t140384200\tLow Mappability\nchr3\t142190700\t142192800\tHigh Signal Region\nchr3\t142513000\t142517200\tHigh Signal Region\nchr3\t143840800\t143847000\tHigh Signal Region\nchr3\t144030200\t144036300\tHigh Signal Region\nchr3\t144655600\t144660600\tHigh Signal Region\nchr3\t145040500\t145061800\tHigh Signal Region\nchr3\t145109000\t145114400\tLow Mappability\nchr3\t145188100\t145190400\tHigh Signal Region\nchr3\t145301600\t145303100\tHigh Signal Region\nchr3\t146073300\t146102400\tHigh Signal Region\nchr3\t146358800\t146362600\tHigh Signal Region\nchr3\t146476200\t146479000\tHigh Signal Region\nchr3\t146918900\t146924200\tHigh Signal Region\nchr3\t147107400\t147113000\tHigh Signal Region\nchr3\t147769500\t147781800\tHigh Signal Region\nchr3\t147874500\t147877600\tHigh Signal Region\nchr3\t148704800\t148716900\tHigh Signal Region\nchr3\t148750100\t148757400\tLow Mappability\nchr3\t148797800\t148799700\tHigh Signal Region\nchr3\t149051500\t149053800\tHigh Signal Region\nchr3\t150120900\t150123800\tHigh Signal Region\nchr3\t150336900\t150341400\tLow Mappability\nchr3\t151028900\t151031200\tHigh Signal Region\nchr3\t151657500\t151679800\tHigh Signal Region\nchr3\t152313800\t152332200\tHigh Signal Region\nchr3\t152700700\t152702700\tHigh Signal Region\nchr3\t153090100\t153109400\tHigh Signal Region\nchr3\t154640300\t154646700\tHigh Signal Region\nchr3\t154931700\t154932800\tHigh Signal Region\nchr3\t155515800\t155517600\tHigh Signal Region\nchr3\t155765900\t155771900\tHigh Signal Region\nchr3\t156256900\t156262800\tLow Mappability\nchr3\t156285600\t156322500\tHigh Signal Region\nchr3\t156799400\t156804900\tLow Mappability\nchr3\t157646900\t157678300\tHigh Signal Region\nchr3\t157946200\t157969400\tHigh Signal Region\nchr3\t158095300\t158119200\tHigh Signal Region\nchr3\t158698600\t158756800\tHigh Signal Region\nchr3\t159165900\t159179700\tHigh Signal Region\nchr3\t159225800\t159239300\tLow Mappability\nchr3\t159478300\t159479700\tHigh Signal Region\nchr3\t159748800\t159826500\tHigh Signal Region\nchr3\t159938500\t160039600\tHigh Signal Region\nchr4\t0\t3114800\tHigh Signal Region\nchr4\t3139700\t3333100\tHigh Signal Region\nchr4\t18476200\t18498400\tHigh Signal Region\nchr4\t20168700\t20213200\tHigh Signal Region\nchr4\t20804100\t20808300\tHigh Signal Region\nchr4\t20982300\t20983700\tHigh Signal Region\nchr4\t21281300\t21287700\tHigh Signal Region\nchr4\t22535900\t22542300\tHigh Signal Region\nchr4\t24193400\t24201100\tHigh Signal Region\nchr4\t25471300\t25473200\tHigh Signal Region\nchr4\t28175900\t28177900\tHigh Signal Region\nchr4\t31353200\t31355200\tHigh Signal Region\nchr4\t34934800\t34936700\tHigh Signal Region\nchr4\t35042700\t35048900\tHigh Signal Region\nchr4\t38305900\t38322000\tHigh Signal Region\nchr4\t57979700\t57981800\tHigh Signal Region\nchr4\t64454600\t64499000\tHigh Signal Region\nchr4\t68427300\t68447900\tHigh Signal Region\nchr4\t70367200\t70379200\tHigh Signal Region\nchr4\t73196300\t73209300\tHigh Signal Region\nchr4\t80001800\t80004900\tHigh Signal Region\nchr4\t83536900\t83541900\tHigh Signal Region\nchr4\t90725600\t90727500\tHigh Signal Region\nchr4\t92230800\t92236500\tHigh Signal Region\nchr4\t93843500\t93853100\tHigh Signal Region\nchr4\t99380500\t99382400\tHigh Signal Region\nchr4\t110469700\t110505300\tHigh Signal Region\nchr4\t118546100\t118549600\tHigh Signal Region\nchr4\t131222500\t131229300\tHigh Signal Region\nchr4\t145404200\t147840400\tHigh Signal Region\nchr4\t149809200\t149811700\tHigh Signal Region\nchr4\t153152100\t153154100\tHigh Signal Region\nchr4\t156256000\t156508100\tHigh Signal Region\nchr5\t3175400\t3186000\tHigh Signal Region\nchr5\t12489500\t12490600\tHigh Signal Region\nchr5\t14899000\t15726800\tHigh Signal Region\nchr5\t17466700\t17481500\tHigh Signal Region\nchr5\t36629400\t36662500\tHigh Signal Region\nchr5\t46434800\t46436700\tHigh Signal Region\nchr5\t49722200\t49755700\tHigh Signal Region\nchr5\t60041900\t60043900\tLow Mappability\nchr5\t80499900\t80501900\tHigh Signal Region\nchr5\t93288700\t93351800\tHigh Signal Region\nchr5\t106126300\t106177800\tHigh Signal Region\nchr5\t110063700\t110075500\tHigh Signal Region\nchr5\t114921500\t114923500\tHigh Signal Region\nchr5\t137148800\t137153800\tHigh Signal Region\nchr5\t146260000\t146262300\tHigh Signal Region\nchr5\t151733600\t151834600\tHigh Signal Region\nchr6\t0\t3255700\tHigh Signal Region\nchr6\t3280700\t3340300\tHigh Signal Region\nchr6\t4922900\t4925100\tHigh Signal Region\nchr6\t5608000\t5657900\tHigh Signal Region\nchr6\t5704400\t5706800\tHigh Signal Region\nchr6\t6400000\t6442800\tHigh Signal Region\nchr6\t6700000\t6727600\tHigh Signal Region\nchr6\t8729200\t8731100\tHigh Signal Region\nchr6\t8906700\t8932300\tHigh Signal Region\nchr6\t9519200\t9529100\tHigh Signal Region\nchr6\t9580600\t9610100\tHigh Signal Region\nchr6\t9646900\t9663400\tHigh Signal Region\nchr6\t9720400\t9733100\tHigh Signal Region\nchr6\t9889000\t9891100\tHigh Signal Region\nchr6\t10228400\t10269900\tHigh Signal Region\nchr6\t10559100\t10588400\tHigh Signal Region\nchr6\t10623400\t10633900\tHigh Signal Region\nchr6\t11251100\t11256800\tHigh Signal Region\nchr6\t11406400\t11457900\tHigh Signal Region\nchr6\t11813900\t11897100\tHigh Signal Region\nchr6\t12671100\t12680300\tHigh Signal Region\nchr6\t13390500\t13394900\tHigh Signal Region\nchr6\t13700500\t13743100\tHigh Signal Region\nchr6\t14085000\t14092300\tLow Mappability\nchr6\t14793800\t14805500\tHigh Signal Region\nchr6\t14929200\t14935100\tHigh Signal Region\nchr6\t16299700\t16310100\tHigh Signal Region\nchr6\t16922600\t16924800\tHigh Signal Region\nchr6\t17004600\t17042000\tHigh Signal Region\nchr6\t17391200\t17397900\tHigh Signal Region\nchr6\t17981700\t17983400\tHigh Signal Region\nchr6\t18264800\t18267200\tHigh Signal Region\nchr6\t18836700\t18848600\tHigh Signal Region\nchr6\t19068900\t19075400\tHigh Signal Region\nchr6\t20113900\t20143500\tHigh Signal Region\nchr6\t21452400\t21458100\tHigh Signal Region\nchr6\t21801300\t21803200\tHigh Signal Region\nchr6\t21841300\t21845300\tHigh Signal Region\nchr6\t21873300\t21876800\tHigh Signal Region\nchr6\t22107700\t22131800\tHigh Signal Region\nchr6\t22479600\t22483900\tHigh Signal Region\nchr6\t22516700\t22534300\tHigh Signal Region\nchr6\t25505600\t25566400\tLow Mappability\nchr6\t26049500\t26072100\tHigh Signal Region\nchr6\t26247700\t26278000\tHigh Signal Region\nchr6\t26834800\t26840700\tHigh Signal Region\nchr6\t26988500\t26992000\tHigh Signal Region\nchr6\t27199000\t27228400\tHigh Signal Region\nchr6\t28924100\t28929500\tLow Mappability\nchr6\t29746800\t29750000\tHigh Signal Region\nchr6\t29974300\t29978200\tHigh Signal Region\nchr6\t30752800\t30806400\tHigh Signal Region\nchr6\t30929300\t30936100\tLow Mappability\nchr6\t31594900\t31597200\tHigh Signal Region\nchr6\t32740700\t32746800\tHigh Signal Region\nchr6\t32867600\t32869000\tHigh Signal Region\nchr6\t33490300\t33495000\tHigh Signal Region\nchr6\t33650500\t33665400\tHigh Signal Region\nchr6\t33743900\t33749000\tHigh Signal Region\nchr6\t36224300\t36230500\tHigh Signal Region\nchr6\t40535500\t40559800\tLow Mappability\nchr6\t40716600\t40723700\tHigh Signal Region\nchr6\t42122800\t42174200\tHigh Signal Region\nchr6\t42492600\t42516600\tHigh Signal Region\nchr6\t42617600\t42620900\tHigh Signal Region\nchr6\t44265200\t44270800\tHigh Signal Region\nchr6\t44497000\t44513300\tHigh Signal Region\nchr6\t44785200\t44794100\tHigh Signal Region\nchr6\t44836300\t44837500\tHigh Signal Region\nchr6\t46381300\t46402000\tHigh Signal Region\nchr6\t46678600\t46685300\tHigh Signal Region\nchr6\t47639000\t47779200\tHigh Signal Region\nchr6\t48120300\t48122300\tHigh Signal Region\nchr6\t48149300\t48172900\tHigh Signal Region\nchr6\t48231500\t48292600\tHigh Signal Region\nchr6\t48320300\t48347000\tHigh Signal Region\nchr6\t49235500\t49237500\tHigh Signal Region\nchr6\t50601400\t50636700\tLow Mappability\nchr6\t51046500\t51048400\tHigh Signal Region\nchr6\t53464100\t53487500\tLow Mappability\nchr6\t54976500\t54993700\tHigh Signal Region\nchr6\t56232700\t56257500\tHigh Signal Region\nchr6\t56455900\t56465300\tHigh Signal Region\nchr6\t57425200\t57455700\tHigh Signal Region\nchr6\t57588900\t57634500\tHigh Signal Region\nchr6\t57919500\t57925700\tHigh Signal Region\nchr6\t58068500\t58073500\tHigh Signal Region\nchr6\t58588700\t58612800\tHigh Signal Region\nchr6\t59123600\t59130100\tHigh Signal Region\nchr6\t59199600\t59230600\tHigh Signal Region\nchr6\t59584300\t59598000\tHigh Signal Region\nchr6\t59676000\t59698200\tHigh Signal Region\nchr6\t60622400\t60625600\tHigh Signal Region\nchr6\t60668000\t60688200\tHigh Signal Region\nchr6\t61023100\t61029400\tHigh Signal Region\nchr6\t61088400\t61094600\tHigh Signal Region\nchr6\t62525500\t62527300\tHigh Signal Region\nchr6\t64331600\t64338900\tLow Mappability\nchr6\t64778500\t64812500\tHigh Signal Region\nchr6\t64882100\t64930500\tHigh Signal Region\nchr6\t65100600\t65106700\tHigh Signal Region\nchr6\t65184300\t65261600\tHigh Signal Region\nchr6\t66070200\t66095900\tHigh Signal Region\nchr6\t66815600\t66831600\tHigh Signal Region\nchr6\t67311500\t67312900\tHigh Signal Region\nchr6\t67494800\t67522100\tLow Mappability\nchr6\t67576400\t67630800\tHigh Signal Region\nchr6\t67658300\t67710900\tHigh Signal Region\nchr6\t68011000\t68012900\tHigh Signal Region\nchr6\t68221900\t68252400\tLow Mappability\nchr6\t68641400\t68661300\tHigh Signal Region\nchr6\t68971900\t68996400\tHigh Signal Region\nchr6\t69017600\t69035700\tHigh Signal Region\nchr6\t70000300\t70053000\tHigh Signal Region\nchr6\t70187800\t70213700\tHigh Signal Region\nchr6\t70620700\t70648600\tHigh Signal Region\nchr6\t73105700\t73113400\tHigh Signal Region\nchr6\t73502200\t73521000\tHigh Signal Region\nchr6\t73671400\t73672600\tHigh Signal Region\nchr6\t74191700\t74194400\tHigh Signal Region\nchr6\t74365900\t74386400\tHigh Signal Region\nchr6\t74700100\t74705300\tHigh Signal Region\nchr6\t75054000\t75083000\tHigh Signal Region\nchr6\t76645400\t76649100\tHigh Signal Region\nchr6\t76847200\t76854100\tHigh Signal Region\nchr6\t78352900\t78359500\tHigh Signal Region\nchr6\t78456200\t78491700\tLow Mappability\nchr6\t78637400\t78639700\tHigh Signal Region\nchr6\t78716700\t78722400\tHigh Signal Region\nchr6\t79627500\t79635200\tHigh Signal Region\nchr6\t79817300\t79819200\tHigh Signal Region\nchr6\t79898900\t79922800\tLow Mappability\nchr6\t79959800\t79967500\tLow Mappability\nchr6\t81012200\t81036700\tHigh Signal Region\nchr6\t81829400\t81875000\tHigh Signal Region\nchr6\t81997000\t82011600\tHigh Signal Region\nchr6\t82213400\t82218800\tHigh Signal Region\nchr6\t84662700\t84688200\tHigh Signal Region\nchr6\t84712600\t84720200\tHigh Signal Region\nchr6\t89723500\t89735600\tHigh Signal Region\nchr6\t91768300\t91770200\tHigh Signal Region\nchr6\t92321600\t92328300\tHigh Signal Region\nchr6\t94988600\t94990700\tLow Mappability\nchr6\t95030100\t95043800\tLow Mappability\nchr6\t95475600\t95479900\tHigh Signal Region\nchr6\t95980800\t95987100\tHigh Signal Region\nchr6\t96877800\t96896100\tHigh Signal Region\nchr6\t97356800\t97379400\tHigh Signal Region\nchr6\t101571200\t101621400\tHigh Signal Region\nchr6\t102379600\t102384100\tHigh Signal Region\nchr6\t102483000\t102505700\tHigh Signal Region\nchr6\t102767600\t102791400\tHigh Signal Region\nchr6\t103313700\t103315600\tHigh Signal Region\nchr6\t103647900\t103650200\tHigh Signal Region\nchr6\t103750700\t103752000\tHigh Signal Region\nchr6\t105194700\t105199600\tHigh Signal Region\nchr6\t105253400\t105257600\tLow Mappability\nchr6\t105306000\t105337600\tHigh Signal Region\nchr6\t107141500\t107146300\tHigh Signal Region\nchr6\t107284300\t107299800\tHigh Signal Region\nchr6\t107860500\t107920500\tHigh Signal Region\nchr6\t109498200\t109506200\tHigh Signal Region\nchr6\t109641800\t109648100\tHigh Signal Region\nchr6\t109984000\t110013000\tHigh Signal Region\nchr6\t114340600\t114343000\tHigh Signal Region\nchr6\t114492200\t114643400\tHigh Signal Region\nchr6\t116021200\t116043900\tHigh Signal Region\nchr6\t116238700\t116252600\tHigh Signal Region\nchr6\t116566200\t116593800\tHigh Signal Region\nchr6\t117087400\t117094300\tHigh Signal Region\nchr6\t118209000\t118234000\tHigh Signal Region\nchr6\t119419600\t119431100\tHigh Signal Region\nchr6\t121690100\t121703800\tHigh Signal Region\nchr6\t122614200\t122616600\tHigh Signal Region\nchr6\t123132100\t123179400\tHigh Signal Region\nchr6\t123204800\t123242900\tHigh Signal Region\nchr6\t126135200\t126137300\tLow Mappability\nchr6\t128680200\t128693700\tHigh Signal Region\nchr6\t128861200\t128865300\tHigh Signal Region\nchr6\t129857800\t129863300\tHigh Signal Region\nchr6\t129935700\t129948400\tHigh Signal Region\nchr6\t131088300\t131114900\tHigh Signal Region\nchr6\t131208300\t131252100\tHigh Signal Region\nchr6\t131495900\t131505900\tHigh Signal Region\nchr6\t132497200\t132523000\tLow Mappability\nchr6\t132597000\t132598700\tHigh Signal Region\nchr6\t132635400\t132642000\tHigh Signal Region\nchr6\t133169000\t133170900\tHigh Signal Region\nchr6\t133891500\t133899800\tHigh Signal Region\nchr6\t134689500\t134692700\tHigh Signal Region\nchr6\t138216100\t138221900\tHigh Signal Region\nchr6\t138647300\t138649100\tHigh Signal Region\nchr6\t138685400\t138700700\tHigh Signal Region\nchr6\t142060700\t142079300\tHigh Signal Region\nchr6\t142396700\t142400200\tLow Mappability\nchr6\t142433400\t142439400\tHigh Signal Region\nchr6\t143014400\t143016300\tHigh Signal Region\nchr6\t143466500\t143481400\tHigh Signal Region\nchr6\t143883500\t143886900\tHigh Signal Region\nchr6\t144655200\t144670000\tHigh Signal Region\nchr6\t145784700\t145787000\tHigh Signal Region\nchr6\t145931800\t145933900\tLow Mappability\nchr6\t146018900\t146080500\tHigh Signal Region\nchr6\t147077200\t147079900\tHigh Signal Region\nchr6\t147459800\t147465000\tLow Mappability\nchr6\t147549600\t147555000\tLow Mappability\nchr6\t147881900\t147908400\tHigh Signal Region\nchr6\t148013100\t148038400\tHigh Signal Region\nchr6\t148121800\t148124500\tHigh Signal Region\nchr6\t148635700\t148640300\tLow Mappability\nchr6\t148662900\t148665000\tLow Mappability\nchr6\t149585500\t149736500\tHigh Signal Region\nchr7\t4558200\t4594300\tHigh Signal Region\nchr7\t4648600\t4651500\tHigh Signal Region\nchr7\t5153200\t5244900\tHigh Signal Region\nchr7\t5588700\t5591600\tHigh Signal Region\nchr7\t6050500\t6056000\tHigh Signal Region\nchr7\t6249400\t6251400\tHigh Signal Region\nchr7\t6590800\t6597400\tHigh Signal Region\nchr7\t7209500\t7231000\tHigh Signal Region\nchr7\t7273500\t7327400\tHigh Signal Region\nchr7\t7527500\t7533900\tHigh Signal Region\nchr7\t7556800\t8278400\tHigh Signal Region\nchr7\t8490800\t9968800\tHigh Signal Region\nchr7\t9992100\t9998900\tHigh Signal Region\nchr7\t10314900\t10320900\tHigh Signal Region\nchr7\t11097700\t11123700\tHigh Signal Region\nchr7\t11271100\t11438600\tHigh Signal Region\nchr7\t12009500\t12084600\tHigh Signal Region\nchr7\t12379600\t12385400\tHigh Signal Region\nchr7\t12526600\t12548100\tHigh Signal Region\nchr7\t13112300\t13118100\tHigh Signal Region\nchr7\t13591200\t13620200\tHigh Signal Region\nchr7\t14051300\t14055900\tHigh Signal Region\nchr7\t14767700\t14823800\tHigh Signal Region\nchr7\t14930100\t15023000\tHigh Signal Region\nchr7\t15128800\t15623000\tHigh Signal Region\nchr7\t16661400\t16667800\tHigh Signal Region\nchr7\t17112200\t17123900\tHigh Signal Region\nchr7\t17215800\t17323400\tHigh Signal Region\nchr7\t17800000\t17806700\tHigh Signal Region\nchr7\t17829700\t17862600\tHigh Signal Region\nchr7\t18487100\t18493200\tHigh Signal Region\nchr7\t19032600\t19034500\tHigh Signal Region\nchr7\t20799700\t21103900\tHigh Signal Region\nchr7\t21135700\t23286800\tHigh Signal Region\nchr7\t23494700\t23503600\tHigh Signal Region\nchr7\t24026200\t24031700\tHigh Signal Region\nchr7\t24103800\t24108200\tHigh Signal Region\nchr7\t24729400\t24731300\tHigh Signal Region\nchr7\t26022700\t26066900\tHigh Signal Region\nchr7\t26779000\t26780900\tHigh Signal Region\nchr7\t27082300\t27098300\tHigh Signal Region\nchr7\t27712800\t27732500\tHigh Signal Region\nchr7\t31365500\t31387000\tHigh Signal Region\nchr7\t31818200\t31876700\tHigh Signal Region\nchr7\t31934500\t32043100\tHigh Signal Region\nchr7\t32215700\t32235200\tHigh Signal Region\nchr7\t32629300\t33098700\tHigh Signal Region\nchr7\t33124200\t33198000\tHigh Signal Region\nchr7\t33949500\t34004800\tHigh Signal Region\nchr7\t34957200\t34959100\tHigh Signal Region\nchr7\t38396600\t38787200\tHigh Signal Region\nchr7\t38839800\t39181000\tHigh Signal Region\nchr7\t39227600\t39404100\tHigh Signal Region\nchr7\t39874600\t39875900\tHigh Signal Region\nchr7\t41791900\t41851900\tHigh Signal Region\nchr7\t43123800\t43220300\tHigh Signal Region\nchr7\t44737800\t44739900\tHigh Signal Region\nchr7\t47175100\t47188600\tHigh Signal Region\nchr7\t47414400\t47519700\tHigh Signal Region\nchr7\t48102600\t48135800\tHigh Signal Region\nchr7\t50940400\t50986800\tHigh Signal Region\nchr7\t51329800\t51335900\tHigh Signal Region\nchr7\t51800300\t51812600\tHigh Signal Region\nchr7\t51909200\t51911200\tHigh Signal Region\nchr7\t52095700\t52104400\tHigh Signal Region\nchr7\t52283300\t52288900\tHigh Signal Region\nchr7\t53677100\t53683100\tHigh Signal Region\nchr7\t53977800\t54027400\tHigh Signal Region\nchr7\t54336000\t54351800\tHigh Signal Region\nchr7\t54808900\t54810100\tHigh Signal Region\nchr7\t54923000\t54971200\tHigh Signal Region\nchr7\t55011500\t55016500\tHigh Signal Region\nchr7\t55080000\t55086300\tHigh Signal Region\nchr7\t55115400\t55141000\tHigh Signal Region\nchr7\t55657400\t55667100\tHigh Signal Region\nchr7\t56062300\t56081700\tHigh Signal Region\nchr7\t56160100\t56163400\tLow Mappability\nchr7\t56660300\t56693600\tHigh Signal Region\nchr7\t57367200\t57374700\tHigh Signal Region\nchr7\t58040300\t58077100\tHigh Signal Region\nchr7\t58161700\t58177900\tHigh Signal Region\nchr7\t59673100\t59910900\tHigh Signal Region\nchr7\t60209400\t60215600\tHigh Signal Region\nchr7\t60676300\t60682800\tHigh Signal Region\nchr7\t61320100\t61395400\tHigh Signal Region\nchr7\t62135200\t62137500\tHigh Signal Region\nchr7\t62651400\t62693400\tHigh Signal Region\nchr7\t63272500\t63287100\tHigh Signal Region\nchr7\t63431300\t63432400\tHigh Signal Region\nchr7\t63803700\t63810800\tHigh Signal Region\nchr7\t63908200\t63910100\tHigh Signal Region\nchr7\t64072600\t64134600\tHigh Signal Region\nchr7\t64465300\t64496400\tHigh Signal Region\nchr7\t64601000\t64617900\tHigh Signal Region\nchr7\t65187500\t65198300\tHigh Signal Region\nchr7\t68534700\t68537900\tHigh Signal Region\nchr7\t68775900\t68778100\tHigh Signal Region\nchr7\t69086500\t69102900\tHigh Signal Region\nchr7\t69785300\t69792200\tHigh Signal Region\nchr7\t70757900\t70765000\tHigh Signal Region\nchr7\t71971100\t71984500\tHigh Signal Region\nchr7\t72317400\t72337900\tHigh Signal Region\nchr7\t72630000\t72679900\tHigh Signal Region\nchr7\t73212000\t73218800\tHigh Signal Region\nchr7\t73671700\t73680000\tHigh Signal Region\nchr7\t75003200\t75007700\tHigh Signal Region\nchr7\t76067800\t76079300\tHigh Signal Region\nchr7\t76556000\t76573000\tHigh Signal Region\nchr7\t76703900\t76708400\tHigh Signal Region\nchr7\t77520600\t77526000\tHigh Signal Region\nchr7\t78416900\t78422400\tHigh Signal Region\nchr7\t80708100\t80730100\tLow Mappability\nchr7\t80787500\t80813800\tHigh Signal Region\nchr7\t81756100\t81760500\tHigh Signal Region\nchr7\t82770300\t82772800\tHigh Signal Region\nchr7\t85017700\t85023600\tHigh Signal Region\nchr7\t85757200\t85768800\tHigh Signal Region\nchr7\t86118700\t86125800\tHigh Signal Region\nchr7\t86497400\t86503500\tHigh Signal Region\nchr7\t86532600\t86534000\tHigh Signal Region\nchr7\t86805600\t86807500\tHigh Signal Region\nchr7\t87989300\t88000600\tHigh Signal Region\nchr7\t89683300\t89704600\tHigh Signal Region\nchr7\t90087300\t90089400\tHigh Signal Region\nchr7\t90441000\t90442900\tHigh Signal Region\nchr7\t91741500\t91747500\tHigh Signal Region\nchr7\t93259400\t93278100\tHigh Signal Region\nchr7\t93699600\t93717500\tHigh Signal Region\nchr7\t93744000\t93766100\tHigh Signal Region\nchr7\t93969600\t93973700\tHigh Signal Region\nchr7\t94293000\t94299300\tHigh Signal Region\nchr7\t94822500\t94848800\tHigh Signal Region\nchr7\t95177200\t95193600\tHigh Signal Region\nchr7\t95527400\t95533200\tHigh Signal Region\nchr7\t97795000\t97797300\tHigh Signal Region\nchr7\t103100800\t103115000\tHigh Signal Region\nchr7\t103195500\t103202100\tHigh Signal Region\nchr7\t103483000\t103487500\tHigh Signal Region\nchr7\t104097400\t104126600\tHigh Signal Region\nchr7\t104476800\t104477900\tHigh Signal Region\nchr7\t104770000\t104801200\tHigh Signal Region\nchr7\t105830300\t106325300\tHigh Signal Region\nchr7\t106979000\t106984900\tHigh Signal Region\nchr7\t107245200\t107271400\tHigh Signal Region\nchr7\t108780600\t108789800\tHigh Signal Region\nchr7\t110058500\t110061600\tHigh Signal Region\nchr7\t111228400\t111230600\tHigh Signal Region\nchr7\t112636600\t112639800\tHigh Signal Region\nchr7\t116432200\t116453400\tHigh Signal Region\nchr7\t119739900\t119742100\tHigh Signal Region\nchr7\t119795700\t119797700\tHigh Signal Region\nchr7\t119998800\t120015100\tHigh Signal Region\nchr7\t124522300\t124528300\tHigh Signal Region\nchr7\t125009800\t125016600\tHigh Signal Region\nchr7\t128171000\t128189300\tHigh Signal Region\nchr7\t130054200\t130055700\tHigh Signal Region\nchr7\t130591400\t130596900\tHigh Signal Region\nchr7\t130833500\t130835600\tHigh Signal Region\nchr7\t134100500\t134107200\tHigh Signal Region\nchr7\t134329200\t134335200\tHigh Signal Region\nchr7\t135006900\t135008800\tHigh Signal Region\nchr7\t135337800\t135340900\tHigh Signal Region\nchr7\t138590500\t138594500\tHigh Signal Region\nchr7\t139447400\t139448900\tHigh Signal Region\nchr7\t140288200\t140307300\tHigh Signal Region\nchr7\t140551100\t140558800\tHigh Signal Region\nchr7\t140580500\t140585700\tHigh Signal Region\nchr7\t141637000\t141640700\tHigh Signal Region\nchr7\t142828900\t142845000\tHigh Signal Region\nchr7\t145340000\t145441400\tHigh Signal Region\nchr8\t3753500\t3779100\tHigh Signal Region\nchr8\t14305800\t14308200\tHigh Signal Region\nchr8\t15508900\t15521000\tHigh Signal Region\nchr8\t19671800\t19937800\tHigh Signal Region\nchr8\t19960800\t20868000\tHigh Signal Region\nchr8\t20945500\t20963700\tHigh Signal Region\nchr8\t23085600\t23096700\tHigh Signal Region\nchr8\t35134000\t35135900\tHigh Signal Region\nchr8\t39132400\t39157700\tHigh Signal Region\nchr8\t55111200\t55397300\tHigh Signal Region\nchr8\t69416700\t69597900\tHigh Signal Region\nchr8\t71432100\t71434100\tHigh Signal Region\nchr8\t71796100\t71863300\tHigh Signal Region\nchr8\t73318700\t73320700\tHigh Signal Region\nchr8\t83755800\t83757900\tHigh Signal Region\nchr8\t114436000\t114437900\tHigh Signal Region\nchr8\t123537300\t123638300\tHigh Signal Region\nchr8\t125778100\t125780100\tHigh Signal Region\nchr8\t129272900\t129401200\tHigh Signal Region\nchr9\t0\t3053100\tHigh Signal Region\nchr9\t3240200\t3259800\tHigh Signal Region\nchr9\t3302000\t3336000\tHigh Signal Region\nchr9\t3461000\t3466600\tLow Mappability\nchr9\t3627400\t3699700\tLow Mappability\nchr9\t3802100\t3806700\tHigh Signal Region\nchr9\t3881100\t3887600\tHigh Signal Region\nchr9\t4238700\t4245700\tLow Mappability\nchr9\t4375700\t4406800\tHigh Signal Region\nchr9\t5248000\t5254100\tHigh Signal Region\nchr9\t5276200\t5284600\tLow Mappability\nchr9\t6431500\t6467200\tHigh Signal Region\nchr9\t6742900\t6806200\tLow Mappability\nchr9\t7294600\t7300700\tHigh Signal Region\nchr9\t7370900\t7412600\tLow Mappability\nchr9\t7520900\t7525900\tHigh Signal Region\nchr9\t8029400\t8067100\tLow Mappability\nchr9\t8275900\t8292300\tLow Mappability\nchr9\t8447200\t8483700\tHigh Signal Region\nchr9\t8628200\t8633700\tLow Mappability\nchr9\t8859900\t8865500\tHigh Signal Region\nchr9\t9598800\t9626700\tHigh Signal Region\nchr9\t9846900\t9891900\tLow Mappability\nchr9\t10193200\t10198800\tLow Mappability\nchr9\t10701300\t10707400\tHigh Signal Region\nchr9\t10964200\t10970600\tHigh Signal Region\nchr9\t11341900\t11345100\tHigh Signal Region\nchr9\t11722300\t11747100\tHigh Signal Region\nchr9\t11792800\t11798400\tLow Mappability\nchr9\t11821400\t11845400\tHigh Signal Region\nchr9\t12282000\t12287500\tHigh Signal Region\nchr9\t12364900\t12379600\tHigh Signal Region\nchr9\t12469100\t12472900\tLow Mappability\nchr9\t12768200\t12773800\tHigh Signal Region\nchr9\t12840100\t12851100\tHigh Signal Region\nchr9\t12917600\t12922300\tHigh Signal Region\nchr9\t12998400\t13045600\tLow Mappability\nchr9\t13324200\t13426100\tHigh Signal Region\nchr9\t13533500\t13535700\tHigh Signal Region\nchr9\t13994600\t13996700\tHigh Signal Region\nchr9\t14410500\t14429300\tLow Mappability\nchr9\t15123900\t15136900\tHigh Signal Region\nchr9\t16607400\t16691900\tLow Mappability\nchr9\t16833700\t16861000\tHigh Signal Region\nchr9\t16939400\t16950500\tLow Mappability\nchr9\t17059000\t17088000\tHigh Signal Region\nchr9\t17197900\t17207600\tHigh Signal Region\nchr9\t17261400\t17263400\tLow Mappability\nchr9\t17387200\t17406200\tHigh Signal Region\nchr9\t17525800\t17527700\tHigh Signal Region\nchr9\t17632000\t17636100\tHigh Signal Region\nchr9\t17916200\t17919600\tHigh Signal Region\nchr9\t18010000\t18015600\tHigh Signal Region\nchr9\t18117000\t18162200\tLow Mappability\nchr9\t18235100\t18270100\tHigh Signal Region\nchr9\t18893800\t18900100\tHigh Signal Region\nchr9\t18980400\t18994100\tHigh Signal Region\nchr9\t19268700\t19294700\tHigh Signal Region\nchr9\t19595400\t19638400\tHigh Signal Region\nchr9\t19720500\t19725500\tLow Mappability\nchr9\t19901400\t19906100\tHigh Signal Region\nchr9\t20183600\t20196700\tLow Mappability\nchr9\t20322100\t20407900\tHigh Signal Region\nchr9\t21879200\t21928200\tHigh Signal Region\nchr9\t22116600\t22191600\tHigh Signal Region\nchr9\t22699500\t22731700\tHigh Signal Region\nchr9\t22892700\t22926500\tLow Mappability\nchr9\t22947900\t22956900\tHigh Signal Region\nchr9\t23508700\t23526900\tHigh Signal Region\nchr9\t24523300\t24576000\tHigh Signal Region\nchr9\t25596700\t25602700\tHigh Signal Region\nchr9\t25842900\t25863600\tHigh Signal Region\nchr9\t26096100\t26103500\tLow Mappability\nchr9\t26700800\t26708000\tHigh Signal Region\nchr9\t26904600\t26911000\tHigh Signal Region\nchr9\t27212200\t27232300\tHigh Signal Region\nchr9\t27974400\t27981700\tHigh Signal Region\nchr9\t29739800\t29741800\tLow Mappability\nchr9\t30604400\t30606300\tLow Mappability\nchr9\t30641800\t30696800\tLow Mappability\nchr9\t30929800\t30931100\tHigh Signal Region\nchr9\t32059200\t32083600\tLow Mappability\nchr9\t32353900\t32356500\tHigh Signal Region\nchr9\t32839200\t32846600\tLow Mappability\nchr9\t32888700\t32896000\tLow Mappability\nchr9\t32953000\t32958100\tLow Mappability\nchr9\t33127100\t33161100\tLow Mappability\nchr9\t33392400\t33402700\tHigh Signal Region\nchr9\t33949500\t33961900\tLow Mappability\nchr9\t35071200\t35091800\tHigh Signal Region\nchr9\t35304300\t35306500\tHigh Signal Region\nchr9\t36235800\t36241900\tHigh Signal Region\nchr9\t36555000\t36569100\tHigh Signal Region\nchr9\t37331400\t37349500\tLow Mappability\nchr9\t37441700\t37448100\tHigh Signal Region\nchr9\t39330900\t39359100\tHigh Signal Region\nchr9\t39444100\t39449600\tHigh Signal Region\nchr9\t39835400\t39899000\tLow Mappability\nchr9\t44214200\t44235400\tLow Mappability\nchr9\t44305700\t44408400\tLow Mappability\nchr9\t47957400\t47959300\tHigh Signal Region\nchr9\t50082000\t50088400\tHigh Signal Region\nchr9\t51667400\t51673700\tHigh Signal Region\nchr9\t52601800\t52617200\tHigh Signal Region\nchr9\t52749000\t52756100\tHigh Signal Region\nchr9\t53089800\t53107000\tHigh Signal Region\nchr9\t53804100\t53805400\tHigh Signal Region\nchr9\t54916200\t54928900\tHigh Signal Region\nchr9\t55070600\t55078000\tLow Mappability\nchr9\t55150300\t55152300\tHigh Signal Region\nchr9\t55936900\t55972500\tHigh Signal Region\nchr9\t56222700\t56224800\tHigh Signal Region\nchr9\t56259500\t56284300\tHigh Signal Region\nchr9\t56991700\t56993700\tLow Mappability\nchr9\t57408000\t57434800\tHigh Signal Region\nchr9\t58766500\t58785800\tHigh Signal Region\nchr9\t59046200\t59052700\tLow Mappability\nchr9\t59103800\t59125000\tHigh Signal Region\nchr9\t60538500\t60551200\tHigh Signal Region\nchr9\t60726100\t60733500\tHigh Signal Region\nchr9\t61721500\t61723400\tHigh Signal Region\nchr9\t62811600\t62868300\tLow Mappability\nchr9\t64236700\t64255000\tLow Mappability\nchr9\t64410400\t64417700\tLow Mappability\nchr9\t65292600\t65314200\tHigh Signal Region\nchr9\t65867400\t65909400\tHigh Signal Region\nchr9\t67198600\t67205000\tLow Mappability\nchr9\t68451200\t68461200\tHigh Signal Region\nchr9\t68527100\t68534600\tHigh Signal Region\nchr9\t71080600\t71120800\tLow Mappability\nchr9\t71421100\t71434600\tHigh Signal Region\nchr9\t72895800\t72900800\tLow Mappability\nchr9\t72957900\t72985700\tLow Mappability\nchr9\t73285500\t73311300\tHigh Signal Region\nchr9\t73396800\t73412500\tLow Mappability\nchr9\t73861400\t73863500\tLow Mappability\nchr9\t73935600\t73946700\tHigh Signal Region\nchr9\t74615600\t74641300\tLow Mappability\nchr9\t74664800\t74690900\tHigh Signal Region\nchr9\t74768600\t74774600\tHigh Signal Region\nchr9\t75709200\t75736000\tLow Mappability\nchr9\t77079900\t77082800\tHigh Signal Region\nchr9\t77152800\t77158800\tHigh Signal Region\nchr9\t77972400\t77974300\tHigh Signal Region\nchr9\t78175200\t78182700\tLow Mappability\nchr9\t78230500\t78296900\tHigh Signal Region\nchr9\t78554700\t78589200\tLow Mappability\nchr9\t78755200\t78757800\tHigh Signal Region\nchr9\t78819200\t78830500\tLow Mappability\nchr9\t80234500\t80235700\tHigh Signal Region\nchr9\t80660700\t80665600\tHigh Signal Region\nchr9\t81251500\t81303200\tHigh Signal Region\nchr9\t81614000\t81620700\tHigh Signal Region\nchr9\t81906400\t81937200\tHigh Signal Region\nchr9\t83278800\t83288100\tHigh Signal Region\nchr9\t83558300\t83560200\tHigh Signal Region\nchr9\t83935500\t83950000\tHigh Signal Region\nchr9\t83992400\t83998900\tHigh Signal Region\nchr9\t84211900\t84226800\tHigh Signal Region\nchr9\t85898900\t85918900\tHigh Signal Region\nchr9\t86062600\t86070000\tLow Mappability\nchr9\t86120100\t86137500\tHigh Signal Region\nchr9\t86458200\t86463100\tHigh Signal Region\nchr9\t87098700\t87112200\tHigh Signal Region\nchr9\t87481400\t87500900\tHigh Signal Region\nchr9\t87576700\t87594000\tHigh Signal Region\nchr9\t87945600\t87952400\tHigh Signal Region\nchr9\t88011000\t88013900\tHigh Signal Region\nchr9\t88592100\t88829800\tHigh Signal Region\nchr9\t89031300\t89075400\tLow Mappability\nchr9\t89321400\t89361800\tHigh Signal Region\nchr9\t90147100\t90149100\tHigh Signal Region\nchr9\t90285200\t90395300\tHigh Signal Region\nchr9\t90455400\t90456800\tHigh Signal Region\nchr9\t90808100\t90821900\tLow Mappability\nchr9\t90857200\t90876300\tLow Mappability\nchr9\t91222100\t91268200\tHigh Signal Region\nchr9\t91598800\t91647400\tHigh Signal Region\nchr9\t92032700\t92035300\tHigh Signal Region\nchr9\t92075300\t92113200\tHigh Signal Region\nchr9\t92239700\t92242900\tHigh Signal Region\nchr9\t92624800\t92654500\tHigh Signal Region\nchr9\t93013300\t93035300\tHigh Signal Region\nchr9\t93286500\t93296500\tHigh Signal Region\nchr9\t93360800\t93442100\tLow Mappability\nchr9\t93618000\t93668500\tLow Mappability\nchr9\t94821700\t94828100\tLow Mappability\nchr9\t95245800\t95299600\tHigh Signal Region\nchr9\t95425000\t95426900\tHigh Signal Region\nchr9\t95829400\t95831300\tHigh Signal Region\nchr9\t96104900\t96111400\tLow Mappability\nchr9\t96852000\t96854100\tHigh Signal Region\nchr9\t98343300\t98345700\tLow Mappability\nchr9\t98451100\t98458500\tLow Mappability\nchr9\t98747700\t98771800\tLow Mappability\nchr9\t99266600\t99273100\tLow Mappability\nchr9\t99735800\t99763300\tHigh Signal Region\nchr9\t99922800\t99937600\tHigh Signal Region\nchr9\t100073800\t100080700\tHigh Signal Region\nchr9\t100516900\t100519200\tHigh Signal Region\nchr9\t100920400\t100922300\tHigh Signal Region\nchr9\t101085500\t101110600\tHigh Signal Region\nchr9\t101292500\t101326600\tLow Mappability\nchr9\t102277400\t102283800\tLow Mappability\nchr9\t102764700\t102766800\tLow Mappability\nchr9\t102812800\t102815000\tHigh Signal Region\nchr9\t102956300\t102970000\tLow Mappability\nchr9\t103296200\t103305600\tHigh Signal Region\nchr9\t103352800\t103367100\tLow Mappability\nchr9\t103988500\t103990400\tHigh Signal Region\nchr9\t104524500\t104525700\tHigh Signal Region\nchr9\t104848800\t104850600\tHigh Signal Region\nchr9\t105086200\t105119300\tHigh Signal Region\nchr9\t105818400\t105820400\tHigh Signal Region\nchr9\t107207900\t107219900\tHigh Signal Region\nchr9\t109036600\t109083500\tHigh Signal Region\nchr9\t109245000\t109252200\tHigh Signal Region\nchr9\t109272900\t109374100\tHigh Signal Region\nchr9\t110280300\t110306700\tHigh Signal Region\nchr9\t110443100\t110455100\tHigh Signal Region\nchr9\t110970300\t110976000\tHigh Signal Region\nchr9\t111661900\t111668700\tHigh Signal Region\nchr9\t112330100\t112336900\tHigh Signal Region\nchr9\t112956300\t112990600\tHigh Signal Region\nchr9\t113260500\t113262400\tHigh Signal Region\nchr9\t113535400\t113541300\tHigh Signal Region\nchr9\t114101400\t114149500\tLow Mappability\nchr9\t114172400\t114322200\tHigh Signal Region\nchr9\t114970100\t114974700\tLow Mappability\nchr9\t115077900\t115085200\tLow Mappability\nchr9\t115349900\t115351800\tHigh Signal Region\nchr9\t115496100\t115498100\tLow Mappability\nchr9\t116981500\t116988600\tHigh Signal Region\nchr9\t118088300\t118151400\tHigh Signal Region\nchr9\t118674000\t118675900\tHigh Signal Region\nchr9\t119861200\t119895000\tLow Mappability\nchr9\t120265300\t120288700\tHigh Signal Region\nchr9\t120633900\t120641200\tLow Mappability\nchr9\t121024600\t121042700\tLow Mappability\nchr9\t121178300\t121184500\tHigh Signal Region\nchr9\t121220100\t121247600\tHigh Signal Region\nchr9\t121313700\t121385800\tLow Mappability\nchr9\t121406300\t121418400\tLow Mappability\nchr9\t122161300\t122163200\tHigh Signal Region\nchr9\t122277700\t122334500\tLow Mappability\nchr9\t122401500\t122441900\tLow Mappability\nchr9\t122660600\t122667200\tLow Mappability\nchr9\t122703400\t122730400\tLow Mappability\nchr9\t122903900\t122906600\tHigh Signal Region\nchr9\t123190700\t123197500\tLow Mappability\nchr9\t123460900\t123463100\tHigh Signal Region\nchr9\t123742600\t123753500\tLow Mappability\nchr9\t123851700\t123929500\tHigh Signal Region\nchr9\t123966100\t124009300\tHigh Signal Region\nchr9\t124161300\t124282600\tHigh Signal Region\nchr9\t124494100\t124595100\tHigh Signal Region\nchrX\t3286700\t4493800\tHigh Signal Region\nchrX\t4524500\t5370300\tHigh Signal Region\nchrX\t8346400\t8348200\tHigh Signal Region\nchrX\t8550300\t8557800\tHigh Signal Region\nchrX\t8818900\t8824300\tHigh Signal Region\nchrX\t9345800\t9395300\tHigh Signal Region\nchrX\t9500200\t9595700\tHigh Signal Region\nchrX\t14739100\t14741000\tHigh Signal Region\nchrX\t21466500\t21472700\tHigh Signal Region\nchrX\t21846900\t21896100\tHigh Signal Region\nchrX\t26459300\t26505100\tHigh Signal Region\nchrX\t26907100\t29639200\tHigh Signal Region\nchrX\t29660500\t35508900\tHigh Signal Region\nchrX\t37612500\t37669100\tHigh Signal Region\nchrX\t39073800\t39075700\tHigh Signal Region\nchrX\t41482500\t41489500\tHigh Signal Region\nchrX\t42676200\t42688100\tHigh Signal Region\nchrX\t44239900\t44293300\tHigh Signal Region\nchrX\t44732600\t44738600\tHigh Signal Region\nchrX\t48699000\t48771100\tHigh Signal Region\nchrX\t54269300\t55286000\tHigh Signal Region\nchrX\t55716700\t55807400\tHigh Signal Region\nchrX\t58475000\t58478700\tHigh Signal Region\nchrX\t59773000\t59796900\tHigh Signal Region\nchrX\t61868200\t61874000\tHigh Signal Region\nchrX\t62065700\t62084900\tHigh Signal Region\nchrX\t63509200\t63515900\tHigh Signal Region\nchrX\t63634600\t63640900\tHigh Signal Region\nchrX\t64125800\t64132200\tHigh Signal Region\nchrX\t65962800\t65999900\tHigh Signal Region\nchrX\t66067900\t66084000\tHigh Signal Region\nchrX\t66143100\t66145700\tHigh Signal Region\nchrX\t66316400\t66356900\tHigh Signal Region\nchrX\t67662500\t67708500\tHigh Signal Region\nchrX\t70055300\t70072000\tHigh Signal Region\nchrX\t72800000\t72818700\tHigh Signal Region\nchrX\t75582400\t75709000\tHigh Signal Region\nchrX\t76589100\t76607100\tHigh Signal Region\nchrX\t79135300\t79150400\tHigh Signal Region\nchrX\t81153100\t81154600\tHigh Signal Region\nchrX\t82475800\t82481000\tHigh Signal Region\nchrX\t84290800\t84296100\tHigh Signal Region\nchrX\t87222400\t87262500\tHigh Signal Region\nchrX\t87838600\t87845200\tHigh Signal Region\nchrX\t88230200\t88246900\tHigh Signal Region\nchrX\t89182800\t89232600\tHigh Signal Region\nchrX\t89914800\t89916600\tHigh Signal Region\nchrX\t90308600\t90336600\tHigh Signal Region\nchrX\t92765200\t92767900\tHigh Signal Region\nchrX\t94795400\t94980600\tHigh Signal Region\nchrX\t95265900\t95291700\tHigh Signal Region\nchrX\t97728000\t97734800\tHigh Signal Region\nchrX\t98008600\t98033000\tHigh Signal Region\nchrX\t98585800\t98612400\tHigh Signal Region\nchrX\t101111300\t101113600\tHigh Signal Region\nchrX\t102560800\t102585100\tHigh Signal Region\nchrX\t103455000\t103457100\tHigh Signal Region\nchrX\t104959400\t104966000\tHigh Signal Region\nchrX\t105523800\t105529900\tHigh Signal Region\nchrX\t108202600\t108222500\tHigh Signal Region\nchrX\t108567500\t108585200\tHigh Signal Region\nchrX\t109871000\t109876200\tHigh Signal Region\nchrX\t110976700\t110997000\tHigh Signal Region\nchrX\t112369800\t112402300\tHigh Signal Region\nchrX\t114412500\t114421300\tHigh Signal Region\nchrX\t118100900\t118102900\tHigh Signal Region\nchrX\t118901200\t118905100\tLow Mappability\nchrX\t119137300\t119142400\tHigh Signal Region\nchrX\t119247400\t119264800\tHigh Signal Region\nchrX\t119335000\t119339300\tHigh Signal Region\nchrX\t120351000\t120355400\tHigh Signal Region\nchrX\t121511200\t121514500\tHigh Signal Region\nchrX\t122901700\t122908000\tHigh Signal Region\nchrX\t123686000\t124042000\tHigh Signal Region\nchrX\t126695300\t126778800\tHigh Signal Region\nchrX\t127935800\t127964600\tHigh Signal Region\nchrX\t128512700\t128514400\tHigh Signal Region\nchrX\t128959800\t128965900\tHigh Signal Region\nchrX\t129055600\t129072400\tHigh Signal Region\nchrX\t129429300\t129448000\tHigh Signal Region\nchrX\t130696000\t130702200\tHigh Signal Region\nchrX\t131802300\t131832800\tHigh Signal Region\nchrX\t132024200\t132026400\tHigh Signal Region\nchrX\t132158700\t132160800\tHigh Signal Region\nchrX\t134149100\t134151200\tHigh Signal Region\nchrX\t135040100\t135056700\tHigh Signal Region\nchrX\t136459400\t136503800\tHigh Signal Region\nchrX\t136897900\t136925800\tHigh Signal Region\nchrX\t138302200\t138324600\tHigh Signal Region\nchrX\t143471300\t143484000\tHigh Signal Region\nchrX\t144699500\t144723900\tHigh Signal Region\nchrX\t145709800\t145739800\tHigh Signal Region\nchrX\t146582500\t146588700\tHigh Signal Region\nchrX\t146758100\t146761900\tHigh Signal Region\nchrX\t147619400\t147620700\tHigh Signal Region\nchrX\t153994800\t154073200\tHigh Signal Region\nchrX\t154242800\t154244800\tHigh Signal Region\nchrX\t158443900\t158460500\tHigh Signal Region\nchrX\t159120000\t159154900\tHigh Signal Region\nchrX\t161179200\t161185600\tHigh Signal Region\nchrX\t162381600\t162384600\tHigh Signal Region\nchrX\t164615100\t164622200\tHigh Signal Region\nchrX\t166063200\t166084500\tHigh Signal Region\nchrX\t167213400\t167220200\tHigh Signal Region\nchrX\t167246000\t167252200\tHigh Signal Region\nchrX\t169968900\t171031200\tHigh Signal Region\nchrY\t0\t806800\tHigh Signal Region\nchrY\t924800\t1005300\tHigh Signal Region\nchrY\t1276400\t1813700\tHigh Signal Region\nchrY\t1834500\t1940700\tHigh Signal Region\nchrY\t1973200\t1996400\tHigh Signal Region\nchrY\t2017200\t2068000\tLow Mappability\nchrY\t2104700\t2210800\tHigh Signal Region\nchrY\t2280300\t2288900\tLow Mappability\nchrY\t2471300\t3819300\tHigh Signal Region\nchrY\t3880300\t4177100\tHigh Signal Region\nchrY\t4249500\t4289100\tHigh Signal Region\nchrY\t4432000\t4956300\tHigh Signal Region\nchrY\t5062400\t5227700\tHigh Signal Region\nchrY\t6376700\t6382700\tHigh Signal Region\nchrY\t6530200\t6663200\tHigh Signal Region\nchrY\t6760200\t6835800\tHigh Signal Region\nchrY\t6984100\t8985400\tHigh Signal Region\nchrY\t10638500\t41003800\tHigh Signal Region\nchrY\t41159200\t91744600\tHigh Signal Region\n" }, { "path": "assets/blacklists/v3.0/GRCh38-blacklist.v3.bed", "content": 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nchr7\t117264231\t117264614\nchr7\t130116678\t130117058\nchr7\t141173000\t141173384\nchr7\t141801916\t141802451\nchr7\t141802901\t141803366\nchr7\t141804074\t141804274\nchr7\t141804814\t141805507\nchr7\t142665099\t142667846\nchr7\t143187483\t143187863\nchr7\t145997159\t145997608\nchr7\t150131843\t150132229\nchr7\t153968598\t153968979\nchr7\t159294463\t159294846\nchr8\t13353292\t13353679\nchr8\t16056863\t16057063\nchr8\t18849121\t18849571\nchr8\t20551162\t20551554\nchr8\t32805708\t32806092\nchr8\t33010514\t33010894\nchr8\t33011359\t33014071\nchr8\t33014510\t33014895\nchr8\t33015020\t33015853\nchr8\t36277446\t36278060\nchr8\t36278272\t36278791\nchr8\t36278835\t36279634\nchr8\t40070431\t40070867\nchr8\t43237631\t43242390\nchr8\t43937900\t45969600\nchr8\t46827305\t46827914\nchr8\t46828298\t46829961\nchr8\t46830195\t46831222\nchr8\t46837581\t46837961\nchr8\t46838101\t46838484\nchr8\t50758259\t50758639\nchr8\t56736733\t56736933\nchr8\t61303079\t61303460\nchr8\t67580689\t67581493\nchr8\t67581588\t67581972\nchr8\t67582178\t67582568\nchr8\t67585216\t67585693\nchr8\t67585787\t67586175\nchr8\t67587282\t67587922\nchr8\t69102851\t69103234\nchr8\t72985528\t72985923\nchr8\t74828644\t74829025\nchr8\t76201592\t76202319\nchr8\t76645407\t76645800\nchr8\t97907908\t97908279\nchr8\t99495689\t99496133\nchr8\t102774315\t102774695\nchr8\t103082925\t103083379\nchr8\t103083704\t103084399\nchr8\t103084730\t103085110\nchr8\t103085323\t103085806\nchr8\t103086859\t103087242\nchr8\t108533901\t108534281\nchr8\t110933150\t110933533\nchr8\t110934510\t110935010\nchr8\t111248936\t111249316\nchr8\t120224204\t120224584\nchr8\t127053876\t127054257\nchr8\t127968653\t127969034\nchr8\t133615761\t133616142\nchr8\t133755390\t133755856\nchr9\t5091131\t5091511\nchr9\t5091962\t5093013\nchr9\t5093063\t5094123\nchr9\t5094192\t5094697\nchr9\t5094931\t5095816\nchr9\t5096206\t5096816\nchr9\t5097188\t5097890\nchr9\t5098134\t5098516\nchr9\t5099352\t5099552\nchr9\t5100044\t5100427\nchr9\t5108063\t5108592\nchr9\t5109193\t5109986\nchr9\t5110030\t5110411\nchr9\t9896970\t9897350\nchr9\t15866612\t15866992\nchr9\t18336471\t18336854\nchr9\t31498260\t31498640\nchr9\t33656533\t33658316\nchr9\t33658346\t33659299\nchr9\t34998988\t34999474\nchr9\t36466192\t36466572\nchr9\t43153721\t45525161\nchr9\t64045550\t64046043\nchr9\t64047855\t64048422\nchr9\t65048153\t65079624\nchr9\t68251002\t68251071\nchr9\t72788174\t72788555\nchr9\t78741395\t78741775\nchr9\t78742155\t78742969\nchr9\t78743199\t78743630\nchr9\t78744108\t78744492\nchr9\t78810721\t78811113\nchr9\t79804550\t79804933\nchr9\t80564643\t80565085\nchr9\t80565478\t80565941\nchr9\t81747641\t81748021\nchr9\t82427689\t82428071\nchr9\t92108965\t92109347\nchr9\t92539106\t92539763\nchr9\t95876956\t95877338\nchr9\t117109914\t117110296\nchr9\t122505687\t122506067\nchr9\t129878699\t129879081\nchr9\t134164478\t134165354\nchr9\t134170819\t134171060\nchrX\t4059512\t4059712\nchrX\t5168678\t5169232\nchrX\t5169733\t5170646\nchrX\t15727702\t15728089\nchrX\t17116414\t17116794\nchrX\t24056083\t24056470\nchrX\t24375345\t24375545\nchrX\t33762401\t33762781\nchrX\t55178596\t55179289\nchrX\t55179434\t55180459\nchrX\t55181196\t55182790\nchrX\t55183051\t55184112\nchrX\t58061543\t62821716\nchrX\t62841379\t62841765\nchrX\t62842257\t62842639\nchrX\t70119464\t70119845\nchrX\t70127233\t70127620\nchrX\t77501934\t77502314\nchrX\t78561721\t78561921\nchrX\t84403779\t84404168\nchrX\t100027094\t100027475\nchrX\t102010329\t102010712\nchrX\t102011531\t102011915\nchrX\t102772405\t102772791\nchrX\t102785904\t102786287\nchrX\t102798001\t102798386\nchrX\t102802747\t102803161\nchrX\t102809395\t102809788\nchrX\t104409869\t104410249\nchrX\t106239694\t106239894\nchrX\t111416893\t111417294\nchrX\t126471558\t126473451\nchrX\t126728884\t126729272\nchrX\t126729326\t126729709\nchrX\t126729837\t126730217\nchrX\t126730716\t126731106\nchrX\t126731624\t126732029\nchrX\t129983338\t129983538\nchrX\t133041871\t133042251\nchrX\t135292293\t135292493\nchrX\t143430213\t143430837\nchrX\t143431144\t143431537\nchrX\t143431716\t143432219\nchrX\t143432410\t143433212\nchrX\t143433510\t143434156\nchrX\t143543636\t143544023\nchrX\t146995842\t146996224\nchrY\t4344757\t4344879\nchrY\t9141870\t9141995\nchrY\t10203380\t10266932\nchrY\t10316749\t10544446\nchrY\t10594583\t10626838\nchrY\t10663669\t10663716\nchrY\t10744417\t10921497\nchrY\t11290797\t11334278\nchrY\t11493053\t11592850\nchrY\t11671014\t11671046\nchrY\t11721528\t11749472\nchrY\t56694632\t56889743\n" }, { "path": "assets/email_template.html", "content": "\n\n \n \n \n\n \n nf-core/atacseq Pipeline Report\n\n\n
\n\n\n\n

nf-core/atacseq v${version}

\n

Run Name: $runName

\n\n<% if (!success){\n out << \"\"\"\n
\n

nf-core/atacseq execution completed unsuccessfully!

\n

The exit status of the task that caused the workflow execution to fail was: $exitStatus.

\n

The full error message was:

\n 
${errorReport}
\n
\n \"\"\"\n} else {\n out << \"\"\"\n
\n nf-core/atacseq execution completed successfully!\n
\n \"\"\"\n}\n%>\n\n

The workflow was completed at $dateComplete (duration: $duration)

\n

The command used to launch the workflow was as follows:

\n
$commandLine
\n\n

Pipeline Configuration:

\n\n \n <% out << summary.collect{ k,v -> \"\" }.join(\"\\n\") %>\n \n
$k
$v
\n\n

nf-core/atacseq

\n

https://github.com/nf-core/atacseq

\n\n
\n\n\n\n" }, { "path": "assets/email_template.txt", "content": "----------------------------------------------------\n ,--./,-.\n ___ __ __ __ ___ /,-._.--~\\\\\n |\\\\ | |__ __ / ` / \\\\ |__) |__ } {\n | \\\\| | \\\\__, \\\\__/ | \\\\ |___ \\\\`-._,-`-,\n `._,._,'\n nf-core/atacseq v${version}\n----------------------------------------------------\nRun Name: $runName\n\n<% if (success){\n out << \"## nf-core/atacseq execution completed successfully! ##\"\n} else {\n out << \"\"\"####################################################\n## nf-core/atacseq execution completed unsuccessfully! ##\n####################################################\nThe exit status of the task that caused the workflow execution to fail was: $exitStatus.\nThe full error message was:\n\n${errorReport}\n\"\"\"\n} %>\n\n\nThe workflow was completed at $dateComplete (duration: $duration)\n\nThe command used to launch the workflow was as follows:\n\n $commandLine\n\n\n\nPipeline Configuration:\n-----------------------\n<% out << summary.collect{ k,v -> \" - $k: $v\" }.join(\"\\n\") %>\n\n--\nnf-core/atacseq\nhttps://github.com/nf-core/atacseq\n" }, { "path": "assets/methods_description_template.yml", "content": "id: \"nf-core-atacseq-methods-description\"\ndescription: \"Suggested text and references to use when describing pipeline usage within the methods section of a publication.\"\nsection_name: \"nf-core/atacseq Methods Description\"\nsection_href: \"https://github.com/nf-core/atacseq\"\nplot_type: \"html\"\n## TODO nf-core: Update the HTML below to your preferred methods description, e.g. add publication citation for this pipeline\n## You inject any metadata in the Nextflow '${workflow}' object\ndata: |\n

Methods

\n

Data was processed using nf-core/atacseq v${workflow.manifest.version} ${doi_text} of the nf-core collection of workflows (Ewels et al., 2020), utilising reproducible software environments from the Bioconda (Grüning et al., 2018) and Biocontainers (da Veiga Leprevost et al., 2017) projects.

\n

The pipeline was executed with Nextflow v${workflow.nextflow.version} (Di Tommaso et al., 2017) with the following command:

\n 
${workflow.commandLine}
\n

${tool_citations}

\n

References

\n
    \n
  • Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow enables reproducible computational workflows. Nature Biotechnology, 35(4), 316-319. doi: 10.1038/nbt.3820
    • \n
  • Ewels, P. A., Peltzer, A., Fillinger, S., Patel, H., Alneberg, J., Wilm, A., Garcia, M. U., Di Tommaso, P., & Nahnsen, S. (2020). The nf-core framework for community-curated bioinformatics pipelines. Nature Biotechnology, 38(3), 276-278. doi: 10.1038/s41587-020-0439-x
    • \n
  • Grüning, B., Dale, R., Sjödin, A., Chapman, B. A., Rowe, J., Tomkins-Tinch, C. H., Valieris, R., Köster, J., & Bioconda Team. (2018). Bioconda: sustainable and comprehensive software distribution for the life sciences. Nature Methods, 15(7), 475–476. doi: 10.1038/s41592-018-0046-7
    • \n
  • da Veiga Leprevost, F., Grüning, B. A., Alves Aflitos, S., Röst, H. L., Uszkoreit, J., Barsnes, H., Vaudel, M., Moreno, P., Gatto, L., Weber, J., Bai, M., Jimenez, R. C., Sachsenberg, T., Pfeuffer, J., Vera Alvarez, R., Griss, J., Nesvizhskii, A. I., & Perez-Riverol, Y. (2017). BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics (Oxford, England), 33(16), 2580–2582. doi: 10.1093/bioinformatics/btx192
    • \n ${tool_bibliography}\n
\n
\n
Notes:
\n
    \n ${nodoi_text}\n
  • The command above does not include parameters contained in any configs or profiles that may have been used. Ensure the config file is also uploaded with your publication!
    • \n
  • You should also cite all software used within this run. Check the \"Software Versions\" of this report to get version information.
    • \n
\n
\n" }, { "path": "assets/multiqc/merged_library_deseq2_clustering_header.txt", "content": "#id: 'mlib_deseq2_clustering'\n#section_name: 'MERGED LIB: DESeq2 sample similarity'\n#description: \"Matrix is generated from clustering with Euclidean distances between\n#\t DESeq2\n# rlog values for each sample\n# in the deseq2_qc.r script.\"\n#plot_type: 'heatmap'\n#anchor: 'mlib_deseq2_clustering'\n#pconfig:\n# title: 'DESeq2: Heatmap of the sample-to-sample distances'\n# xlab: True\n# reverseColors: True\n" }, { "path": "assets/multiqc/merged_library_deseq2_pca_header.txt", "content": "#id: 'mlib_deseq2_pca'\n#section_name: 'MERGED LIB: DESeq2 PCA plot'\n#description: \"PCA plot of the samples in the experiment.\n# These values are calculated using DESeq2\n# in the deseq2_qc.r script.\"\n#plot_type: 'scatter'\n#anchor: 'mlib_deseq2_pca'\n#pconfig:\n# title: 'DESeq2: Principal component plot'\n# xlab: PC1\n# ylab: PC2\n" }, { "path": "assets/multiqc/merged_library_frip_score_header.txt", "content": "#id: 'mlib_frip_score'\n#section_name: 'MERGED LIB: MACS2 peak FRiP score'\n#description: \"is generated by calculating the fraction of all mapped reads that fall\n# into the MACS2 called peak regions. A read must overlap a peak by at least 20% to be counted.\n# See FRiP score.\"\n#plot_type: 'bargraph'\n#anchor: 'mlib_frip_score'\n#pconfig:\n# title: 'FRiP score'\n# ylab: 'FRiP score'\n# ymax: 1\n# ymin: 0\n# tt_decimals: 2\n# cpswitch: False\n" }, { "path": "assets/multiqc/merged_library_peak_annotation_header.txt", "content": "#id: 'mlib_peak_annotation'\n#section_name: 'MERGED LIB: HOMER peak annotation'\n#description: \"is generated by calculating the proportion of peaks assigned to genomic features by\n# HOMER annotatePeaks.pl.\"\n#plot_type: 'bargraph'\n#anchor: 'mlib_peak_annotation'\n#pconfig:\n# title: 'Peak to feature proportion'\n# ylab: 'Peak count'\n" }, { "path": "assets/multiqc/merged_library_peak_count_header.txt", "content": "#id: 'mlib_peak_count'\n#section_name: 'MERGED LIB: MACS2 peak count'\n#description: \"is calculated from total number of peaks called by\n#\t MACS2\"\n#plot_type: 'bargraph'\n#anchor: 'mlib_peak_count'\n#pconfig:\n# title: 'Total peak count'\n# ylab: 'Peak count'\n# cpswitch: False\n" }, { "path": "assets/multiqc/merged_replicate_deseq2_clustering_header.txt", "content": "#id: 'mrep_deseq2_clustering'\n#section_name: 'MERGED REP: DESeq2 sample similarity'\n#description: \"Matrix is generated from clustering with Euclidean distances between\n#\t DESeq2\n# rlog values for each sample\n# in the deseq2_qc.r script.\"\n#plot_type: 'heatmap'\n#anchor: 'mrep_deseq2_clustering'\n#pconfig:\n# title: 'DESeq2: Heatmap of the sample-to-sample distances'\n# xlab: True\n# reverseColors: True\n" }, { "path": "assets/multiqc/merged_replicate_deseq2_pca_header.txt", "content": "#id: 'mrep_deseq2_pca'\n#section_name: 'MERGED REP: DESeq2 PCA plot'\n#description: \"PCA plot of the samples in the experiment.\n# These values are calculated using DESeq2\n# in the deseq2_qc.r script.\"\n#plot_type: 'scatter'\n#anchor: 'mrep_deseq2_pca'\n#pconfig:\n# title: 'DESeq2: Principal component plot'\n# xlab: PC1\n# ylab: PC2\n" }, { "path": "assets/multiqc/merged_replicate_frip_score_header.txt", "content": "#id: 'mrep_frip_score'\n#section_name: 'MERGED REP: MACS2 peak FRiP score'\n#description: \"is generated by calculating the fraction of all mapped reads that fall\n# into the MACS2 called peak regions. A read must overlap a peak by at least 20% to be counted.\n# See FRiP score.\"\n#plot_type: 'bargraph'\n#anchor: 'mrep_frip_score'\n#pconfig:\n# title: 'FRiP score'\n# ylab: 'FRiP score'\n# ymax: 1\n# ymin: 0\n# tt_decimals: 2\n# cpswitch: False\n" }, { "path": "assets/multiqc/merged_replicate_peak_annotation_header.txt", "content": "#id: 'mrep_peak_annotation'\n#section_name: 'MERGED REP: HOMER peak annotation'\n#description: \"is generated by calculating the proportion of peaks assigned to genomic features by\n# HOMER annotatePeaks.pl.\"\n#plot_type: 'bargraph'\n#anchor: 'mrep_peak_annotation'\n#pconfig:\n# title: 'Peak to feature proportion'\n# ylab: 'Peak count'\n" }, { "path": "assets/multiqc/merged_replicate_peak_count_header.txt", "content": "#id: 'mrep_peak_count'\n#section_name: 'MERGED REP: MACS2 Peak count'\n#description: \"is calculated from total number of peaks called by\n#\t MACS2\"\n#plot_type: 'bargraph'\n#anchor: 'mrep_peak_count'\n#pconfig:\n# title: 'Total peak count'\n# ylab: 'Peak count'\n# cpswitch: False\n" }, { "path": "assets/multiqc_config.yml", "content": "report_comment: >\n This report has been generated by the nf-core/atacseq\n analysis pipeline. For information about how to interpret these results, please see the\n documentation.\n\ndata_format: \"yaml\"\n\nexport_plots: true\n\nrun_modules:\n - custom_content\n - fastqc\n - cutadapt\n - samtools\n - picard\n - preseq\n - featureCounts\n - deeptools\n\nexclude_modules:\n - \"general_stats\"\n\nmodule_order:\n - fastqc:\n name: \"LIB: FastQC (raw)\"\n info: \"This section of the report shows FastQC results before adapter trimming for individual libraries.\"\n path_filters:\n - \"./fastqc/*.zip\"\n - cutadapt:\n name: \"LIB: Cutadapt (trimmed)\"\n info: \"This section of the report shows the length of trimmed reads by Cutadapt for individual libraries.\"\n - fastqc:\n name: \"LIB: FastQC (trimmed)\"\n info: \"This section of the report shows FastQC results after adapter trimming for individual libraries.\"\n path_filters:\n - \"./trimgalore/fastqc/*.zip\"\n - samtools:\n name: \"LIB: SAMTools\"\n info: \"This section of the report shows SAMTools results for individual libraries.\"\n path_filters:\n - \"./alignment/library/*\"\n - samtools:\n name: \"MERGED LIB: SAMTools (unfiltered)\"\n info: \"This section of the report shows SAMTools results after merging libraries and before filtering.\"\n path_filters:\n - \"./alignment/merged_library/unfiltered/*.mLb.mkD.sorted*\"\n - picard:\n name: \"MERGED LIB: Picard (unfiltered)\"\n info: \"This section of the report shows picard results after merging libraries and before filtering.\"\n path_filters:\n - \"./alignment/merged_library/unfiltered/picard_metrics/*\"\n - preseq:\n name: \"MERGED LIB: Preseq (unfiltered)\"\n info: \"This section of the report shows Preseq results after merging libraries and before filtering.\"\n - samtools:\n name: \"MERGED LIB: SAMTools (filtered)\"\n info: \"This section of the report shows SAMTools results after merging libraries and after filtering.\"\n path_filters:\n - \"./alignment/merged_library/filtered/*.mLb.clN.sorted*\"\n - picard:\n name: \"MERGED LIB: Picard (filtered)\"\n info: \"This section of the report shows picard results after merging libraries and after filtering.\"\n path_filters:\n - \"./alignment/merged_library/filtered/picard_metrics/*\"\n - deeptools:\n name: \"MERGED LIB: deepTools\"\n anchor: \"mlib_deeptools\"\n info: \"This section of the report shows QC plots generated by deepTools.\"\n - featureCounts:\n name: \"MERGED LIB: featureCounts\"\n anchor: \"mlib_featurecounts\"\n info: \"This section of the report shows featureCounts results for the number of reads assigned to merged library consensus peaks.\"\n path_filters:\n - \"./macs2/merged_library/featurecounts/*.summary\"\n - samtools:\n name: \"MERGED REP: SAMTools\"\n info: \"This section of the report shows SAMTools results after merging replicates and filtering.\"\n path_filters:\n - \"./alignment/merged_replicate/*\"\n - picard:\n name: \"MERGED REP: Picard\"\n anchor: \"mrep_picard\"\n info: \"This section of the report shows picard results after merging libraries and before filtering.\"\n path_filters:\n - \"./alignment/merged_replicate/picard_metrics/*\"\n - featureCounts:\n name: \"MERGED REP: featureCounts\"\n anchor: \"mrep_featurecounts\"\n info: \"This section of the report shows featureCounts results for the number of reads assigned to merged replicate consensus peaks.\"\n path_filters:\n - \"./macs2/merged_replicate/featurecounts/*.summary\"\n\nreport_section_order:\n mlib_peak_count:\n before: mlib_deeptools\n mlib_frip_score:\n before: mlib_peak_count\n mlib_peak_annotation:\n before: mlib_frip_score\n mlib_featurecounts:\n before: mlib_peak_annotation\n mlib_deseq2_pca_1:\n before: mlib_featurecounts\n mlib_deseq2_clustering_1:\n before: mlib_deseq2_pca_1\n mrep_peak_count:\n before: mrep_picard\n mrep_frip_score:\n before: mrep_peak_count\n mrep_peak_annotation:\n before: mrep_frip_score\n mrep_featurecounts:\n before: mrep_peak_annotation\n mrep_deseq2_pca_1:\n before: mrep_featurecounts\n mrep_deseq2_clustering_1:\n before: mrep_deseq2_pca_1\n \"nf-core-atacseq-methods-description\":\n order: -1000\n software_versions:\n order: -1001\n \"nf-core-atacseq-summary\":\n order: -1002\n\ncustom_plot_config:\n picard_insert_size:\n cpswitch_c_active: False\n smooth_points: 1000\n featurecounts:\n cpswitch_c_active: False\n featurecounts-1:\n cpswitch_c_active: False\n\nextra_fn_clean_exts:\n - \"fastq.gz\"\n - \"_trimmed\"\n - \"_val\"\n - \"sorted.bam\"\n - \".Lb\"\n - \"mkD\"\n - \"clN\"\n - \"mLb\"\n - \"mRp\"\n - \"_peaks\"\n - \".FRiP\"\n - \".peak\"\n - \"lc_extrap\"\n\n# # Customise the module search patterns to speed up execution time\n# # - Skip module sub-tools that we are not interested in\n# # - Replace file-content searching with filename pattern searching\n# # - Don't add anything that is the same as the MultiQC default\n# # See https://multiqc.info/docs/#optimise-file-search-patterns for details\nsp:\n cutadapt:\n fn: \"*trimming_report.txt\"\n preseq:\n fn: \"*.lc_extrap.txt\"\n deeptools/plotFingerprintOutRawCounts:\n fn: \"*plotFingerprint*\"\n deeptools/plotProfile:\n fn: \"*plotProfile*\"\n" }, { "path": "assets/samplesheet.csv", "content": "sample,fastq_1,fastq_2,replicate\nCONTROL,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz,1\nCONTROL,AEG588A2_S2_L002_R1_001.fastq.gz,AEG588A2_S2_L002_R2_001.fastq.gz,2\nCONTROL,AEG588A3_S3_L002_R1_001.fastq.gz,AEG588A3_S3_L002_R2_001.fastq.gz,3\nTREATMENT,AEG588A4_S4_L003_R1_001.fastq.gz,,1\nTREATMENT,AEG588A5_S5_L003_R1_001.fastq.gz,,2\nTREATMENT,AEG588A6_S6_L003_R1_001.fastq.gz,,3\nTREATMENT,AEG588A6_S6_L004_R1_001.fastq.gz,,3\n" }, { "path": "assets/schema_input.json", "content": "{\n \"$schema\": \"http://json-schema.org/draft-07/schema\",\n \"$id\": \"https://raw.githubusercontent.com/nf-core/atacseq/master/assets/schema_input.json\",\n \"title\": \"nf-core/atacseq pipeline - params.input schema\",\n \"description\": \"Schema for the file provided with params.input\",\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"sample\": {\n \"type\": \"string\",\n \"pattern\": \"^\\\\S+$\",\n \"errorMessage\": \"Sample name must be provided and cannot contain spaces\"\n },\n \"fastq_1\": {\n \"type\": \"string\",\n \"pattern\": \"^\\\\S+\\\\.f(ast)?q\\\\.gz$\",\n \"errorMessage\": \"FastQ file for reads 1 must be provided, cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz'\"\n },\n \"fastq_2\": {\n \"errorMessage\": \"FastQ file for reads 2 cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz'\",\n \"anyOf\": [\n {\n \"type\": \"string\",\n \"pattern\": \"^\\\\S+\\\\.f(ast)?q\\\\.gz$\"\n },\n {\n \"type\": \"string\",\n \"maxLength\": 0\n }\n ]\n },\n \"replicate\": {\n \"type\": \"integer\",\n \"pattern\": \"^[1-9][0-9]*$\",\n \"errorMessage\": \"Integer representing replicate number. Must start from 1...\"\n },\n \"control\": {\n \"type\": \"string\",\n \"pattern\": \"^\\\\S+$\",\n \"errorMessage\": \"Control entry cannot contain spaces\"\n },\n \"control_replicate\": {\n \"type\": \"integer\",\n \"pattern\": \"^[1-9][0-9]*$\",\n \"errorMessage\": \"Integer representing control's replicate number.\"\n }\n },\n \"required\": [\"sample\", \"fastq_1\", \"replicate\"]\n }\n}\n" }, { "path": "assets/sendmail_template.txt", "content": "To: $email\nSubject: $subject\nMime-Version: 1.0\nContent-Type: multipart/related;boundary=\"nfcoremimeboundary\"\n\n--nfcoremimeboundary\nContent-Type: text/html; charset=utf-8\n\n$email_html\n\n--nfcoremimeboundary\nContent-Type: image/png;name=\"nf-core-atacseq_logo.png\"\nContent-Transfer-Encoding: base64\nContent-ID: \nContent-Disposition: inline; filename=\"nf-core-atacseq_logo_light.png\"\n\n<% out << new File(\"$projectDir/assets/nf-core-atacseq_logo_light.png\").\n bytes.\n encodeBase64().\n toString().\n tokenize( '\\n' )*.\n toList()*.\n collate( 76 )*.\n collect { it.join() }.\n flatten().\n join( '\\n' ) %>\n\n<%\nif (mqcFile){\ndef mqcFileObj = new File(\"$mqcFile\")\nif (mqcFileObj.length() < mqcMaxSize){\nout << \"\"\"\n--nfcoremimeboundary\nContent-Type: text/html; name=\\\"multiqc_report\\\"\nContent-Transfer-Encoding: base64\nContent-ID: \nContent-Disposition: attachment; filename=\\\"${mqcFileObj.getName()}\\\"\n\n${mqcFileObj.\n bytes.\n encodeBase64().\n toString().\n tokenize( '\\n' )*.\n toList()*.\n collate( 76 )*.\n collect { it.join() }.\n flatten().\n join( '\\n' )}\n\"\"\"\n}}\n%>\n\n--nfcoremimeboundary--\n" }, { "path": "assets/slackreport.json", "content": "{\n \"attachments\": [\n {\n \"fallback\": \"Plain-text summary of the attachment.\",\n \"color\": \"<% if (success) { %>good<% } else { %>danger<%} %>\",\n \"author_name\": \"nf-core/atacseq v${version} - ${runName}\",\n \"author_icon\": \"https://www.nextflow.io/docs/latest/_static/favicon.ico\",\n \"text\": \"<% if (success) { %>Pipeline completed successfully!<% } else { %>Pipeline completed with errors<% } %>\",\n \"fields\": [\n {\n \"title\": \"Command used to launch the workflow\",\n \"value\": \"```${commandLine}```\",\n \"short\": false\n }\n <%\n if (!success) { %>\n ,\n {\n \"title\": \"Full error message\",\n \"value\": \"```${errorReport}```\",\n \"short\": false\n },\n {\n \"title\": \"Pipeline configuration\",\n \"value\": \"<% out << summary.collect{ k,v -> k == \"hook_url\" ? \"_${k}_: (_hidden_)\" : ( ( v.class.toString().contains('Path') || ( v.class.toString().contains('String') && v.contains('/') ) ) ? \"_${k}_: `${v}`\" : (v.class.toString().contains('DateTime') ? (\"_${k}_: \" + v.format(java.time.format.DateTimeFormatter.ofLocalizedDateTime(java.time.format.FormatStyle.MEDIUM))) : \"_${k}_: ${v}\") ) }.join(\",\\n\") %>\",\n \"short\": false\n }\n <% }\n %>\n ],\n \"footer\": \"Completed at <% out << dateComplete.format(java.time.format.DateTimeFormatter.ofLocalizedDateTime(java.time.format.FormatStyle.MEDIUM)) %> (duration: ${duration})\"\n }\n ]\n}\n" }, { "path": "bin/bampe_rm_orphan.py", "content": "#!/usr/bin/env python3\n\n###############################################################################\n###############################################################################\n## Created on February 1st 2017 to remove singletons from paired-end BAM file\n###############################################################################\n###############################################################################\n\nimport os\nimport pysam\nimport errno\nimport argparse\n\n############################################\n############################################\n## PARSE ARGUMENTS\n############################################\n############################################\n\nDescription = (\n \"Remove singleton reads from paired-end BAM file i.e if read1 is present in BAM file without read 2 and vice versa.\"\n)\nEpilog = \"\"\"Example usage: bampe_rm_orphan.py \"\"\"\n\nargParser = argparse.ArgumentParser(description=Description, epilog=Epilog)\n\n## REQUIRED PARAMETERS\nargParser.add_argument(\"BAM_INPUT_FILE\", help=\"Input BAM file sorted by name.\")\nargParser.add_argument(\"BAM_OUTPUT_FILE\", help=\"Output BAM file sorted by name.\")\n\n## OPTIONAL PARAMETERS\nargParser.add_argument(\n \"-fr\",\n \"--only_fr_pairs\",\n dest=\"ONLY_FR_PAIRS\",\n help=\"Only keeps pairs that are in FR orientation on same chromosome.\",\n action=\"store_true\",\n)\nargs = argParser.parse_args()\n\n############################################\n############################################\n## HELPER FUNCTIONS\n############################################\n############################################\n\n\ndef makedir(path):\n if not len(path) == 0:\n try:\n os.makedirs(path)\n except OSError as exception:\n if exception.errno != errno.EEXIST:\n raise\n\n\n############################################\n############################################\n## MAIN FUNCTION\n############################################\n############################################\n\n\ndef bampe_rm_orphan(BAMIn, BAMOut, onlyFRPairs=False):\n ## SETUP DIRECTORY/FILE STRUCTURE\n OutDir = os.path.dirname(BAMOut)\n makedir(OutDir)\n\n ## COUNT VARIABLES\n totalReads = 0\n totalOutputPairs = 0\n totalSingletons = 0\n totalImproperPairs = 0\n\n ## ITERATE THROUGH BAM FILE\n EOF = 0\n SAMFin = pysam.AlignmentFile(BAMIn, \"rb\")\n SAMFout = pysam.AlignmentFile(BAMOut, \"wb\", header=SAMFin.header)\n iter = SAMFin.fetch(until_eof=True)\n currRead = next(iter)\n for read in iter:\n totalReads += 1\n if currRead.qname == read.qname:\n pair1 = currRead\n pair2 = read\n\n ## FILTER FOR READS ON SAME CHROMOSOME IN FR ORIENTATION\n if onlyFRPairs:\n if pair1.tid == pair2.tid:\n ## READ1 FORWARD AND READ2 REVERSE STRAND\n if not pair1.is_reverse and pair2.is_reverse:\n if pair1.reference_start <= pair2.reference_start:\n totalOutputPairs += 1\n SAMFout.write(pair1)\n SAMFout.write(pair2)\n else:\n totalImproperPairs += 1\n\n ## READ1 REVERSE AND READ2 FORWARD STRAND\n elif pair1.is_reverse and not pair2.is_reverse:\n if pair2.reference_start <= pair1.reference_start:\n totalOutputPairs += 1\n SAMFout.write(pair1)\n SAMFout.write(pair2)\n else:\n totalImproperPairs += 1\n\n else:\n totalImproperPairs += 1\n else:\n totalImproperPairs += 1\n else:\n totalOutputPairs += 1\n SAMFout.write(pair1)\n SAMFout.write(pair2)\n\n ## RESET COUNTER\n try:\n totalReads += 1\n currRead = next(iter)\n except:\n StopIteration\n EOF = 1\n\n ## READS WHERE ONLY ONE OF A PAIR IS IN FILE\n else:\n totalSingletons += 1\n pair1 = currRead\n currRead = read\n\n if not EOF:\n totalReads += 1\n totalSingletons += 1\n pair1 = currRead\n\n ## CLOSE ALL FILE HANDLES\n SAMFin.close()\n SAMFout.close()\n\n LogFile = os.path.join(OutDir, \"%s_bampe_rm_orphan.log\" % (os.path.basename(BAMOut[:-4])))\n SamLogFile = open(LogFile, \"w\")\n SamLogFile.write(\"\\n##############################\\n\")\n SamLogFile.write(\"FILES/DIRECTORIES\")\n SamLogFile.write(\"\\n##############################\\n\\n\")\n SamLogFile.write(\"Input File: \" + BAMIn + \"\\n\")\n SamLogFile.write(\"Output File: \" + BAMOut + \"\\n\")\n SamLogFile.write(\"\\n##############################\\n\")\n SamLogFile.write(\"OVERALL COUNTS\")\n SamLogFile.write(\"\\n##############################\\n\\n\")\n SamLogFile.write(\"Total Input Reads = \" + str(totalReads) + \"\\n\")\n SamLogFile.write(\"Total Output Pairs = \" + str(totalOutputPairs) + \"\\n\")\n SamLogFile.write(\"Total Singletons Excluded = \" + str(totalSingletons) + \"\\n\")\n SamLogFile.write(\"Total Improper Pairs Excluded = \" + str(totalImproperPairs) + \"\\n\")\n SamLogFile.write(\"\\n##############################\\n\")\n SamLogFile.close()\n\n\n############################################\n############################################\n## RUN FUNCTION\n############################################\n############################################\n\nbampe_rm_orphan(BAMIn=args.BAM_INPUT_FILE, BAMOut=args.BAM_OUTPUT_FILE, onlyFRPairs=args.ONLY_FR_PAIRS)\n\n############################################\n############################################\n############################################\n############################################\n" }, { "path": "bin/check_samplesheet.py", "content": "#!/usr/bin/env python3\n\nimport os\nimport sys\nimport argparse\n\n\ndef parse_args(args=None):\n Description = \"Reformat nf-core/atacseq samplesheet file and check its contents.\"\n Epilog = \"Example usage: python check_samplesheet.py \"\n\n parser = argparse.ArgumentParser(description=Description, epilog=Epilog)\n parser.add_argument(\"FILE_IN\", help=\"Input samplesheet file.\")\n parser.add_argument(\"FILE_OUT\", help=\"Output file.\")\n parser.add_argument(\"--with_control\", action=\"store_true\", help=\"shows output\")\n return parser.parse_args(args)\n\n\ndef make_dir(path):\n if len(path) > 0:\n try:\n os.makedirs(path)\n except OSError as exception:\n if exception.errno != errno.EEXIST:\n raise exception\n\n\ndef print_error(error, context=\"Line\", context_str=\"\"):\n error_str = \"ERROR: Please check samplesheet -> {}\".format(error)\n if context != \"\" and context_str != \"\":\n error_str = \"ERROR: Please check samplesheet -> {}\\n{}: '{}'\".format(\n error, context.strip(), context_str.strip()\n )\n print(error_str)\n sys.exit(1)\n\n\ndef check_samplesheet(file_in, file_out, with_control=False):\n \"\"\"\n This function checks that the samplesheet follows the following structure:\n sample,fastq_1,fastq_2,replicate\n OSMOTIC_STRESS_T0,s3://nf-core-awsmegatests/atacseq/input_data/minimal/GSE66386/SRR1822153_1.fastq.gz,s3://nf-core-awsmegatests/atacseq/input_data/minimal/GSE66386/SRR1822153_2.fastq.gz,1\n OSMOTIC_STRESS_T0,s3://nf-core-awsmegatests/atacseq/input_data/minimal/GSE66386/SRR1822154_1.fastq.gz,s3://nf-core-awsmegatests/atacseq/input_data/minimal/GSE66386/SRR1822154_2.fastq.gz,2\n OSMOTIC_STRESS_T15,s3://nf-core-awsmegatests/atacseq/input_data/minimal/GSE66386/SRR1822157_1.fastq.gz,s3://nf-core-awsmegatests/atacseq/input_data/minimal/GSE66386/SRR1822157_2.fastq.gz,1\n OSMOTIC_STRESS_T15,s3://nf-core-awsmegatests/atacseq/input_data/minimal/GSE66386/SRR1822158_1.fastq.gz,s3://nf-core-awsmegatests/atacseq/input_data/minimal/GSE66386/SRR1822158_2.fastq.gz,1\n\n For an example see:\n https://raw.githubusercontent.com/nf-core/test-datasets/atacseq/samplesheet/v2.1/samplesheet_test.csv\n \"\"\"\n\n sample_mapping_dict = {}\n with open(file_in, \"r\", encoding=\"utf-8-sig\") as fin:\n ## Check header\n MIN_COLS = 3\n if with_control:\n HEADER = [\"sample\", \"fastq_1\", \"fastq_2\", \"replicate\", \"control\", \"control_replicate\"]\n else:\n HEADER = [\"sample\", \"fastq_1\", \"fastq_2\", \"replicate\"]\n header = [x.strip('\"') for x in fin.readline().strip().split(\",\")]\n if header[: len(HEADER)] != HEADER:\n print(f\"ERROR: Please check samplesheet header -> {','.join(header)} != {','.join(HEADER)}\")\n sys.exit(1)\n\n ## Check sample entries\n for line in fin:\n if line.strip():\n lspl = [x.strip().strip('\"') for x in line.strip().split(\",\")]\n\n # Check valid number of columns per row\n if len(lspl) < len(HEADER):\n print_error(\n \"Invalid number of columns (minimum = {})!\".format(len(HEADER)),\n \"Line\",\n line,\n )\n num_cols = len([x for x in lspl[: len(HEADER)] if x])\n if num_cols < MIN_COLS:\n print_error(\n \"Invalid number of populated columns (minimum = {})!\".format(MIN_COLS),\n \"Line\",\n line,\n )\n\n ## Check sample name entries\n sample, fastq_1, fastq_2, replicate = lspl[: len(HEADER) - 2 if with_control else len(HEADER)]\n control = lspl[len(HEADER) - 2] if with_control else \"\"\n control_replicate = lspl[len(HEADER) - 1] if with_control else \"\"\n if sample.find(\" \") != -1:\n print(f\"WARNING: Spaces have been replaced by underscores for sample: {sample}\")\n sample = sample.replace(\" \", \"_\")\n if not sample:\n print_error(\"Sample entry has not been specified!\", \"Line\", line)\n\n ## Check FastQ file extension\n for fastq in [fastq_1, fastq_2]:\n if fastq:\n if fastq.find(\" \") != -1:\n print_error(\"FastQ file contains spaces!\", \"Line\", line)\n if not fastq.endswith(\".fastq.gz\") and not fastq.endswith(\".fq.gz\"):\n print_error(\n \"FastQ file does not have extension '.fastq.gz' or '.fq.gz'!\",\n \"Line\",\n line,\n )\n\n ## Check replicate column is integer\n if not replicate.isdecimal():\n print_error(\"Replicate id not an integer!\", \"Line\", line)\n sys.exit(1)\n\n if with_control and control:\n if control.find(\" \") != -1:\n print(f\"WARNING: Spaces have been replaced by underscores for control: {control}\")\n control = control.replace(\" \", \"_\")\n if not control_replicate.isdecimal():\n print_error(\"Control replicate id not an integer!\", \"Line\", line)\n sys.exit(1)\n control = \"{}_REP{}\".format(control, control_replicate)\n\n ## Auto-detect paired-end/single-end\n sample_info = []\n ## Paired-end short reads\n if sample and fastq_1 and fastq_2:\n sample_info = [fastq_1, fastq_2, replicate, \"0\", control]\n ## Single-end short reads\n elif sample and fastq_1 and not fastq_2:\n sample_info = [fastq_1, fastq_2, replicate, \"1\", control]\n else:\n print_error(\"Invalid combination of columns provided!\", \"Line\", line)\n\n ## Create sample mapping dictionary = {sample: {replicate: [[ fastq_1, fastq_2, replicate, control, single_end ]]}}\n replicate = int(replicate)\n sample_info = sample_info + lspl[len(HEADER) :]\n if sample not in sample_mapping_dict:\n sample_mapping_dict[sample] = {}\n if replicate not in sample_mapping_dict[sample]:\n sample_mapping_dict[sample][replicate] = [sample_info]\n else:\n if sample_info in sample_mapping_dict[sample][replicate]:\n print_error(\"Samplesheet contains duplicate rows!\", \"Line\", line)\n else:\n sample_mapping_dict[sample][replicate].append(sample_info)\n\n ## Write validated samplesheet with appropriate columns\n if len(sample_mapping_dict) > 0:\n out_dir = os.path.dirname(file_out)\n make_dir(out_dir)\n with open(file_out, \"w\") as fout:\n if with_control:\n fout.write(\",\".join(HEADER[:-2] + [\"single_end\", \"control\"] + header[len(HEADER) :]) + \"\\n\")\n else:\n fout.write(\",\".join(HEADER + [\"single_end\", \"control\"] + header[len(HEADER) :]) + \"\\n\")\n\n for sample in sorted(sample_mapping_dict.keys()):\n ## Check that replicate ids are in format 1..\n uniq_rep_ids = sorted(list(set(sample_mapping_dict[sample].keys())))\n if len(uniq_rep_ids) != max(uniq_rep_ids) or 1 != min(uniq_rep_ids):\n print_error(\n \"Replicate ids must start with 1..!\",\n \"Sample\",\n \"{}, replicate ids: {}\".format(sample, \",\".join([str(x) for x in uniq_rep_ids])),\n )\n sys.exit(1)\n\n ## Check that multiple replicates are of the same datatype i.e. single-end / paired-end\n if not all(\n x[0][3] == sample_mapping_dict[sample][1][0][3] for x in sample_mapping_dict[sample].values()\n ):\n print_error(\n f\"Multiple replicates of a sample must be of the same datatype i.e. single-end or paired-end!\",\n \"Sample\",\n sample,\n )\n\n for replicate in sorted(sample_mapping_dict[sample].keys()):\n ## Check that multiple runs of the same sample are of the same datatype i.e. single-end / paired-end\n if not all(\n x[3] == sample_mapping_dict[sample][replicate][0][3]\n for x in sample_mapping_dict[sample][replicate]\n ):\n print_error(\n f\"Multiple runs of a sample must be of the same datatype i.e. single-end or paired-end!\",\n \"Sample\",\n sample,\n )\n\n for idx, val in enumerate(sample_mapping_dict[sample][replicate]):\n control = \"_REP\".join(val[4].split(\"_REP\")[:-1])\n control_replicate = val[4].split(\"_REP\")[-1]\n if control and (\n control not in sample_mapping_dict.keys()\n or int(control_replicate) not in sample_mapping_dict[control].keys()\n ):\n print_error(\n f\"Control identifier and replicate has to match a provided sample identifier and replicate!\",\n \"Control\",\n val[4],\n )\n\n ## Write to file\n for idx in range(len(sample_mapping_dict[sample][replicate])):\n fastq_files = sample_mapping_dict[sample][replicate][idx]\n sample_id = \"{}_REP{}_T{}\".format(sample, replicate, idx + 1)\n if len(fastq_files) == 1:\n fout.write(\",\".join([sample_id] + fastq_files) + \",\\n\")\n else:\n fout.write(\",\".join([sample_id] + fastq_files) + \"\\n\")\n else:\n print_error(f\"No entries to process!\", \"Samplesheet: {file_in}\")\n\n\ndef main(args=None):\n args = parse_args(args)\n check_samplesheet(args.FILE_IN, args.FILE_OUT, args.with_control)\n\n\nif __name__ == \"__main__\":\n sys.exit(main())\n" }, { "path": "bin/deseq2_qc.r", "content": "#!/usr/bin/env Rscript\n\n################################################\n################################################\n## REQUIREMENTS ##\n################################################\n################################################\n\n## PCA, HEATMAP AND SCATTERPLOTS FOR SAMPLES IN COUNTS FILE\n## - SAMPLE NAMES HAVE TO END IN e.g. \"_R1\" REPRESENTING REPLICATE ID. LAST 3 CHARACTERS OF SAMPLE NAME WILL BE TRIMMED TO OBTAIN GROUP ID FOR DESEQ2 COMPARISONS.\n## - PACKAGES BELOW NEED TO BE AVAILABLE TO LOAD WHEN RUNNING R\n\n################################################\n################################################\n## LOAD LIBRARIES ##\n################################################\n################################################\n\nlibrary(optparse)\nlibrary(DESeq2)\nlibrary(ggplot2)\nlibrary(RColorBrewer)\nlibrary(pheatmap)\n\n################################################\n################################################\n## PARSE COMMAND-LINE PARAMETERS ##\n################################################\n################################################\n\noption_list <- list(\n make_option(c(\"-i\", \"--count_file\" ), type=\"character\", default=NULL , metavar=\"path\" , help=\"Count file matrix where rows are genes and columns are samples.\" ),\n make_option(c(\"-f\", \"--count_col\" ), type=\"integer\" , default=2 , metavar=\"integer\", help=\"First column containing sample count data.\" ),\n make_option(c(\"-d\", \"--id_col\" ), type=\"integer\" , default=1 , metavar=\"integer\", help=\"Column containing identifiers to be used.\" ),\n make_option(c(\"-r\", \"--sample_suffix\" ), type=\"character\", default='' , metavar=\"string\" , help=\"Suffix to remove after sample name in columns e.g. '.rmDup.bam' if 'DRUG_R1.rmDup.bam'.\"),\n make_option(c(\"-o\", \"--outdir\" ), type=\"character\", default='./' , metavar=\"path\" , help=\"Output directory.\" ),\n make_option(c(\"-p\", \"--outprefix\" ), type=\"character\", default='deseq2', metavar=\"string\" , help=\"Output prefix.\" ),\n make_option(c(\"-v\", \"--vst\" ), type=\"logical\" , default=FALSE , metavar=\"boolean\", help=\"Run vst transform instead of rlog.\" ),\n make_option(c(\"-c\", \"--cores\" ), type=\"integer\" , default=1 , metavar=\"integer\", help=\"Number of cores.\" )\n)\n\nopt_parser <- OptionParser(option_list=option_list)\nopt <- parse_args(opt_parser)\n\nif (is.null(opt$count_file)){\n print_help(opt_parser)\n stop(\"Please provide a counts file.\", call.=FALSE)\n}\n\n################################################\n################################################\n## READ IN COUNTS FILE ##\n################################################\n################################################\n\ncount.table <- read.delim(file=opt$count_file,header=TRUE, row.names=NULL, skip=1, check.names=FALSE)\nrownames(count.table) <- count.table[,opt$id_col]\ncount.table <- count.table[,opt$count_col:ncol(count.table),drop=FALSE]\ncolnames(count.table) <- gsub(opt$sample_suffix,\"\",colnames(count.table))\ncolnames(count.table) <- gsub(pattern='\\\\.$', replacement='', colnames(count.table))\n\n################################################\n################################################\n## RUN DESEQ2 ##\n################################################\n################################################\n\nif (file.exists(opt$outdir) == FALSE) {\n dir.create(opt$outdir, recursive=TRUE)\n}\nsetwd(opt$outdir)\n\nsamples.vec <- colnames(count.table)\nname_components <- strsplit(samples.vec, \"_\")\nn_components <- length(name_components[[1]])\ndecompose <- n_components!=1 && all(sapply(name_components, length)==n_components)\ncoldata <- data.frame(samples.vec, sample=samples.vec, row.names=1)\nif (decompose) {\n groupings <- as.data.frame(lapply(1:n_components, function(i) sapply(name_components, \"[[\", i)))\n names(groupings) <- paste0(\"Group\", 1:n_components)\n n_distinct <- sapply(groupings, function(grp) length(unique(grp)))\n groupings <- groupings[n_distinct!=1 & n_distinct!=length(samples.vec)]\n if (ncol(groupings)!=0) {\n coldata <- cbind(coldata, groupings)\n } else {\n decompose <- FALSE\n }\n}\n\nDDSFile <- paste(opt$outprefix,\".dds.RData\",sep=\"\")\n\ncounts <- count.table[,samples.vec,drop=FALSE]\ndds <- DESeqDataSetFromMatrix(countData=round(counts), colData=coldata, design=~ 1)\ndds <- estimateSizeFactors(dds)\nif (min(dim(count.table))<=1) { # No point if only one sample, or one gene\n save(dds,file=DDSFile)\n saveRDS(dds, file=sub(\"\\\\.dds\\\\.RData$\", \".rds\", DDSFile))\n warning(\"Not enough samples or genes in counts file for PCA.\", call.=FALSE)\n quit(save = \"no\", status = 0, runLast = FALSE)\n}\nif (!opt$vst) {\n vst_name <- \"rlog\"\n rld <- rlog(dds)\n} else {\n vst_name <- \"vst\"\n rld <- varianceStabilizingTransformation(dds)\n}\n\nassay(dds, vst_name) <- assay(rld)\nsave(dds,file=DDSFile)\nsaveRDS(dds, file=sub(\"\\\\.dds\\\\.RData$\", \".rds\", DDSFile))\n\n################################################\n################################################\n## PLOT QC ##\n################################################\n################################################\n\n##' PCA pre-processeor\n##'\n##' Generate all the necessary information to plot PCA from a DESeq2 object\n##' in which an assay containing a variance-stabilised matrix of counts is\n##' stored. Copied from DESeq2::plotPCA, but with additional ability to\n##' say which assay to run the PCA on.\n##'\n##' @param object The DESeq2DataSet object.\n##' @param ntop number of top genes to use for principla components, selected by highest row variance.\n##' @param assay the name or index of the assay that stores the variance-stabilised data.\n##' @return A data.frame containing the projected data alongside the grouping columns.\n##' A 'percentVar' attribute is set which includes the percentage of variation each PC explains,\n##' and additionally how much the variation within that PC is explained by the grouping variable.\n##' @author Gavin Kelly\nplotPCA_vst <- function (object, ntop = 500, assay=length(assays(object))) {\n rv <- rowVars(assay(object, assay))\n select <- order(rv, decreasing = TRUE)[seq_len(min(ntop, length(rv)))]\n pca <- prcomp(t(assay(object, assay)[select, ]), center=TRUE, scale=FALSE)\n percentVar <- pca$sdev^2/sum(pca$sdev^2)\n df <- cbind( as.data.frame(colData(object)), pca$x)\n #Order points so extreme samples are more likely to get label\n ord <- order(abs(rank(df$PC1)-median(df$PC1)), abs(rank(df$PC2)-median(df$PC2)))\n df <- df[ord,]\n attr(df, \"percentVar\") <- data.frame(PC=seq(along=percentVar), percentVar=100*percentVar)\n return(df)\n}\n\nPlotFile <- paste(opt$outprefix,\".plots.pdf\",sep=\"\")\n\npdf(file=PlotFile, onefile=TRUE, width=7, height=7)\n## PCA\nntop <- c(500, Inf)\nfor (n_top_var in ntop) {\n pca.data <- plotPCA_vst(dds, assay=vst_name, ntop=n_top_var)\n percentVar <- round(attr(pca.data, \"percentVar\")$percentVar)\n plot_subtitle <- ifelse(n_top_var==Inf, \"All genes\", paste(\"Top\", n_top_var, \"genes\"))\n pl <- ggplot(pca.data, aes(PC1, PC2, label=paste0(\" \", sample, \" \"))) +\n geom_point() +\n geom_text(check_overlap=TRUE, vjust=0.5, hjust=\"inward\") +\n xlab(paste0(\"PC1: \",percentVar[1],\"% variance\")) +\n ylab(paste0(\"PC2: \",percentVar[2],\"% variance\")) +\n labs(title = paste0(\"First PCs on \", vst_name, \"-transformed data\"), subtitle = plot_subtitle) +\n theme(legend.position=\"top\",\n panel.grid.major = element_blank(),\n panel.grid.minor = element_blank(),\n panel.background = element_blank(),\n panel.border = element_rect(colour = \"black\", fill=NA, size=1))\n print(pl)\n\n if (decompose) {\n pc_names <- paste0(\"PC\", attr(pca.data, \"percentVar\")$PC)\n long_pc <- reshape(pca.data, varying=pc_names, direction=\"long\", sep=\"\", timevar=\"component\", idvar=\"pcrow\")\n long_pc <- subset(long_pc, component<=5)\n long_pc_grp <- reshape(long_pc, varying=names(groupings), direction=\"long\", sep=\"\", timevar=\"grouper\")\n long_pc_grp <- subset(long_pc_grp, grouper<=5)\n long_pc_grp$component <- paste(\"PC\", long_pc_grp$component)\n long_pc_grp$grouper <- paste0(long_pc_grp$grouper, c(\"st\",\"nd\",\"rd\",\"th\",\"th\")[long_pc_grp$grouper], \" prefix\")\n pl <- ggplot(long_pc_grp, aes(x=Group, y=PC)) +\n geom_point() +\n stat_summary(fun=mean, geom=\"line\", aes(group = 1)) +\n labs(x=NULL, y=NULL, subtitle = plot_subtitle, title=\"PCs split by sample-name prefixes\") +\n facet_grid(component~grouper, scales=\"free_x\") +\n scale_x_discrete(guide = guide_axis(n.dodge = 3))\n print(pl)\n }\n} # at end of loop, we'll be using the user-defined ntop if any, else all genes\n\n## WRITE PC1 vs PC2 VALUES TO FILE\npca.vals <- pca.data[,c(\"PC1\",\"PC2\")]\ncolnames(pca.vals) <- paste0(colnames(pca.vals), \": \", percentVar[1:2], '% variance')\npca.vals <- cbind(sample = rownames(pca.vals), pca.vals)\nwrite.table(pca.vals, file = paste(opt$outprefix, \".pca.vals.txt\", sep=\"\"),\n row.names = FALSE, col.names = TRUE, sep = \"\\t\", quote = TRUE)\n\n## SAMPLE CORRELATION HEATMAP\nsampleDists <- dist(t(assay(dds, vst_name)))\nsampleDistMatrix <- as.matrix(sampleDists)\ncolors <- colorRampPalette( rev(brewer.pal(9, \"Blues\")) )(255)\npheatmap(\n sampleDistMatrix,\n clustering_distance_rows=sampleDists,\n clustering_distance_cols=sampleDists,\n col=colors,\n main=paste(\"Euclidean distance between\", vst_name, \"of samples\")\n)\n\n## WRITE SAMPLE DISTANCES TO FILE\nwrite.table(cbind(sample = rownames(sampleDistMatrix), sampleDistMatrix),file=paste(opt$outprefix, \".sample.dists.txt\", sep=\"\"),\n row.names=FALSE, col.names=TRUE, sep=\"\\t\", quote=FALSE)\ndev.off()\n\n################################################\n################################################\n## SAVE SIZE FACTORS ##\n################################################\n################################################\n\nSizeFactorsDir <- \"size_factors/\"\nif (file.exists(SizeFactorsDir) == FALSE) {\n dir.create(SizeFactorsDir, recursive=TRUE)\n}\n\nNormFactorsFile <- paste(SizeFactorsDir,opt$outprefix, \".size_factors.RData\", sep=\"\")\n\nnormFactors <- sizeFactors(dds)\nsave(normFactors, file=NormFactorsFile)\n\nfor (name in names(sizeFactors(dds))) {\n sizeFactorFile <- paste(SizeFactorsDir,name, \".size_factors.txt\", sep=\"\")\n write(as.numeric(sizeFactors(dds)[name]), file=sizeFactorFile)\n}\n\n################################################\n################################################\n## R SESSION INFO ##\n################################################\n################################################\n\nRLogFile <- \"R_sessionInfo.log\"\n\nsink(RLogFile)\na <- sessionInfo()\nprint(a)\nsink()\n\n################################################\n################################################\n################################################\n################################################\n" }, { "path": "bin/get_autosomes.py", "content": "#!/usr/bin/env python\n\n#######################################################################\n#######################################################################\n## Created on January 23rd 2019 to get autosomes from samtools FAI file\n#######################################################################\n#######################################################################\n\nimport os\nimport errno\nimport argparse\n\n############################################\n############################################\n## PARSE ARGUMENTS\n############################################\n############################################\n\nDescription = \"Get a list of autosomes from FAI file for assembly and write to file.\"\nEpilog = \"\"\"Example usage: python get_autosomes.py \"\"\"\n\nargParser = argparse.ArgumentParser(description=Description, epilog=Epilog)\n\n## REQUIRED PARAMETERS\nargParser.add_argument(\"FAI_FILE\", help=\"FAI input file.\")\nargParser.add_argument(\"OUT_FILE\", help=\"Output file containing one chromosome per line.\")\nargs = argParser.parse_args()\n\n############################################\n############################################\n## HELPER FUNCTIONS\n############################################\n############################################\n\n\ndef makedir(path):\n if not len(path) == 0:\n try:\n os.makedirs(path)\n except OSError as exception:\n if exception.errno != errno.EEXIST:\n raise\n\n\n############################################\n############################################\n## MAIN FUNCTION\n############################################\n############################################\n\n## TESTED WITH IGENOMES ASSEMBLIES FOR:\n# Arabidopsis_thaliana\n# Caenorhabditis_elegans\n# Danio_rerio\n# Drosophila_melanogaster\n# Enterobacteriophage_lambda\n# Escherichia_coli_K_12_DH10B\n# Escherichia_coli_K_12_MG1655\n# Gallus_gallus\n# Homo_sapiens\n# Mus_musculus\n# Mycobacterium_tuberculosis_H37RV\n# PhiX\n# Rattus_norvegicus\n# Saccharomyces_cerevisiae\n# Schizosaccharomyces_pombe\n# Staphylococcus_aureus_NCTC_8325\n\n\ndef get_autosomes(FAIFile, OutFile):\n makedir(os.path.dirname(OutFile))\n\n ## READ IN CHROMOSOME IDS\n chrList = []\n fin = open(FAIFile, \"r\")\n while True:\n line = fin.readline()\n if line:\n chrList.append(line.strip().split(\"\\t\")[0])\n else:\n fin.close()\n break\n\n ## REMOVE EXACT MATCHES TO MITOCHONDRIAL, SEX AND OTHER NON-AUTOSOMAL CHROMOSOMES\n exactMatch = [\"y\", \"w\", \"z\", \"m\", \"mt\", \"mtdna\", \"pt\", \"mtr\", \"2-micron\", \"ebv\"]\n if (\n \"VI\" not in chrList and \"chrVI\" not in chrList\n ): ## Caenorhabditis elegans has roman numerals and chrX but only 5 chromosomes!\n exactMatch += [\"x\"]\n filteredList = [x for x in chrList if x.lower() not in exactMatch and x.lower().lstrip(\"chr\") not in exactMatch]\n\n ## REMOVE INEXACT MATCHS TO SMALLER/RANDOM HUMAN CONTIGS\n fuzzyMatch = [\"chrUn\", \"random\", \"v1\", \"v2\", \"kn707\", \"jtfh\"]\n filteredList = [x for x in filteredList if not any(y in x.lower() for y in fuzzyMatch)]\n\n ## WRITE TO FILE\n fout = open(OutFile, \"w\")\n for chrom in filteredList:\n fout.write(\"%s\\n\" % (chrom))\n fout.close()\n\n\n############################################\n############################################\n## RUN FUNCTION\n############################################\n############################################\n\nget_autosomes(FAIFile=args.FAI_FILE, OutFile=args.OUT_FILE)\n\n############################################\n############################################\n############################################\n############################################\n" }, { "path": "bin/gtf2bed", "content": "#!/usr/bin/env perl\n\n# Copyright (c) 2011 Erik Aronesty (erik@q32.com)\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitation the rights\n# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n# copies of the Software, and to permit persons to whom the Software is\n# furnished to do so, subject to the following conditions:\n#\n# The above copyright notice and this permission notice shall be included in\n# all copies or substantial portions of the Software.\n#\n# THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n# THE SOFTWARE.\n#\n# ALSO, IT WOULD BE NICE IF YOU LET ME KNOW YOU USED IT.\n\nuse Getopt::Long;\n\nmy $extended;\nGetOptions(\"x\"=>\\$extended);\n\n$in = shift @ARGV;\n\nmy $in_cmd =($in =~ /\\.gz$/ ? \"gunzip -c $in|\" : $in =~ /\\.zip$/ ? \"unzip -p $in|\" : \"$in\") || die \"Can't open $in: $!\\n\";\nopen IN, $in_cmd;\n\nwhile () {\n $gff = 2 if /^##gff-version 2/;\n $gff = 3 if /^##gff-version 3/;\n next if /^#/ && $gff;\n\n s/\\s+$//;\n # 0-chr 1-src 2-feat 3-beg 4-end 5-scor 6-dir 7-fram 8-attr\n my @f = split /\\t/;\n if ($gff) {\n # most ver 2's stick gene names in the id field\n ($id) = $f[8]=~ /\\bID=\"([^\"]+)\"/;\n # most ver 3's stick unquoted names in the name field\n ($id) = $f[8]=~ /\\bName=([^\";]+)/ if !$id && $gff == 3;\n } else {\n ($id) = $f[8]=~ /transcript_id \"([^\"]+)\"/;\n }\n\n next unless $id && $f[0];\n\n if ($f[2] eq 'exon') {\n die \"no position at exon on line $.\" if ! $f[3];\n # gff3 puts :\\d in exons sometimes\n $id =~ s/:\\d+$// if $gff == 3;\n push @{$exons{$id}}, \\@f;\n # save lowest start\n $trans{$id} = \\@f if !$trans{$id};\n } elsif ($f[2] eq 'start_codon') {\n #optional, output codon start/stop as \"thick\" region in bed\n $sc{$id}->[0] = $f[3];\n } elsif ($f[2] eq 'stop_codon') {\n $sc{$id}->[1] = $f[4];\n } elsif ($f[2] eq 'miRNA' ) {\n $trans{$id} = \\@f if !$trans{$id};\n push @{$exons{$id}}, \\@f;\n }\n}\n\nfor $id (\n # sort by chr then pos\n sort {\n $trans{$a}->[0] eq $trans{$b}->[0] ?\n $trans{$a}->[3] <=> $trans{$b}->[3] :\n $trans{$a}->[0] cmp $trans{$b}->[0]\n } (keys(%trans)) ) {\n my ($chr, undef, undef, undef, undef, undef, $dir, undef, $attr, undef, $cds, $cde) = @{$trans{$id}};\n my ($cds, $cde);\n ($cds, $cde) = @{$sc{$id}} if $sc{$id};\n\n # sort by pos\n my @ex = sort {\n $a->[3] <=> $b->[3]\n } @{$exons{$id}};\n\n my $beg = $ex[0][3];\n my $end = $ex[-1][4];\n\n if ($dir eq '-') {\n # swap\n $tmp=$cds;\n $cds=$cde;\n $cde=$tmp;\n $cds -= 2 if $cds;\n $cde += 2 if $cde;\n }\n\n # not specified, just use exons\n $cds = $beg if !$cds;\n $cde = $end if !$cde;\n\n # adjust start for bed\n --$beg; --$cds;\n\n my $exn = @ex;\t\t\t\t\t\t\t\t\t\t\t\t# exon count\n my $exst = join \",\", map {$_->[3]-$beg-1} @ex;\t\t\t\t# exon start\n my $exsz = join \",\", map {$_->[4]-$_->[3]+1} @ex;\t\t\t# exon size\n\n my $gene_id;\n my $extend = \"\";\n if ($extended) {\n ($gene_id) = $attr =~ /gene_name \"([^\"]+)\"/;\n ($gene_id) = $attr =~ /gene_id \"([^\"]+)\"/ unless $gene_id;\n $extend=\"\\t$gene_id\";\n }\n # added an extra comma to make it look exactly like ucsc's beds\n print \"$chr\\t$beg\\t$end\\t$id\\t0\\t$dir\\t$cds\\t$cde\\t0\\t$exn\\t$exsz,\\t$exst,$extend\\n\";\n}\n\n\nclose IN;\n" }, { "path": "bin/igv_files_to_session.py", "content": "#!/usr/bin/env python3\n\n#######################################################################\n#######################################################################\n## Created on July 4th 2018 to create IGV session file from file list\n#######################################################################\n#######################################################################\n\nimport os\nimport errno\nimport argparse\n\n############################################\n############################################\n## PARSE ARGUMENTS\n############################################\n############################################\n\nDescription = 'Create IGV session file from a list of files and associated colours - \".bed\", \".bw\", \".bigwig\", \".tdf\", \".gtf\" files currently supported.'\nEpilog = \"\"\"Example usage: python igv_files_to_session.py \"\"\"\n\nargParser = argparse.ArgumentParser(description=Description, epilog=Epilog)\n\n## REQUIRED PARAMETERS\nargParser.add_argument(\"XML_OUT\", help=\"XML output file.\")\nargParser.add_argument(\n \"LIST_FILE\", help=\"Tab-delimited file containing two columns i.e. file_name\\tcolour. Header isnt required.\"\n)\nargParser.add_argument(\n \"GENOME\", help=\"Full path to genome fasta file or shorthand for genome available in IGV e.g. hg19.\"\n)\n\n## OPTIONAL PARAMETERS\nargParser.add_argument(\n \"-pp\",\n \"--path_prefix\",\n type=str,\n dest=\"PATH_PREFIX\",\n default=\"\",\n help=\"Path prefix to be added at beginning of all files in input list file.\",\n)\nargs = argParser.parse_args()\n\n############################################\n############################################\n## HELPER FUNCTIONS\n############################################\n############################################\n\n\ndef makedir(path):\n if not len(path) == 0:\n try:\n os.makedirs(path)\n except OSError as exception:\n if exception.errno != errno.EEXIST:\n raise\n\n\n############################################\n############################################\n## MAIN FUNCTION\n############################################\n############################################\n\n\ndef igv_files_to_session(XMLOut, ListFile, Genome, PathPrefix=\"\"):\n makedir(os.path.dirname(XMLOut))\n\n fileList = []\n fin = open(ListFile, \"r\")\n while True:\n line = fin.readline()\n if line:\n ifile, colour = line.strip().split(\"\\t\")\n if len(colour.strip()) == 0:\n colour = \"0,0,178\"\n fileList.append((PathPrefix.strip() + ifile, colour))\n else:\n break\n fout.close()\n\n ## ADD RESOURCES SECTION\n XMLStr = '\\n'\n XMLStr += '\\n' % (Genome)\n XMLStr += \"\\t\\n\"\n for ifile, colour in fileList:\n XMLStr += '\\t\\t\\n' % (ifile)\n XMLStr += \"\\t\\n\"\n\n ## ADD PANEL SECTION\n XMLStr += '\\t\\n'\n for ifile, colour in fileList:\n extension = os.path.splitext(ifile)[1].lower()\n if extension in [\".bed\", \".broadpeak\", \".narrowpeak\"]:\n XMLStr += (\n '\\t\\t\\n'\n % (ifile, os.path.basename(ifile))\n )\n elif extension in [\".bw\", \".bigwig\", \".tdf\"]:\n XMLStr += (\n '\\t\\t\\n'\n % (ifile, os.path.basename(ifile))\n )\n XMLStr += '\\t\\t\\t\\n'\n XMLStr += \"\\t\\t\\n\"\n elif extension in [\".gtf\"]:\n XMLStr += (\n '\\t\\t\\n'\n % (ifile, os.path.basename(ifile))\n )\n elif extension in [\".bam\"]:\n pass\n else:\n XMLStr += (\n '\\t\\t\\n'\n % (ifile, os.path.basename(ifile))\n )\n\n XMLStr += \"\\t\\n\"\n # XMLStr += '\\t\\n\\t\\t\\n\\t\\t\\n\\t\\t\\n\\t\\n'\n XMLStr += \"\"\n XMLOut = open(XMLOut, \"w\")\n XMLOut.write(XMLStr)\n XMLOut.close()\n\n\n############################################\n############################################\n## RUN FUNCTION\n############################################\n############################################\n\nigv_files_to_session(XMLOut=args.XML_OUT, ListFile=args.LIST_FILE, Genome=args.GENOME, PathPrefix=args.PATH_PREFIX)\n\n############################################\n############################################\n############################################\n############################################\n" }, { "path": "bin/macs2_merged_expand.py", "content": "#!/usr/bin/env python3\n\n#######################################################################\n#######################################################################\n## Created on June 29th 2018 to annotate merged peaks\n#######################################################################\n#######################################################################\n\nimport os\nimport errno\nimport argparse\n\n############################################\n############################################\n## PARSE ARGUMENTS\n############################################\n############################################\n\nDescription = \"Add sample boolean files and aggregate columns from merged MACS narrow or broad peak file.\"\nEpilog = \"\"\"Example usage: python macs2_merged_expand.py --is_narrow_peak --min_replicates 1\"\"\"\n\nargParser = argparse.ArgumentParser(description=Description, epilog=Epilog)\n\n## REQUIRED PARAMETERS\nargParser.add_argument(\"MERGED_INTERVAL_FILE\", help=\"Merged MACS2 interval file created using linux sort and mergeBed.\")\nargParser.add_argument(\n \"SAMPLE_NAME_LIST\",\n help=\"Comma-separated list of sample names as named in individual MACS2 broadPeak/narrowPeak output file e.g. SAMPLE_R1 for SAMPLE_R1_peak_1.\",\n)\nargParser.add_argument(\"OUTFILE\", help=\"Full path to output directory.\")\n\n## OPTIONAL PARAMETERS\nargParser.add_argument(\n \"-in\",\n \"--is_narrow_peak\",\n dest=\"IS_NARROW_PEAK\",\n help=\"Whether merged interval file was generated from narrow or broad peak files (default: False).\",\n action=\"store_true\",\n)\nargParser.add_argument(\n \"-mr\",\n \"--min_replicates\",\n type=int,\n dest=\"MIN_REPLICATES\",\n default=1,\n help=\"Minumum number of replicates per sample required to contribute to merged peak (default: 1).\",\n)\nargs = argParser.parse_args()\n\n############################################\n############################################\n## HELPER FUNCTIONS\n############################################\n############################################\n\n\ndef makedir(path):\n if not len(path) == 0:\n try:\n os.makedirs(path)\n except OSError as exception:\n if exception.errno != errno.EEXIST:\n raise\n\n\n############################################\n############################################\n## MAIN FUNCTION\n############################################\n############################################\n\n## MergedIntervalTxtFile is file created using commands below:\n## 1) broadPeak\n## sort -k1,1 -k2,2n | mergeBed -c 2,3,4,5,6,7,8,9 -o collapse,collapse,collapse,collapse,collapse,collapse,collapse,collapse > merged_peaks.txt\n## 2) narrowPeak\n## sort -k1,1 -k2,2n | mergeBed -c 2,3,4,5,6,7,8,9,10 -o collapse,collapse,collapse,collapse,collapse,collapse,collapse,collapse,collapse > merged_peaks.txt\n\n\ndef macs2_merged_expand(MergedIntervalTxtFile, SampleNameList, OutFile, isNarrow=False, minReplicates=1):\n makedir(os.path.dirname(OutFile))\n\n combFreqDict = {}\n totalOutIntervals = 0\n SampleNameList = sorted(SampleNameList)\n fin = open(MergedIntervalTxtFile, \"r\")\n fout = open(OutFile, \"w\")\n oFields = (\n [\"chr\", \"start\", \"end\", \"interval_id\", \"num_peaks\", \"num_samples\"]\n + [x + \".bool\" for x in SampleNameList]\n + [x + \".fc\" for x in SampleNameList]\n + [x + \".qval\" for x in SampleNameList]\n + [x + \".pval\" for x in SampleNameList]\n + [x + \".start\" for x in SampleNameList]\n + [x + \".end\" for x in SampleNameList]\n )\n if isNarrow:\n oFields += [x + \".summit\" for x in SampleNameList]\n fout.write(\"\\t\".join(oFields) + \"\\n\")\n while True:\n line = fin.readline()\n if line:\n lspl = line.strip().split(\"\\t\")\n\n chromID = lspl[0]\n mstart = int(lspl[1])\n mend = int(lspl[2])\n starts = [int(x) for x in lspl[3].split(\",\")]\n ends = [int(x) for x in lspl[4].split(\",\")]\n names = lspl[5].split(\",\")\n fcs = [float(x) for x in lspl[8].split(\",\")]\n pvals = [float(x) for x in lspl[9].split(\",\")]\n qvals = [float(x) for x in lspl[10].split(\",\")]\n summits = []\n if isNarrow:\n summits = [int(x) for x in lspl[11].split(\",\")]\n\n ## GROUP SAMPLES BY REMOVING TRAILING *_R*\n groupDict = {}\n for sID in [\"_\".join(x.split(\"_\")[:-2]) for x in names]:\n gID = \"_\".join(sID.split(\"_\")[:-1])\n if gID not in groupDict:\n groupDict[gID] = []\n if sID not in groupDict[gID]:\n groupDict[gID].append(sID)\n\n ## GET SAMPLES THAT PASS REPLICATE THRESHOLD\n passRepThreshList = []\n for gID, sIDs in groupDict.items():\n if len(sIDs) >= minReplicates:\n passRepThreshList += sIDs\n\n ## GET VALUES FROM INDIVIDUAL PEAK SETS\n fcDict = {}\n qvalDict = {}\n pvalDict = {}\n startDict = {}\n endDict = {}\n summitDict = {}\n for idx in range(len(names)):\n sample = \"_\".join(names[idx].split(\"_\")[:-2])\n if sample in passRepThreshList:\n if sample not in fcDict:\n fcDict[sample] = []\n fcDict[sample].append(str(fcs[idx]))\n if sample not in qvalDict:\n qvalDict[sample] = []\n qvalDict[sample].append(str(qvals[idx]))\n if sample not in pvalDict:\n pvalDict[sample] = []\n pvalDict[sample].append(str(pvals[idx]))\n if sample not in startDict:\n startDict[sample] = []\n startDict[sample].append(str(starts[idx]))\n if sample not in endDict:\n endDict[sample] = []\n endDict[sample].append(str(ends[idx]))\n if isNarrow:\n if sample not in summitDict:\n summitDict[sample] = []\n summitDict[sample].append(str(summits[idx]))\n\n samples = sorted(fcDict.keys())\n if samples != []:\n numSamples = len(samples)\n boolList = [\"TRUE\" if x in samples else \"FALSE\" for x in SampleNameList]\n fcList = [\";\".join(fcDict[x]) if x in samples else \"NA\" for x in SampleNameList]\n qvalList = [\";\".join(qvalDict[x]) if x in samples else \"NA\" for x in SampleNameList]\n pvalList = [\";\".join(pvalDict[x]) if x in samples else \"NA\" for x in SampleNameList]\n startList = [\";\".join(startDict[x]) if x in samples else \"NA\" for x in SampleNameList]\n endList = [\";\".join(endDict[x]) if x in samples else \"NA\" for x in SampleNameList]\n oList = [\n str(x)\n for x in [chromID, mstart, mend, \"Interval_\" + str(totalOutIntervals + 1), len(names), numSamples]\n + boolList\n + fcList\n + qvalList\n + pvalList\n + startList\n + endList\n ]\n if isNarrow:\n oList += [\";\".join(summitDict[x]) if x in samples else \"NA\" for x in SampleNameList]\n fout.write(\"\\t\".join(oList) + \"\\n\")\n\n tsamples = tuple(sorted(samples))\n if tsamples not in combFreqDict:\n combFreqDict[tsamples] = 0\n combFreqDict[tsamples] += 1\n totalOutIntervals += 1\n\n else:\n fin.close()\n fout.close()\n break\n\n ## WRITE FILE FOR INTERVAL INTERSECT ACROSS SAMPLES.\n ## COMPATIBLE WITH UPSETR PACKAGE.\n fout = open(OutFile[:-4] + \".intersect.txt\", \"w\")\n combFreqItems = sorted([(combFreqDict[x], x) for x in combFreqDict.keys()], reverse=True)\n for k, v in combFreqItems:\n fout.write(\"%s\\t%s\\n\" % (\"&\".join(v), k))\n fout.close()\n\n\n############################################\n############################################\n## RUN FUNCTION\n############################################\n############################################\n\nmacs2_merged_expand(\n MergedIntervalTxtFile=args.MERGED_INTERVAL_FILE,\n SampleNameList=args.SAMPLE_NAME_LIST.split(\",\"),\n OutFile=args.OUTFILE,\n isNarrow=args.IS_NARROW_PEAK,\n minReplicates=args.MIN_REPLICATES,\n)\n\n############################################\n############################################\n############################################\n############################################\n" }, { "path": "bin/plot_homer_annotatepeaks.r", "content": "#!/usr/bin/env Rscript\n\n################################################\n################################################\n## LOAD LIBRARIES ##\n################################################\n################################################\n\nlibrary(optparse)\nlibrary(ggplot2)\nlibrary(reshape2)\nlibrary(scales)\n\n################################################\n################################################\n## PARSE COMMAND-LINE PARAMETERS ##\n################################################\n################################################\n\noption_list <- list(make_option(c(\"-i\", \"--homer_files\"), type=\"character\", default=NULL, help=\"Comma-separated list of homer annotated text files.\", metavar=\"path\"),\n make_option(c(\"-s\", \"--sample_ids\"), type=\"character\", default=NULL, help=\"Comma-separated list of sample ids associated with homer annotated text files. Must be unique and in same order as homer files input.\", metavar=\"string\"),\n make_option(c(\"-o\", \"--outdir\"), type=\"character\", default='./', help=\"Output directory\", metavar=\"path\"),\n make_option(c(\"-p\", \"--outprefix\"), type=\"character\", default='homer_annotation', help=\"Output prefix\", metavar=\"string\"))\n\nopt_parser <- OptionParser(option_list=option_list)\nopt <- parse_args(opt_parser)\n\nif (is.null(opt$homer_files)){\n print_help(opt_parser)\n stop(\"At least one homer annotated file must be supplied\", call.=FALSE)\n}\nif (is.null(opt$sample_ids)){\n print_help(opt_parser)\n stop(\"Please provide sample ids associated with homer files.\", call.=FALSE)\n}\n\nif (file.exists(opt$outdir) == FALSE) {\n dir.create(opt$outdir,recursive=TRUE)\n}\n\nHomerFiles <- unlist(strsplit(opt$homer_files,\",\"))\nSampleIDs <- unlist(strsplit(opt$sample_ids,\",\"))\nif (length(HomerFiles) != length(SampleIDs)) {\n print_help(opt_parser)\n stop(\"Number of sample ids must equal number of homer annotated files.\", call.=FALSE)\n}\n\n################################################\n################################################\n## READ IN DATA ##\n################################################\n################################################\n\nplot.dat <- data.frame()\nplot.dist.dat <- data.frame()\nplot.feature.dat <- data.frame()\nfor (idx in 1:length(HomerFiles)) {\n\n sampleid = SampleIDs[idx]\n anno.dat <- read.csv(HomerFiles[idx], sep=\"\\t\", header=TRUE)\n anno.dat <- anno.dat[,c(\"Annotation\",\"Distance.to.TSS\",\"Nearest.PromoterID\")]\n\n ## REPLACE UNASSIGNED FEATURE ENTRIES WITH SENSIBLE VALUES\n unassigned <- which(is.na(as.character(anno.dat$Distance.to.TSS)))\n anno.dat$Distance.to.TSS[unassigned] <- 1000000\n\n anno.dat$Annotation <- as.character(anno.dat$Annotation)\n anno.dat$Annotation[unassigned] <- \"Unassigned\"\n anno.dat$Annotation <- as.factor(anno.dat$Annotation)\n\n anno.dat$Nearest.PromoterID <- as.character(anno.dat$Nearest.PromoterID)\n anno.dat$Nearest.PromoterID[unassigned] <- \"Unassigned\"\n anno.dat$Nearest.PromoterID <- as.factor(anno.dat$Nearest.PromoterID)\n\n anno.dat$name <- rep(sampleid,nrow(anno.dat))\n anno.dat$Distance.to.TSS <- abs(anno.dat$Distance.to.TSS) + 1\n plot.dat <- rbind(plot.dat,anno.dat)\n\n ## GET ANNOTATION COUNTS\n anno.freq <- as.character(lapply(strsplit(as.character(anno.dat$Annotation),\" \"), function(x) x[1]))\n anno.freq <- as.data.frame(table(anno.freq))\n colnames(anno.freq) <- c(\"feature\",sampleid)\n anno.melt <- melt(anno.freq)\n plot.feature.dat <- rbind(plot.feature.dat,anno.melt)\n\n ## GET CLOSEST INSTANCE OF GENE TO ANY GIVEN PEAK\n unique.gene.dat <- anno.dat[order(anno.dat$Distance.to.TSS),]\n unique.gene.dat <- unique.gene.dat[!duplicated(unique.gene.dat$Nearest.PromoterID), ]\n dist.freq <- rep(\"> 10kb\",nrow(unique.gene.dat))\n dist.freq[which(unique.gene.dat$Distance.to.TSS < 10000)] <- \"< 10kb\"\n dist.freq[which(unique.gene.dat$Distance.to.TSS < 5000)] <- \"< 5kb\"\n dist.freq[which(unique.gene.dat$Distance.to.TSS < 2000)] <- \"< 2kb\"\n dist.freq <- as.data.frame(table(dist.freq))\n colnames(dist.freq) <- c(\"distance\",sampleid)\n dist.melt <- melt(dist.freq)\n plot.dist.dat <- rbind(plot.dist.dat,dist.melt)\n\n}\nplot.dat$name <- factor(plot.dat$name, levels=sort(unique(as.character(plot.dat$name))))\nplot.dist.dat$variable <- factor(plot.dist.dat$variable, levels=sort(unique(as.character(plot.dist.dat$variable))))\nplot.feature.dat$variable <- factor(plot.feature.dat$variable, levels=sort(unique(as.character(plot.feature.dat$variable))))\n\nsummary.dat <- dcast(plot.feature.dat, variable ~ feature, value.var=\"value\")\ncolnames(summary.dat)[1] <- \"sample\"\nwrite.table(summary.dat,file=file.path(opt$outdir,paste(opt$outprefix,\".summary.txt\",sep=\"\")),sep=\"\\t\",row.names=F,col.names=T,quote=F)\n\n################################################\n################################################\n## PLOTS ##\n################################################\n################################################\n\nPlotFile <- file.path(opt$outdir,paste(opt$outprefix,\".plots.pdf\",sep=\"\"))\npdf(PlotFile,height=6,width=3*length(HomerFiles))\n\n## FEATURE COUNT STACKED BARPLOT\nplot <- ggplot(plot.feature.dat, aes(x=variable, y=value, group=feature)) +\n geom_bar(stat=\"identity\", position = \"fill\", aes(colour=feature,fill=feature), alpha = 0.3) +\n xlab(\"\") +\n ylab(\"% Feature\") +\n ggtitle(\"Peak Location Relative to Annotation\") +\n scale_y_continuous(labels = percent_format()) +\n theme(panel.grid.major = element_blank(),\n panel.grid.minor = element_blank(),\n panel.background = element_blank(),\n axis.text.y = element_text(colour=\"black\"),\n axis.text.x= element_text(colour=\"black\",face=\"bold\"),\n axis.line.x = element_line(size = 1, colour = \"black\", linetype = \"solid\"),\n axis.line.y = element_line(size = 1, colour = \"black\", linetype = \"solid\"))\nprint(plot)\n\n## DISTANCE TO CLOSEST GENE ACROSS ALL PEAKS STACKED BARPLOT\nplot <- ggplot(plot.dist.dat, aes(x=variable, y=value, group=distance)) +\n geom_bar(stat=\"identity\", position = \"fill\", aes(colour=distance,fill=distance), alpha = 0.3) +\n xlab(\"\") +\n ylab(\"% Unique genes to closest peak\") +\n ggtitle(\"Distance of Closest Peak to Gene\") +\n scale_y_continuous(labels = percent_format()) +\n theme(panel.grid.major = element_blank(),\n panel.grid.minor = element_blank(),\n panel.background = element_blank(),\n axis.text.y = element_text(colour=\"black\"),\n axis.text.x= element_text(colour=\"black\",face=\"bold\"),\n axis.line.x = element_line(size = 1, colour = \"black\", linetype = \"solid\"),\n axis.line.y = element_line(size = 1, colour = \"black\", linetype = \"solid\"))\nprint(plot)\n\n## VIOLIN PLOT OF PEAK DISTANCE TO TSS\nplot <- ggplot(plot.dat, aes(x=name, y=Distance.to.TSS)) +\n geom_violin(aes(colour=name,fill=name), alpha = 0.3) +\n geom_boxplot(width=0.1) +\n xlab(\"\") +\n ylab(expression(log[10]*\" distance to TSS\")) +\n ggtitle(\"Peak Distribution Relative to TSS\") +\n scale_y_continuous(trans='log10',breaks = trans_breaks(\"log10\", function(x) 10^x), labels = trans_format(\"log10\", math_format(10^.x))) +\n theme(legend.position=\"none\",\n panel.grid.major = element_blank(),\n panel.grid.minor = element_blank(),\n panel.background = element_blank(),\n axis.text.y = element_text(colour=\"black\"),\n axis.text.x= element_text(colour=\"black\",face=\"bold\"),\n axis.line.x = element_line(size = 1, colour = \"black\", linetype = \"solid\"),\n axis.line.y = element_line(size = 1, colour = \"black\", linetype = \"solid\"))\nprint(plot)\ndev.off()\n\n################################################\n################################################\n################################################\n################################################\n" }, { "path": "bin/plot_macs2_qc.r", "content": "#!/usr/bin/env Rscript\n\n################################################\n################################################\n## LOAD LIBRARIES ##\n################################################\n################################################\n\nlibrary(optparse)\nlibrary(ggplot2)\nlibrary(reshape2)\nlibrary(scales)\n\n################################################\n################################################\n## PARSE COMMAND-LINE PARAMETERS ##\n################################################\n################################################\n\noption_list <- list(make_option(c(\"-i\", \"--peak_files\"), type=\"character\", default=NULL, help=\"Comma-separated list of peak files.\", metavar=\"path\"),\n make_option(c(\"-s\", \"--sample_ids\"), type=\"character\", default=NULL, help=\"Comma-separated list of sample ids associated with peak files. Must be unique and in same order as peaks files input.\", metavar=\"string\"),\n make_option(c(\"-o\", \"--outdir\"), type=\"character\", default='./', help=\"Output directory\", metavar=\"path\"),\n make_option(c(\"-p\", \"--outprefix\"), type=\"character\", default='macs2_peakqc', help=\"Output prefix\", metavar=\"string\"))\n\nopt_parser <- OptionParser(option_list=option_list)\nopt <- parse_args(opt_parser)\n\nif (is.null(opt$peak_files)){\n print_help(opt_parser)\n stop(\"At least one peak file must be supplied\", call.=FALSE)\n}\nif (is.null(opt$sample_ids)){\n print_help(opt_parser)\n stop(\"Please provide sample ids associated with peak files.\", call.=FALSE)\n}\n\nif (file.exists(opt$outdir) == FALSE) {\n dir.create(opt$outdir,recursive=TRUE)\n}\n\nPeakFiles <- unlist(strsplit(opt$peak_files,\",\"))\nSampleIDs <- unlist(strsplit(opt$sample_ids,\",\"))\nif (length(PeakFiles) != length(SampleIDs)) {\n print_help(opt_parser)\n stop(\"Number of sample ids must equal number of homer annotated files.\", call.=FALSE)\n}\n\n################################################\n################################################\n## READ IN DATA ##\n################################################\n################################################\n\nplot.dat <- data.frame()\nsummary.dat <- data.frame()\nfor (idx in 1:length(PeakFiles)) {\n\n sampleid = SampleIDs[idx]\n isNarrow <- FALSE\n header <- c(\"chrom\",\"start\",\"end\",\"name\",\"pileup\", \"strand\", \"fold\", \"-log10(pvalue)\",\"-log10(qvalue)\")\n fsplit <- unlist(strsplit(basename(PeakFiles[idx]), split='.',fixed=TRUE))\n if (fsplit[length(fsplit)] == 'narrowPeak') {\n isNarrow <- TRUE\n header <- c(header,\"summit\")\n }\n peaks <- read.table(PeakFiles[idx], sep=\"\\t\", header=FALSE)\n colnames(peaks) <- header\n\n ## GET SUMMARY STATISTICS\n peaks.dat <- peaks[,c('fold','-log10(qvalue)','-log10(pvalue)')]\n peaks.dat$length <- (peaks$end - peaks$start)\n for (cname in colnames(peaks.dat)) {\n sdat <- summary(peaks.dat[,cname])\n sdat[\"num_peaks\"] <- nrow(peaks.dat)\n sdat[\"measure\"] <- cname\n sdat[\"sample\"] <- sampleid\n sdat <- t(data.frame(x=matrix(sdat),row.names=names(sdat)))\n summary.dat <- rbind(summary.dat,sdat)\n }\n colnames(peaks.dat) <- c('fold','fdr','pvalue','length')\n peaks.dat$name <- rep(sampleid,nrow(peaks.dat))\n plot.dat <- rbind(plot.dat,peaks.dat)\n}\nplot.dat$name <- factor(plot.dat$name, levels=sort(unique(as.character(plot.dat$name))))\n\nSummaryFile <- file.path(opt$outdir,paste(opt$outprefix,\".summary.txt\",sep=\"\"))\nwrite.table(summary.dat,file=SummaryFile,quote=FALSE,sep=\"\\t\",row.names=FALSE,col.names=TRUE)\n\n################################################\n################################################\n## PLOTS ##\n################################################\n################################################\n\n## RETURNS VIOLIN PLOT OBJECT\nviolin.plot <- function(plot.dat,x,y,ylab,title,log) {\n\n plot <- ggplot(plot.dat, aes_string(x=x, y=y)) +\n geom_violin(aes_string(colour=x,fill=x), alpha = 0.3) +\n geom_boxplot(width=0.1) +\n xlab(\"\") +\n ylab(ylab) +\n ggtitle(title) +\n theme(legend.position=\"none\",\n panel.grid.major = element_blank(),\n panel.grid.minor = element_blank(),\n panel.background = element_blank(),\n axis.text.y = element_text(colour=\"black\"),\n axis.text.x= element_text(colour=\"black\",face=\"bold\"),\n axis.line.x = element_line(size = 1, colour = \"black\", linetype = \"solid\"),\n axis.line.y = element_line(size = 1, colour = \"black\", linetype = \"solid\"))\n if (log == 10) {\n plot <- plot + scale_y_continuous(trans='log10',breaks = trans_breaks(\"log10\", function(x) 10^x), labels = trans_format(\"log10\", math_format(10^.x)))\n }\n if (log == 2) {\n plot <- plot + scale_y_continuous(trans='log2',breaks = trans_breaks(\"log2\", function(x) 2^x), labels = trans_format(\"log2\", math_format(2^.x)))\n }\n return(plot)\n}\n\n############################\n\nPlotFile <- file.path(opt$outdir,paste(opt$outprefix,\".plots.pdf\",sep=\"\"))\npdf(PlotFile,height=6,width=3*length(unique(plot.dat$name)))\n\n## PEAK COUNT PLOT\npeak.count.dat <- as.data.frame(table(plot.dat$name))\ncolnames(peak.count.dat) <- c(\"name\",\"count\")\nplot <- ggplot(peak.count.dat, aes(x=name, y=count)) +\n geom_bar(stat=\"identity\",aes(colour=name,fill=name), position = \"dodge\", width = 0.8, alpha = 0.3) +\n xlab(\"\") +\n ylab(\"Number of peaks\") +\n ggtitle(\"Peak count\") +\n theme(legend.position=\"none\",\n panel.grid.major = element_blank(),\n panel.grid.minor = element_blank(),\n panel.background = element_blank(),\n axis.text.y = element_text(colour=\"black\"),\n axis.text.x= element_text(colour=\"black\",face=\"bold\"),\n axis.line.x = element_line(size = 1, colour = \"black\", linetype = \"solid\"),\n axis.line.y = element_line(size = 1, colour = \"black\", linetype = \"solid\")) +\n geom_text(aes(label = count, x = name, y = count), position = position_dodge(width = 0.8), vjust = -0.6)\nprint(plot)\n\n## VIOLIN PLOTS\nprint(violin.plot(plot.dat=plot.dat,x=\"name\",y=\"length\",ylab=expression(log[10]*\" peak length\"),title=\"Peak length distribution\",log=10))\nprint(violin.plot(plot.dat=plot.dat,x=\"name\",y=\"fold\",ylab=expression(log[2]*\" fold-enrichment\"),title=\"Fold-change distribution\",log=2))\nprint(violin.plot(plot.dat=plot.dat,x=\"name\",y=\"fdr\",ylab=expression(-log[10]*\" qvalue\"),title=\"FDR distribution\",log=-1))\nprint(violin.plot(plot.dat=plot.dat,x=\"name\",y=\"pvalue\",ylab=expression(-log[10]*\" pvalue\"),title=\"Pvalue distribution\",log=-1))\ndev.off()\n\n################################################\n################################################\n################################################\n################################################\n" }, { "path": "bin/plot_peak_intersect.r", "content": "#!/usr/bin/env Rscript\n\n################################################\n################################################\n## LOAD LIBRARIES ##\n################################################\n################################################\n\nlibrary(optparse)\nlibrary(UpSetR)\n\n################################################\n################################################\n## PARSE COMMAND-LINE PARAMETERS ##\n################################################\n################################################\n\noption_list <- list(make_option(c(\"-i\", \"--input_file\"), type=\"character\", default=NULL, help=\"Path to tab-delimited file containing two columns i.e sample1&sample2&sample3 indicating intersect between samples set size.\", metavar=\"path\"),\n make_option(c(\"-o\", \"--output_file\"), type=\"character\", default=NULL, help=\"Path to output file with '.pdf' extension.\", metavar=\"path\"))\n\nopt_parser <- OptionParser(option_list=option_list)\nopt <- parse_args(opt_parser)\n\nif (is.null(opt$input_file)){\n print_help(opt_parser)\n stop(\"Input file must be supplied.\", call.=FALSE)\n}\nif (is.null(opt$output_file)){\n print_help(opt_parser)\n stop(\"Output pdf file must be supplied.\", call.=FALSE)\n}\n\nOutDir <- dirname(opt$output_file)\nif (file.exists(OutDir) == FALSE) {\n dir.create(OutDir,recursive=TRUE)\n}\n\n################################################\n################################################\n## PLOT DATA ##\n################################################\n################################################\n\ncomb.dat <- read.table(opt$input_file,sep=\"\\t\",header=FALSE)\ncomb.vec <- comb.dat[,2]\ncomb.vec <- setNames(comb.vec,comb.dat[,1])\nsets <- sort(unique(unlist(strsplit(names(comb.vec),split='&'))), decreasing = TRUE)\n\nnintersects = length(names(comb.vec))\nif (nintersects > 70) {\n nintersects <- 70\n comb.vec <- sort(comb.vec, decreasing = TRUE)[1:70]\n sets <- sort(unique(unlist(strsplit(names(comb.vec),split='&'))), decreasing = TRUE)\n}\n\npdf(opt$output_file,onefile=F,height=10,width=20)\n\nupset(\n fromExpression(comb.vec),\n nsets = length(sets),\n nintersects = nintersects,\n sets = sets,\n keep.order = TRUE,\n sets.bar.color = \"#56B4E9\",\n point.size = 3,\n line.size = 1,\n mb.ratio = c(0.55, 0.45),\n order.by = \"freq\",\n number.angles = 30,\n text.scale = c(1.5, 1.5, 1.5, 1.5, 1.5, 1.2)\n)\n\ndev.off()\n\n################################################\n################################################\n################################################\n################################################\n" }, { "path": "conf/base.config", "content": "/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n nf-core/atacseq Nextflow base config file\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n A 'blank slate' config file, appropriate for general use on most high performance\n compute environments. Assumes that all software is installed and available on\n the PATH. Runs in `local` mode - all jobs will be run on the logged in environment.\n----------------------------------------------------------------------------------------\n*/\n\nprocess {\n\n cpus = { check_max( 1 * task.attempt, 'cpus' ) }\n memory = { check_max( 6.GB * task.attempt, 'memory' ) }\n time = { check_max( 4.h * task.attempt, 'time' ) }\n\n errorStrategy = { task.exitStatus in ((130..145) + 104) ? 'retry' : 'finish' }\n maxRetries = 1\n maxErrors = '-1'\n\n // Process-specific resource requirements\n // NOTE - Please try and re-use the labels below as much as possible.\n // These labels are used and recognised by default in DSL2 files hosted on nf-core/modules.\n // If possible, it would be nice to keep the same label naming convention when\n // adding in your local modules too.\n // See https://www.nextflow.io/docs/latest/config.html#config-process-selectors\n withLabel:process_single {\n cpus = { check_max( 1 , 'cpus' ) }\n memory = { check_max( 6.GB * task.attempt, 'memory' ) }\n time = { check_max( 4.h * task.attempt, 'time' ) }\n }\n withLabel:process_low {\n cpus = { check_max( 2 * task.attempt, 'cpus' ) }\n memory = { check_max( 12.GB * task.attempt, 'memory' ) }\n time = { check_max( 4.h * task.attempt, 'time' ) }\n }\n withLabel:process_medium {\n cpus = { check_max( 6 * task.attempt, 'cpus' ) }\n memory = { check_max( 36.GB * task.attempt, 'memory' ) }\n time = { check_max( 8.h * task.attempt, 'time' ) }\n }\n withLabel:process_high {\n cpus = { check_max( 12 * task.attempt, 'cpus' ) }\n memory = { check_max( 72.GB * task.attempt, 'memory' ) }\n time = { check_max( 16.h * task.attempt, 'time' ) }\n }\n withLabel:process_long {\n time = { check_max( 20.h * task.attempt, 'time' ) }\n }\n withLabel:process_high_memory {\n memory = { check_max( 200.GB * task.attempt, 'memory' ) }\n }\n withLabel:error_ignore {\n errorStrategy = 'ignore'\n }\n withLabel:error_retry {\n errorStrategy = 'retry'\n maxRetries = 2\n }\n withName:CUSTOM_DUMPSOFTWAREVERSIONS {\n cache = false\n }\n}\n" }, { "path": "conf/igenomes.config", "content": "/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Nextflow config file for iGenomes paths\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Defines reference genomes using iGenome paths.\n Can be used by any config that customises the base path using:\n $params.igenomes_base / --igenomes_base\n----------------------------------------------------------------------------------------\n*/\n\nparams {\n // illumina iGenomes reference file paths\n genomes {\n 'GRCh37' {\n fasta = \"${params.igenomes_base}/Homo_sapiens/Ensembl/GRCh37/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Homo_sapiens/Ensembl/GRCh37/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Homo_sapiens/Ensembl/GRCh37/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Homo_sapiens/Ensembl/GRCh37/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Homo_sapiens/Ensembl/GRCh37/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Homo_sapiens/Ensembl/GRCh37/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Homo_sapiens/Ensembl/GRCh37/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Homo_sapiens/Ensembl/GRCh37/Annotation/README.txt\"\n mito_name = \"MT\"\n blacklist = \"${projectDir}/assets/blacklists/v1.0/GRCh37-blacklist.v1.bed\"\n macs_gsize = [\n \"50\" : 2684219875,\n \"75\" : 2733035409,\n \"100\" : 2774803719,\n \"150\" : 2824648687,\n \"200\" : 2848794782\n ]\n }\n 'GRCh38' {\n fasta = \"${params.igenomes_base}/Homo_sapiens/NCBI/GRCh38/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Homo_sapiens/NCBI/GRCh38/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Homo_sapiens/NCBI/GRCh38/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Homo_sapiens/NCBI/GRCh38/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Homo_sapiens/NCBI/GRCh38/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Homo_sapiens/NCBI/GRCh38/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Homo_sapiens/NCBI/GRCh38/Annotation/Genes/genes.bed\"\n mito_name = \"chrM\"\n blacklist = \"${projectDir}/assets/blacklists/v3.0/hg38-blacklist.v3.bed\"\n macs_gsize = [\n \"50\" : 2701262066,\n \"75\" : 2749859687,\n \"100\" : 2805665311,\n \"150\" : 2862089864,\n \"200\" : 2892537351\n ]\n }\n 'CHM13' {\n fasta = \"${params.igenomes_base}/Homo_sapiens/UCSC/CHM13/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Homo_sapiens/UCSC/CHM13/Sequence/BWAIndex/\"\n bwamem2 = \"${params.igenomes_base}/Homo_sapiens/UCSC/CHM13/Sequence/BWAmem2Index/\"\n gtf = \"${params.igenomes_base}/Homo_sapiens/NCBI/CHM13/Annotation/Genes/genes.gtf\"\n gff = \"ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/009/914/755/GCF_009914755.1_T2T-CHM13v2.0/GCF_009914755.1_T2T-CHM13v2.0_genomic.gff.gz\"\n mito_name = \"chrM\"\n }\n 'GRCm38' {\n fasta = \"${params.igenomes_base}/Mus_musculus/Ensembl/GRCm38/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Mus_musculus/Ensembl/GRCm38/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Mus_musculus/Ensembl/GRCm38/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Mus_musculus/Ensembl/GRCm38/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Mus_musculus/Ensembl/GRCm38/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Mus_musculus/Ensembl/GRCm38/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Mus_musculus/Ensembl/GRCm38/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Mus_musculus/Ensembl/GRCm38/Annotation/README.txt\"\n mito_name = \"MT\"\n blacklist = \"${projectDir}/assets/blacklists/v2.0/GRCm38-blacklist.v2.bed\"\n macs_gsize = [\n \"50\" : 2307679482,\n \"75\" : 2406655830,\n \"100\" : 2466184610,\n \"150\" : 2492306232,\n \"200\" : 2519386924\n ]\n }\n 'TAIR10' {\n fasta = \"${params.igenomes_base}/Arabidopsis_thaliana/Ensembl/TAIR10/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Arabidopsis_thaliana/Ensembl/TAIR10/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Arabidopsis_thaliana/Ensembl/TAIR10/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Arabidopsis_thaliana/Ensembl/TAIR10/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Arabidopsis_thaliana/Ensembl/TAIR10/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Arabidopsis_thaliana/Ensembl/TAIR10/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Arabidopsis_thaliana/Ensembl/TAIR10/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Arabidopsis_thaliana/Ensembl/TAIR10/Annotation/README.txt\"\n mito_name = \"Mt\"\n macs_gsize = [\n \"50\" : 114339094,\n \"75\" : 115317469,\n \"100\" : 118459858,\n \"150\" : 118504138,\n \"200\" : 117723393\n ]\n }\n 'EB2' {\n fasta = \"${params.igenomes_base}/Bacillus_subtilis_168/Ensembl/EB2/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Bacillus_subtilis_168/Ensembl/EB2/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Bacillus_subtilis_168/Ensembl/EB2/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Bacillus_subtilis_168/Ensembl/EB2/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Bacillus_subtilis_168/Ensembl/EB2/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Bacillus_subtilis_168/Ensembl/EB2/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Bacillus_subtilis_168/Ensembl/EB2/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Bacillus_subtilis_168/Ensembl/EB2/Annotation/README.txt\"\n macs_gsize = [\n \"50\" : 4150072,\n \"75\" : 4191132,\n \"100\" : 4198752,\n \"150\" : 4176800,\n \"200\" : 4197072\n ]\n }\n 'UMD3.1' {\n fasta = \"${params.igenomes_base}/Bos_taurus/Ensembl/UMD3.1/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Bos_taurus/Ensembl/UMD3.1/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Bos_taurus/Ensembl/UMD3.1/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Bos_taurus/Ensembl/UMD3.1/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Bos_taurus/Ensembl/UMD3.1/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Bos_taurus/Ensembl/UMD3.1/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Bos_taurus/Ensembl/UMD3.1/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Bos_taurus/Ensembl/UMD3.1/Annotation/README.txt\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 2370644326,\n \"75\" : 2480511357,\n \"100\" : 2567220492,\n \"150\" : 2594494201,\n \"200\" : 2648740387\n ]\n }\n 'WBcel235' {\n fasta = \"${params.igenomes_base}/Caenorhabditis_elegans/Ensembl/WBcel235/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Caenorhabditis_elegans/Ensembl/WBcel235/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Caenorhabditis_elegans/Ensembl/WBcel235/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Caenorhabditis_elegans/Ensembl/WBcel235/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Caenorhabditis_elegans/Ensembl/WBcel235/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Caenorhabditis_elegans/Ensembl/WBcel235/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Caenorhabditis_elegans/Ensembl/WBcel235/Annotation/Genes/genes.bed\"\n mito_name = \"MtDNA\"\n macs_gsize = [\n \"50\" : 95159402,\n \"75\" : 96945370,\n \"100\" : 98259898,\n \"150\" : 98721103,\n \"200\" : 98672558\n ]\n }\n 'CanFam3.1' {\n fasta = \"${params.igenomes_base}/Canis_familiaris/Ensembl/CanFam3.1/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Canis_familiaris/Ensembl/CanFam3.1/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Canis_familiaris/Ensembl/CanFam3.1/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Canis_familiaris/Ensembl/CanFam3.1/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Canis_familiaris/Ensembl/CanFam3.1/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Canis_familiaris/Ensembl/CanFam3.1/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Canis_familiaris/Ensembl/CanFam3.1/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Canis_familiaris/Ensembl/CanFam3.1/Annotation/README.txt\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 2237684358,\n \"75\" : 2279860111,\n \"100\" : 2293979635,\n \"150\" : 2300527794,\n \"200\" : 2313332891\n ]\n }\n 'GRCz10' {\n fasta = \"${params.igenomes_base}/Danio_rerio/Ensembl/GRCz10/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Danio_rerio/Ensembl/GRCz10/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Danio_rerio/Ensembl/GRCz10/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Danio_rerio/Ensembl/GRCz10/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Danio_rerio/Ensembl/GRCz10/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Danio_rerio/Ensembl/GRCz10/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Danio_rerio/Ensembl/GRCz10/Annotation/Genes/genes.bed\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 1172895610,\n \"75\" : 1229400206,\n \"100\" : 1253908756,\n \"150\" : 1285330773,\n \"200\" : 1292538906\n ]\n }\n 'BDGP6' {\n fasta = \"${params.igenomes_base}/Drosophila_melanogaster/Ensembl/BDGP6/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Drosophila_melanogaster/Ensembl/BDGP6/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Drosophila_melanogaster/Ensembl/BDGP6/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Drosophila_melanogaster/Ensembl/BDGP6/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Drosophila_melanogaster/Ensembl/BDGP6/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Drosophila_melanogaster/Ensembl/BDGP6/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Drosophila_melanogaster/Ensembl/BDGP6/Annotation/Genes/genes.bed\"\n mito_name = \"M\"\n macs_gsize = [\n \"50\" : 123519388,\n \"75\" : 124886264,\n \"100\" : 126807034,\n \"150\" : 126903604,\n \"200\" : 128575605\n ]\n }\n 'EquCab2' {\n fasta = \"${params.igenomes_base}/Equus_caballus/Ensembl/EquCab2/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Equus_caballus/Ensembl/EquCab2/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Equus_caballus/Ensembl/EquCab2/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Equus_caballus/Ensembl/EquCab2/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Equus_caballus/Ensembl/EquCab2/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Equus_caballus/Ensembl/EquCab2/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Equus_caballus/Ensembl/EquCab2/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Equus_caballus/Ensembl/EquCab2/Annotation/README.txt\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 2294980416,\n \"75\" : 2289244826,\n \"100\" : 2334155865,\n \"150\" : 2343297042,\n \"200\" : 2350515523\n ]\n }\n 'EB1' {\n fasta = \"${params.igenomes_base}/Escherichia_coli_K_12_DH10B/Ensembl/EB1/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Escherichia_coli_K_12_DH10B/Ensembl/EB1/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Escherichia_coli_K_12_DH10B/Ensembl/EB1/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Escherichia_coli_K_12_DH10B/Ensembl/EB1/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Escherichia_coli_K_12_DH10B/Ensembl/EB1/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Escherichia_coli_K_12_DH10B/Ensembl/EB1/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Escherichia_coli_K_12_DH10B/Ensembl/EB1/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Escherichia_coli_K_12_DH10B/Ensembl/EB1/Annotation/README.txt\"\n macs_gsize = [\n \"50\" : 4481912,\n \"75\" : 4485018,\n \"100\" : 4468952,\n \"150\" : 4489684,\n \"200\" : 4527891\n ]\n }\n 'Galgal4' {\n fasta = \"${params.igenomes_base}/Gallus_gallus/Ensembl/Galgal4/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Gallus_gallus/Ensembl/Galgal4/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Gallus_gallus/Ensembl/Galgal4/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Gallus_gallus/Ensembl/Galgal4/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Gallus_gallus/Ensembl/Galgal4/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Gallus_gallus/Ensembl/Galgal4/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Gallus_gallus/Ensembl/Galgal4/Annotation/Genes/genes.bed\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 974987959,\n \"75\" : 978772437,\n \"100\" : 984935167,\n \"150\" : 979442039,\n \"200\" : 991678648\n ]\n }\n 'Gm01' {\n fasta = \"${params.igenomes_base}/Glycine_max/Ensembl/Gm01/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Glycine_max/Ensembl/Gm01/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Glycine_max/Ensembl/Gm01/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Glycine_max/Ensembl/Gm01/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Glycine_max/Ensembl/Gm01/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Glycine_max/Ensembl/Gm01/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Glycine_max/Ensembl/Gm01/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Glycine_max/Ensembl/Gm01/Annotation/README.txt\"\n macs_gsize = [\n \"50\" : 748112428,\n \"75\" : 826455017,\n \"100\" : 857283568,\n \"150\" : 895077451,\n \"200\" : 911783687\n ]\n }\n 'Mmul_1' {\n fasta = \"${params.igenomes_base}/Macaca_mulatta/Ensembl/Mmul_1/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Macaca_mulatta/Ensembl/Mmul_1/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Macaca_mulatta/Ensembl/Mmul_1/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Macaca_mulatta/Ensembl/Mmul_1/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Macaca_mulatta/Ensembl/Mmul_1/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Macaca_mulatta/Ensembl/Mmul_1/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Macaca_mulatta/Ensembl/Mmul_1/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Macaca_mulatta/Ensembl/Mmul_1/Annotation/README.txt\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 2498932238,\n \"75\" : 2598624693,\n \"100\" : 2642166663,\n \"150\" : 2661433343,\n \"200\" : 2674888870\n ]\n }\n 'IRGSP-1.0' {\n fasta = \"${params.igenomes_base}/Oryza_sativa_japonica/Ensembl/IRGSP-1.0/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Oryza_sativa_japonica/Ensembl/IRGSP-1.0/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Oryza_sativa_japonica/Ensembl/IRGSP-1.0/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Oryza_sativa_japonica/Ensembl/IRGSP-1.0/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Oryza_sativa_japonica/Ensembl/IRGSP-1.0/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Oryza_sativa_japonica/Ensembl/IRGSP-1.0/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Oryza_sativa_japonica/Ensembl/IRGSP-1.0/Annotation/Genes/genes.bed\"\n mito_name = \"Mt\"\n macs_gsize = [\n \"50\" : 322594956,\n \"75\" : 337043804,\n \"100\" : 345775274,\n \"150\" : 355020671,\n \"200\" : 363478234\n ]\n }\n 'CHIMP2.1.4' {\n fasta = \"${params.igenomes_base}/Pan_troglodytes/Ensembl/CHIMP2.1.4/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Pan_troglodytes/Ensembl/CHIMP2.1.4/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Pan_troglodytes/Ensembl/CHIMP2.1.4/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Pan_troglodytes/Ensembl/CHIMP2.1.4/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Pan_troglodytes/Ensembl/CHIMP2.1.4/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Pan_troglodytes/Ensembl/CHIMP2.1.4/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Pan_troglodytes/Ensembl/CHIMP2.1.4/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Pan_troglodytes/Ensembl/CHIMP2.1.4/Annotation/README.txt\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 2576111695,\n \"75\" : 2702821987,\n \"100\" : 2733435831,\n \"150\" : 2735167196,\n \"200\" : 2738912507\n ]\n }\n 'Rnor_5.0' {\n fasta = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_5.0/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_5.0/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_5.0/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_5.0/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_5.0/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_5.0/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_5.0/Annotation/Genes/genes.bed\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 2303951475,\n \"75\" : 2367071843,\n \"100\" : 2402745922,\n \"150\" : 2405692811,\n \"200\" : 2407324495\n ]\n }\n 'Rnor_6.0' {\n fasta = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_6.0/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_6.0/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_6.0/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_6.0/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_6.0/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_6.0/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Rattus_norvegicus/Ensembl/Rnor_6.0/Annotation/Genes/genes.bed\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 2375372135,\n \"75\" : 2440746491,\n \"100\" : 2480029900,\n \"150\" : 2477334634,\n \"200\" : 2478552171\n ]\n }\n 'R64-1-1' {\n fasta = \"${params.igenomes_base}/Saccharomyces_cerevisiae/Ensembl/R64-1-1/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Saccharomyces_cerevisiae/Ensembl/R64-1-1/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Saccharomyces_cerevisiae/Ensembl/R64-1-1/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Saccharomyces_cerevisiae/Ensembl/R64-1-1/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Saccharomyces_cerevisiae/Ensembl/R64-1-1/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Saccharomyces_cerevisiae/Ensembl/R64-1-1/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Saccharomyces_cerevisiae/Ensembl/R64-1-1/Annotation/Genes/genes.bed\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 11624332,\n \"75\" : 11693438,\n \"100\" : 11777680,\n \"150\" : 11783749,\n \"200\" : 11825681\n ]\n }\n 'EF2' {\n fasta = \"${params.igenomes_base}/Schizosaccharomyces_pombe/Ensembl/EF2/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Schizosaccharomyces_pombe/Ensembl/EF2/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Schizosaccharomyces_pombe/Ensembl/EF2/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Schizosaccharomyces_pombe/Ensembl/EF2/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Schizosaccharomyces_pombe/Ensembl/EF2/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Schizosaccharomyces_pombe/Ensembl/EF2/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Schizosaccharomyces_pombe/Ensembl/EF2/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Schizosaccharomyces_pombe/Ensembl/EF2/Annotation/README.txt\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 12190646,\n \"75\" : 12291456,\n \"100\" : 12346649,\n \"150\" : 12403911,\n \"200\" : 12442064\n ]\n }\n 'Sbi1' {\n fasta = \"${params.igenomes_base}/Sorghum_bicolor/Ensembl/Sbi1/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Sorghum_bicolor/Ensembl/Sbi1/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Sorghum_bicolor/Ensembl/Sbi1/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Sorghum_bicolor/Ensembl/Sbi1/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Sorghum_bicolor/Ensembl/Sbi1/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Sorghum_bicolor/Ensembl/Sbi1/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Sorghum_bicolor/Ensembl/Sbi1/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Sorghum_bicolor/Ensembl/Sbi1/Annotation/README.txt\"\n macs_gsize = [\n \"50\" : 444102512,\n \"75\" : 506986021,\n \"100\" : 540037446,\n \"150\" : 575130820,\n \"200\" : 595857042\n ]\n }\n 'Sscrofa10.2' {\n fasta = \"${params.igenomes_base}/Sus_scrofa/Ensembl/Sscrofa10.2/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Sus_scrofa/Ensembl/Sscrofa10.2/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Sus_scrofa/Ensembl/Sscrofa10.2/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Sus_scrofa/Ensembl/Sscrofa10.2/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Sus_scrofa/Ensembl/Sscrofa10.2/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Sus_scrofa/Ensembl/Sscrofa10.2/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Sus_scrofa/Ensembl/Sscrofa10.2/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Sus_scrofa/Ensembl/Sscrofa10.2/Annotation/README.txt\"\n mito_name = \"MT\"\n macs_gsize = [\n \"50\" : 2105185708,\n \"75\" : 2131615607,\n \"100\" : 2149244400,\n \"150\" : 2189757848,\n \"200\" : 2203893315\n ]\n }\n 'AGPv3' {\n fasta = \"${params.igenomes_base}/Zea_mays/Ensembl/AGPv3/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Zea_mays/Ensembl/AGPv3/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Zea_mays/Ensembl/AGPv3/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Zea_mays/Ensembl/AGPv3/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Zea_mays/Ensembl/AGPv3/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Zea_mays/Ensembl/AGPv3/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Zea_mays/Ensembl/AGPv3/Annotation/Genes/genes.bed\"\n mito_name = \"Mt\"\n macs_gsize = [\n \"50\" : 1113453752,\n \"75\" : 1392458449,\n \"100\" : 1579923466,\n \"150\" : 1729475311,\n \"200\" : 1841419596\n ]\n }\n 'hg38' {\n fasta = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg38/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg38/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg38/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg38/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg38/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg38/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg38/Annotation/Genes/genes.bed\"\n mito_name = \"chrM\"\n blacklist = \"${projectDir}/assets/blacklists/v3.0/hg38-blacklist.v3.bed\"\n macs_gsize = [\n \"50\" : 2701262066,\n \"75\" : 2749859687,\n \"100\" : 2805665311,\n \"150\" : 2862089864,\n \"200\" : 2892537351\n ]\n }\n 'hg19' {\n fasta = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg19/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg19/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg19/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg19/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg19/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg19/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg19/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Homo_sapiens/UCSC/hg19/Annotation/README.txt\"\n mito_name = \"chrM\"\n blacklist = \"${projectDir}/assets/blacklists/v1.0/hg19-blacklist.v1.bed\"\n macs_gsize = [\n \"50\" : 2684219875,\n \"75\" : 2733035409,\n \"100\" : 2774803719,\n \"150\" : 2824648687,\n \"200\" : 2848794782\n ]\n }\n 'mm10' {\n fasta = \"${params.igenomes_base}/Mus_musculus/UCSC/mm10/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Mus_musculus/UCSC/mm10/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Mus_musculus/UCSC/mm10/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Mus_musculus/UCSC/mm10/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Mus_musculus/UCSC/mm10/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Mus_musculus/UCSC/mm10/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Mus_musculus/UCSC/mm10/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Mus_musculus/UCSC/mm10/Annotation/README.txt\"\n mito_name = \"chrM\"\n blacklist = \"${projectDir}/assets/blacklists/v2.0/mm10-blacklist.v2.bed\"\n macs_gsize = [\n \"50\" : 2307679482,\n \"75\" : 2406655830,\n \"100\" : 2466184610,\n \"150\" : 2492306232,\n \"200\" : 2519386924\n ]\n }\n 'bosTau8' {\n fasta = \"${params.igenomes_base}/Bos_taurus/UCSC/bosTau8/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Bos_taurus/UCSC/bosTau8/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Bos_taurus/UCSC/bosTau8/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Bos_taurus/UCSC/bosTau8/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Bos_taurus/UCSC/bosTau8/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Bos_taurus/UCSC/bosTau8/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Bos_taurus/UCSC/bosTau8/Annotation/Genes/genes.bed\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 2370644326,\n \"75\" : 2480511357,\n \"100\" : 2567220492,\n \"150\" : 2594494201,\n \"200\" : 2648740387\n ]\n }\n 'ce10' {\n fasta = \"${params.igenomes_base}/Caenorhabditis_elegans/UCSC/ce10/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Caenorhabditis_elegans/UCSC/ce10/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Caenorhabditis_elegans/UCSC/ce10/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Caenorhabditis_elegans/UCSC/ce10/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Caenorhabditis_elegans/UCSC/ce10/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Caenorhabditis_elegans/UCSC/ce10/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Caenorhabditis_elegans/UCSC/ce10/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Caenorhabditis_elegans/UCSC/ce10/Annotation/README.txt\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 95156190,\n \"75\" : 96995949,\n \"100\" : 98287299,\n \"150\" : 98879728,\n \"200\" : 98769409\n ]\n }\n 'canFam3' {\n fasta = \"${params.igenomes_base}/Canis_familiaris/UCSC/canFam3/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Canis_familiaris/UCSC/canFam3/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Canis_familiaris/UCSC/canFam3/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Canis_familiaris/UCSC/canFam3/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Canis_familiaris/UCSC/canFam3/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Canis_familiaris/UCSC/canFam3/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Canis_familiaris/UCSC/canFam3/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Canis_familiaris/UCSC/canFam3/Annotation/README.txt\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 2237684358,\n \"75\" : 2279860111,\n \"100\" : 2293979635,\n \"150\" : 2300527794,\n \"200\" : 2313332891\n ]\n }\n 'danRer10' {\n fasta = \"${params.igenomes_base}/Danio_rerio/UCSC/danRer10/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Danio_rerio/UCSC/danRer10/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Danio_rerio/UCSC/danRer10/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Danio_rerio/UCSC/danRer10/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Danio_rerio/UCSC/danRer10/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Danio_rerio/UCSC/danRer10/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Danio_rerio/UCSC/danRer10/Annotation/Genes/genes.bed\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 1172895610,\n \"75\" : 1229400206,\n \"100\" : 1253908756,\n \"150\" : 1285330773,\n \"200\" : 1292538906\n ]\n }\n 'dm6' {\n fasta = \"${params.igenomes_base}/Drosophila_melanogaster/UCSC/dm6/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Drosophila_melanogaster/UCSC/dm6/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Drosophila_melanogaster/UCSC/dm6/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Drosophila_melanogaster/UCSC/dm6/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Drosophila_melanogaster/UCSC/dm6/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Drosophila_melanogaster/UCSC/dm6/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Drosophila_melanogaster/UCSC/dm6/Annotation/Genes/genes.bed\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 123548253,\n \"75\" : 124886264,\n \"100\" : 126807034,\n \"150\" : 126908682,\n \"200\" : 128599061\n ]\n }\n 'equCab2' {\n fasta = \"${params.igenomes_base}/Equus_caballus/UCSC/equCab2/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Equus_caballus/UCSC/equCab2/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Equus_caballus/UCSC/equCab2/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Equus_caballus/UCSC/equCab2/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Equus_caballus/UCSC/equCab2/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Equus_caballus/UCSC/equCab2/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Equus_caballus/UCSC/equCab2/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Equus_caballus/UCSC/equCab2/Annotation/README.txt\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 2294980416,\n \"75\" : 2289244826,\n \"100\" : 2334155865,\n \"150\" : 2343297042,\n \"200\" : 2350515523\n ]\n }\n 'galGal4' {\n fasta = \"${params.igenomes_base}/Gallus_gallus/UCSC/galGal4/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Gallus_gallus/UCSC/galGal4/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Gallus_gallus/UCSC/galGal4/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Gallus_gallus/UCSC/galGal4/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Gallus_gallus/UCSC/galGal4/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Gallus_gallus/UCSC/galGal4/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Gallus_gallus/UCSC/galGal4/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Gallus_gallus/UCSC/galGal4/Annotation/README.txt\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 974987959,\n \"75\" : 978772437,\n \"100\" : 984935167,\n \"150\" : 979442039,\n \"200\" : 991678648\n ]\n }\n 'panTro4' {\n fasta = \"${params.igenomes_base}/Pan_troglodytes/UCSC/panTro4/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Pan_troglodytes/UCSC/panTro4/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Pan_troglodytes/UCSC/panTro4/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Pan_troglodytes/UCSC/panTro4/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Pan_troglodytes/UCSC/panTro4/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Pan_troglodytes/UCSC/panTro4/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Pan_troglodytes/UCSC/panTro4/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Pan_troglodytes/UCSC/panTro4/Annotation/README.txt\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 2576111695,\n \"75\" : 2702821987,\n \"100\" : 2733435831,\n \"150\" : 2735167196,\n \"200\" : 2738912507\n ]\n }\n 'rn6' {\n fasta = \"${params.igenomes_base}/Rattus_norvegicus/UCSC/rn6/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Rattus_norvegicus/UCSC/rn6/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Rattus_norvegicus/UCSC/rn6/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Rattus_norvegicus/UCSC/rn6/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Rattus_norvegicus/UCSC/rn6/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Rattus_norvegicus/UCSC/rn6/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Rattus_norvegicus/UCSC/rn6/Annotation/Genes/genes.bed\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 2375372135,\n \"75\" : 2440746491,\n \"100\" : 2480029900,\n \"150\" : 2477334634,\n \"200\" : 2478552171\n ]\n }\n 'sacCer3' {\n fasta = \"${params.igenomes_base}/Saccharomyces_cerevisiae/UCSC/sacCer3/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Saccharomyces_cerevisiae/UCSC/sacCer3/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Saccharomyces_cerevisiae/UCSC/sacCer3/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Saccharomyces_cerevisiae/UCSC/sacCer3/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Saccharomyces_cerevisiae/UCSC/sacCer3/Sequence/BismarkIndex/\"\n readme = \"${params.igenomes_base}/Saccharomyces_cerevisiae/UCSC/sacCer3/Annotation/README.txt\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 11624332,\n \"75\" : 11693438,\n \"100\" : 11777680,\n \"150\" : 11783749,\n \"200\" : 11825681\n ]\n }\n 'susScr3' {\n fasta = \"${params.igenomes_base}/Sus_scrofa/UCSC/susScr3/Sequence/WholeGenomeFasta/genome.fa\"\n bwa = \"${params.igenomes_base}/Sus_scrofa/UCSC/susScr3/Sequence/BWAIndex/version0.6.0/\"\n bowtie2 = \"${params.igenomes_base}/Sus_scrofa/UCSC/susScr3/Sequence/Bowtie2Index/\"\n star = \"${params.igenomes_base}/Sus_scrofa/UCSC/susScr3/Sequence/STARIndex/\"\n bismark = \"${params.igenomes_base}/Sus_scrofa/UCSC/susScr3/Sequence/BismarkIndex/\"\n gtf = \"${params.igenomes_base}/Sus_scrofa/UCSC/susScr3/Annotation/Genes/genes.gtf\"\n bed12 = \"${params.igenomes_base}/Sus_scrofa/UCSC/susScr3/Annotation/Genes/genes.bed\"\n readme = \"${params.igenomes_base}/Sus_scrofa/UCSC/susScr3/Annotation/README.txt\"\n mito_name = \"chrM\"\n macs_gsize = [\n \"50\" : 2105185708,\n \"75\" : 2131615607,\n \"100\" : 2149244400,\n \"150\" : 2189757848,\n \"200\" : 2203893315\n ]\n }\n }\n}\n" }, { "path": "conf/modules.config", "content": "/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Config file for defining DSL2 per module options and publishing paths\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Available keys to override module options:\n ext.args = Additional arguments appended to command in module.\n ext.args2 = Second set of arguments appended to command in module (multi-tool modules).\n ext.args3 = Third set of arguments appended to command in module (multi-tool modules).\n ext.prefix = File name prefix for output files.\n----------------------------------------------------------------------------------------\n*/\n\n//\n// General configuration options\n//\n\nprocess {\n publishDir = [\n path: { \"${params.outdir}/${task.process.tokenize(':')[-1].tokenize('_')[0].toLowerCase()}\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n\n withName: 'SAMPLESHEET_CHECK' {\n ext.args = {\n [\n 'samplesheet.valid.csv',\n params.with_control ? \"--with_control\" : ''\n ].join(' ').trim()\n }\n publishDir = [\n path: { \"${params.outdir}/pipeline_info\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: 'CUSTOM_DUMPSOFTWAREVERSIONS' {\n publishDir = [\n path: { \"${params.outdir}/pipeline_info\" },\n mode: params.publish_dir_mode,\n pattern: '*_versions.yml'\n ]\n }\n}\n\n//\n// Genome preparation options\n//\n\nprocess {\n withName: 'GUNZIP_.*' {\n publishDir = [\n path: { \"${params.outdir}/genome\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_reference\n ]\n }\n\n withName: 'UNTAR_.*' {\n ext.args2 = '--no-same-owner'\n publishDir = [\n path: { \"${params.outdir}/genome/index\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_reference\n ]\n }\n\n withName: 'BWA_INDEX|BOWTIE2_BUILD|STAR_GENOMEGENERATE|CHROMAP_INDEX' {\n publishDir = [\n path: { \"${params.outdir}/genome/index\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_reference\n ]\n }\n\n withName: 'GFFREAD' {\n ext.args = '--keep-exon-attrs -F -T'\n publishDir = [\n path: { \"${params.outdir}/genome\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_reference\n ]\n }\n\n withName: 'GTF2BED' {\n publishDir = [\n path: { \"${params.outdir}/genome\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_reference\n ]\n }\n\n withName: 'CUSTOM_GETCHROMSIZES' {\n publishDir = [\n path: { \"${params.outdir}/genome\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_reference\n ]\n }\n\n withName: 'TSS_EXTRACT' {\n publishDir = [\n path: { \"${params.outdir}/genome\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_reference\n ]\n }\n\n withName: 'GENOME_BLACKLIST_REGIONS' {\n publishDir = [\n path: { \"${params.outdir}/genome\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_reference\n ]\n }\n\n withName: 'GET_AUTOSOMES' {\n publishDir = [\n path: { \"${params.outdir}/genome\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_reference\n ]\n }\n\n withName: 'KHMER_UNIQUEKMERS' {\n publishDir = [ enabled: false ]\n }\n}\n\n//\n// Read QC and trimming options\n//\n\nif (!(params.skip_fastqc || params.skip_qc)) {\n process {\n withName: 'FASTQC' {\n ext.args = '--quiet'\n publishDir = [\n [\n path: { \"${params.outdir}/fastqc\" },\n mode: params.publish_dir_mode,\n pattern: \"*.{html}\"\n ],\n [\n path: { \"${params.outdir}/fastqc/zips\" },\n mode: params.publish_dir_mode,\n pattern: \"*.{zip}\"\n ]\n ]\n }\n }\n}\n\nif (!params.skip_trimming) {\n process {\n withName: 'TRIMGALORE' {\n ext.args = {\n [\n '--fastqc',\n params.trim_nextseq > 0 ? \"--nextseq ${params.trim_nextseq}\" : '',\n params.clip_r1 > 0 ? \"--clip_r1 ${params.clip_r1}\" : '',\n params.clip_r2 > 0 ? \"--clip_r2 ${params.clip_r2}\" : '',\n params.three_prime_clip_r1 > 0 ? \"--three_prime_clip_r1 ${params.three_prime_clip_r1}\" : '',\n params.three_prime_clip_r2 > 0 ? \"--three_prime_clip_r2 ${params.three_prime_clip_r2}\" : ''\n ].join(' ').trim()\n }\n publishDir = [\n [\n path: { \"${params.outdir}/trimgalore/fastqc\" },\n mode: params.publish_dir_mode,\n pattern: \"*.{html}\"\n ],\n [\n path: { \"${params.outdir}/trimgalore/fastqc/zips\" },\n mode: params.publish_dir_mode,\n pattern: \"*.{zip}\"\n ],\n [\n path: { \"${params.outdir}/trimgalore/logs\" },\n mode: params.publish_dir_mode,\n pattern: \"*.txt\"\n ],\n [\n path: { \"${params.outdir}/trimgalore\" },\n mode: params.publish_dir_mode,\n pattern: \"*.fq.gz\",\n enabled: params.save_trimmed\n ]\n ]\n }\n }\n}\n\nprocess {\n withName: 'NFCORE_ATACSEQ:ATACSEQ:.*:BAM_SORT_STATS_SAMTOOLS:SAMTOOLS_SORT' {\n ext.prefix = { \"${meta.id}.Lb.sorted\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/library\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_align_intermeds\n ]\n }\n\n withName: 'NFCORE_ATACSEQ:ATACSEQ:.*:BAM_SORT_STATS_SAMTOOLS:SAMTOOLS_INDEX' {\n ext.prefix = { \"${meta.id}.Lb.sorted\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/library\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_align_intermeds\n ]\n }\n\n withName: 'NFCORE_ATACSEQ:ATACSEQ:.*:BAM_SORT_STATS_SAMTOOLS:BAM_STATS_SAMTOOLS:SAMTOOLS_.*' {\n ext.prefix = { \"${meta.id}.Lb.sorted.bam\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/library/samtools_stats\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: params.save_align_intermeds\n ]\n }\n}\n\nif (params.aligner == 'bwa') {\n process {\n withName: 'BWA_MEM' {\n ext.args = {\n [\n '-M',\n params.bwa_min_score ? \" -T ${params.bwa_min_score}\" : '',\n meta.read_group ? \"-R ${meta.read_group}\": ''\n ].join(' ').trim()\n }\n ext.args2 = '-bhS -F 0x0100 -O BAM'\n ext.prefix = { \"${meta.id}.Lb\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/library\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: false\n ]\n }\n }\n}\n\nif (params.aligner == 'bowtie2') {\n process {\n withName: 'BOWTIE2_ALIGN' {\n ext.args = {\n [\n meta.read_group ? \"--rg-id ${meta.id} --rg SM:${meta.id - ~/_T\\d+$/} --rg PL:ILLUMINA --rg LB:${meta.id} --rg PU:1\" : '',\n params.seq_center ? \"--rg CN:${params.seq_center}\" : ''\n ].join(' ').trim()\n }\n ext.prefix = { \"${meta.id}.Lb\" }\n publishDir = [\n [\n path: { \"${params.outdir}/${params.aligner}/library\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: false\n ],\n [\n path: { \"${params.outdir}/${params.aligner}/library/unmapped\" },\n mode: params.publish_dir_mode,\n pattern: '*.fastq.gz',\n enabled: params.save_unaligned\n ]\n ]\n }\n }\n}\n\nif (params.aligner == 'chromap') {\n process {\n withName: 'CHROMAP_INDEX' {\n publishDir = [\n path: { \"${params.outdir}/genome/${params.aligner}/index\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: 'CHROMAP_CHROMAP' {\n ext.args = '-l 2000 --Tn5-shift --low-mem --SAM'\n ext.prefix = { \"${meta.id}.Lb\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/library\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename },\n enabled: false\n ]\n }\n }\n}\n\nif (params.aligner == 'star') {\n process {\n withName: 'STAR_ALIGN' {\n ext.args = [\n '--runMode alignReads',\n '--alignIntronMax 1',\n '--alignEndsType EndToEnd',\n '--outSAMtype BAM Unsorted',\n '--readFilesCommand zcat',\n '--runRNGseed 0',\n '--outSAMattributes NH HI AS NM MD',\n params.save_unaligned ? '--outReadsUnmapped Fastx' : ''\n ].join(' ').trim()\n publishDir = [\n [\n path: { \"${params.outdir}/${params.aligner}/library/log\" },\n mode: params.publish_dir_mode,\n pattern: '*.{out,tab}'\n ],\n [\n path: { \"${params.outdir}/${params.aligner}/library\" },\n mode: params.publish_dir_mode,\n pattern: '*.bam',\n enabled: false\n ],\n [\n path: { \"${params.outdir}/${params.aligner}/library/unmapped\" },\n mode: params.publish_dir_mode,\n pattern: '*.fastq.gz',\n enabled: params.save_unaligned\n ]\n ]\n }\n }\n}\n\nprocess {\n withName: 'PICARD_MERGESAMFILES_LIBRARY' {\n ext.args = '--SORT_ORDER coordinate --VALIDATION_STRINGENCY LENIENT --TMP_DIR tmp'\n ext.prefix = { \"${meta.id}.mLb.sorted\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library\" },\n mode: params.publish_dir_mode,\n pattern: '*.bam',\n enabled: params.save_align_intermeds\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_MARKDUPLICATES_PICARD:PICARD_MARKDUPLICATES' {\n ext.args = '--ASSUME_SORTED true --REMOVE_DUPLICATES false --VALIDATION_STRINGENCY LENIENT --TMP_DIR tmp'\n ext.prefix = { \"${meta.id}.mLb.mkD.sorted\" }\n publishDir = [\n [\n path: { \"${params.outdir}/${params.aligner}/merged_library/picard_metrics\" },\n mode: params.publish_dir_mode,\n pattern: '*.metrics.txt'\n ],\n [\n path: { \"${params.outdir}/${params.aligner}/merged_library\" },\n mode: params.publish_dir_mode,\n pattern: '*.bam',\n enabled: params.save_align_intermeds\n ]\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_MARKDUPLICATES_PICARD:SAMTOOLS_INDEX' {\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library\" },\n mode: params.publish_dir_mode,\n pattern: '*.{bai,csi}',\n enabled: params.save_align_intermeds\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_MARKDUPLICATES_PICARD:BAM_STATS_SAMTOOLS:.*' {\n ext.prefix = { \"${meta.id}.mLb.mkD.sorted.bam\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/samtools_stats\" },\n mode: params.publish_dir_mode,\n pattern: '*.{stats,flagstat,idxstats}'\n ]\n }\n\n withName: 'BAMTOOLS_FILTER' {\n ext.args = {\n [\n meta.single_end ? '-F 0x004' : '-F 0x004 -F 0x0008 -f 0x001',\n params.keep_dups ? '' : '-F 0x0400',\n params.keep_multi_map ? '' : '-q 1'\n ].join(' ').trim()\n }\n ext.prefix = { meta.single_end ? \"${meta.id}.mLb.clN.sorted\" : \"${meta.id}.mLb.flT.sorted\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library\" },\n mode: params.publish_dir_mode,\n pattern: '*.bam',\n saveAs: { (meta.single_end || params.save_align_intermeds) ? \"${it}\" : null }\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_FILTER_BAM:SAMTOOLS_INDEX' {\n ext.prefix = { \"${meta.id}.mLb.clN.sorted\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library\" },\n mode: params.publish_dir_mode,\n pattern: '*.{bai,csi}'\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_FILTER_BAM:BAM_STATS_SAMTOOLS:.*' {\n ext.prefix = { \"${meta.id}.mLb.clN.sorted.bam\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/samtools_stats\" },\n mode: params.publish_dir_mode,\n pattern: '*.{stats,flagstat,idxstats}'\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_FILTER_BAM:SAMTOOLS_SORT' {\n ext.args = '-n'\n ext.prefix = { \"${meta.id}.mLb.flT.name_sorted\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library\" },\n mode: params.publish_dir_mode,\n pattern: '*.bam',\n enabled: params.save_align_intermeds\n ]\n }\n\n withName: 'BAM_REMOVE_ORPHANS' {\n ext.args = '--only_fr_pairs'\n ext.prefix = { \"${meta.id}.mLb.clN\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library\" },\n mode: params.publish_dir_mode,\n pattern: '*.bam',\n enabled: params.save_align_intermeds\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_FILTER_BAM:BAM_SORT_STATS_SAMTOOLS:.*' {\n ext.prefix = { \"${meta.id}.mLb.clN.sorted\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library\" },\n mode: params.publish_dir_mode,\n pattern: \"*.{bam,bai}\"\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_FILTER_BAM:BAM_SORT_STATS_SAMTOOLS:BAM_STATS_SAMTOOLS:.*' {\n ext.prefix = { \"${meta.id}.mLb.clN.sorted.bam\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/samtools_stats\" },\n mode: params.publish_dir_mode,\n pattern: \"*.{stats,flagstat,idxstats}\"\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_BAM_TO_BIGWIG:BEDTOOLS_GENOMECOV' {\n ext.args = { (meta.single_end && params.fragment_size > 0) ? \"-fs ${params.fragment_size}\" : '' }\n ext.prefix = { \"${meta.id}.mLb.clN\" }\n publishDir = [\n [\n path: { \"${params.outdir}/${params.aligner}/merged_library/bigwig\" },\n mode: params.publish_dir_mode,\n pattern: \"*.bigWig\"\n ],\n [\n path: { \"${params.outdir}/${params.aligner}/merged_library/bigwig/scale\" },\n mode: params.publish_dir_mode,\n pattern: \"*.txt\"\n ]\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_BAM_TO_BIGWIG:UCSC_BEDGRAPHTOBIGWIG' {\n ext.prefix = { \"${meta.id}.mLb.clN\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/bigwig\" },\n mode: params.publish_dir_mode,\n pattern: \"*.bigWig\"\n ]\n }\n}\n\nif (!params.skip_picard_metrics) {\n process {\n withName: 'MERGED_LIBRARY_PICARD_COLLECTMULTIPLEMETRICS' {\n ext.args = '--VALIDATION_STRINGENCY LENIENT --TMP_DIR tmp'\n ext.prefix = { \"${meta.id}.mLb.clN\" }\n publishDir = [\n [\n path: { \"${params.outdir}/${params.aligner}/merged_library/picard_metrics\" },\n mode: params.publish_dir_mode,\n pattern: \"*_metrics\"\n ],\n [\n path: { \"${params.outdir}/${params.aligner}/merged_library/picard_metrics/pdf\" },\n mode: params.publish_dir_mode,\n pattern: \"*.pdf\"\n ]\n ]\n }\n }\n}\n\nif (!params.skip_preseq) {\n process {\n withName: 'MERGED_LIBRARY_PRESEQ_LCEXTRAP' {\n ext.args = '-verbose -bam -seed 1'\n ext.prefix = { \"${meta.id}.mLb.mkD\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/preseq\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n}\n\nif (!params.skip_plot_profile) {\n process {\n withName: 'DEEPTOOLS_COMPUTEMATRIX_SCALE_REGIONS' {\n ext.args = 'scale-regions --regionBodyLength 1000 --beforeRegionStartLength 3000 --afterRegionStartLength 3000 --missingDataAsZero --skipZeros --smartLabels'\n ext.prefix = { \"${meta.id}.mLb.clN.scale_regions\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/deeptools/plotprofile\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: 'DEEPTOOLS_COMPUTEMATRIX_REFERENCE_POINT' {\n ext.args = 'reference-point --missingDataAsZero --skipZeros --smartLabels --upstream 3000 --downstream 3000'\n ext.prefix = { \"${meta.id}.mLb.clN.reference_point\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/deeptools/plotprofile\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: 'DEEPTOOLS_PLOTPROFILE' {\n ext.prefix = { \"${meta.id}.mLb.clN.reference_point\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/deeptools/plotprofile\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: 'DEEPTOOLS_PLOTHEATMAP' {\n ext.prefix = { \"${meta.id}.mLb.clN.scale_regions\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/deeptools/plotprofile\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n}\n\nif (!params.skip_plot_fingerprint) {\n process {\n withName: 'MERGED_LIBRARY_DEEPTOOLS_PLOTFINGERPRINT' {\n ext.args = {\n [\n '--skipZeros',\n \"--numberOfSamples $params.fingerprint_bins\",\n params.with_control ? \"--labels ${meta.id}.mLb.clN $meta.control\" : \"--labels ${meta.id}.mLb.clN\"\n ].join(' ').trim()\n }\n ext.prefix = { \"${meta.id}.mLb.clN\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/deeptools/plotfingerprint\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n}\n\nprocess {\n withName: '.*:MERGED_LIBRARY_CALL_ANNOTATE_PEAKS:MACS2_CALLPEAK' {\n ext.args = [\n '--keep-dup all',\n '--nomodel',\n params.narrow_peak ? '' : \"--broad --broad-cutoff ${params.broad_cutoff}\",\n params.save_macs_pileup ? '--bdg --SPMR' : '',\n params.macs_pvalue ? \"--pvalue ${params.macs_pvalue}\" : '',\n params.macs_fdr ? \"--qvalue ${params.macs_fdr}\" : ''\n ].join(' ').trim()\n ext.prefix = { \"${meta.id}.mLb.clN\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_CALL_ANNOTATE_PEAKS:FRIP_SCORE' {\n ext.args = '-bed -c -f 0.20'\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/qc\" },\n enabled: false\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_CALL_ANNOTATE_PEAKS:MULTIQC_CUSTOM_PEAKS' {\n ext.prefix = { \"${meta.id}.mLb.clN_peaks\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/qc\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n}\n\nif (!params.skip_peak_annotation) {\n process {\n withName: '.*:MERGED_LIBRARY_CALL_ANNOTATE_PEAKS:HOMER_ANNOTATEPEAKS' {\n ext.args = '-gid'\n ext.prefix = { \"${meta.id}.mLb.clN_peaks\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n\n if (!params.skip_peak_qc) {\n process {\n withName: '.*:MERGED_LIBRARY_CALL_ANNOTATE_PEAKS:PLOT_MACS2_QC' {\n ext.args = '-o ./ -p macs2_peak.mLb.clN'\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/qc\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_CALL_ANNOTATE_PEAKS:PLOT_HOMER_ANNOTATEPEAKS' {\n ext.args = '-o ./'\n ext.prefix = 'macs2_annotatePeaks.mLb.clN'\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/qc\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n }\n}\n\nif (!params.skip_consensus_peaks) {\n process {\n withName: '.*:MERGED_LIBRARY_CONSENSUS_PEAKS:MACS2_CONSENSUS' {\n ext.args = \"--min_replicates ${params.min_reps_consensus}\"\n ext.prefix = \"consensus_peaks.mLb.clN\"\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/consensus\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: '.*:MERGED_LIBRARY_CONSENSUS_PEAKS:SUBREAD_FEATURECOUNTS' {\n ext.args = '-F SAF -O --fracOverlap 0.2'\n ext.prefix = \"consensus_peaks.mLb.clN\"\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/consensus\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n\n if (!params.skip_deseq2_qc) {\n process {\n withName: '.*:MERGED_LIBRARY_CONSENSUS_PEAKS:DESEQ2_QC' {\n ext.args = [\n '--id_col 1',\n '--sample_suffix \\'.mLb.clN.sorted.bam\\'',\n '--count_col 7',\n params.deseq2_vst ? '--vst TRUE' : ''\n ].join(' ').trim()\n ext.prefix = { \"${meta.id}.mLb.clN\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/consensus/deseq2\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n }\n}\n\nif (!params.skip_peak_annotation) {\n process {\n withName: '.*:MERGED_LIBRARY_CONSENSUS_PEAKS:HOMER_ANNOTATEPEAKS' {\n ext.args = '-gid'\n ext.prefix = \"consensus_peaks.mLb.clN\"\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/consensus\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n}\n\nif (!params.skip_ataqv) {\n process {\n withName: 'MERGED_LIBRARY_ATAQV_ATAQV' {\n ext.args = '--ignore-read-groups'\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/ataqv/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n withName: 'MERGED_LIBRARY_ATAQV_MKARV' {\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_library/ataqv/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n}\n\nif (!params.skip_merge_replicates) {\n process {\n withName: 'PICARD_MERGESAMFILES_REPLICATE' {\n ext.args = '--SORT_ORDER coordinate --VALIDATION_STRINGENCY LENIENT --TMP_DIR tmp'\n ext.prefix = { \"${meta.id}.mRp.sorted\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate\" },\n mode: params.publish_dir_mode,\n pattern: '*.bam',\n enabled: params.save_align_intermeds\n ]\n }\n\n withName: '.*:MERGED_REPLICATE_MARKDUPLICATES_PICARD:PICARD_MARKDUPLICATES' {\n ext.args = '--ASSUME_SORTED true --REMOVE_DUPLICATES true --VALIDATION_STRINGENCY LENIENT --TMP_DIR tmp'\n ext.prefix = { \"${meta.id}.mRp.clN.sorted\" }\n publishDir = [\n [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/picard_metrics\" },\n mode: params.publish_dir_mode,\n pattern: '*.metrics.txt'\n ],\n [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate\" },\n mode: params.publish_dir_mode,\n pattern: '*.bam',\n ]\n ]\n }\n\n withName: '.*:MERGED_REPLICATE_MARKDUPLICATES_PICARD:SAMTOOLS_INDEX' {\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate\" },\n mode: params.publish_dir_mode,\n pattern: '*.{bai,csi}'\n ]\n }\n\n withName: '.*:MERGED_REPLICATE_MARKDUPLICATES_PICARD:BAM_STATS_SAMTOOLS:.*' {\n ext.prefix = { \"${meta.id}.mRp.clN.sorted.bam\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/samtools_stats\" },\n mode: params.publish_dir_mode,\n pattern: '*.{stats,flagstat,idxstats}'\n ]\n }\n\n withName: '.*:MERGED_REPLICATE_BAM_TO_BIGWIG:BEDTOOLS_GENOMECOV' {\n ext.args = { (meta.single_end && params.fragment_size > 0) ? \"-fs ${params.fragment_size}\" : '' }\n ext.prefix = { \"${meta.id}.mRp.clN\" }\n publishDir = [\n [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/bigwig\" },\n mode: params.publish_dir_mode,\n pattern: \"*.bigWig\"\n ],\n [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/bigwig/scale\" },\n mode: params.publish_dir_mode,\n pattern: \"*.txt\"\n ]\n ]\n }\n\n withName: '.*:MERGED_REPLICATE_BAM_TO_BIGWIG:UCSC_BEDGRAPHTOBIGWIG' {\n ext.prefix = { \"${meta.id}.mRp.clN\" }\n publishDir = [\n [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/bigwig\" },\n mode: params.publish_dir_mode,\n pattern: \"*.bigWig\"\n ]\n ]\n }\n }\n\n process {\n withName: '.*:MERGED_REPLICATE_CALL_ANNOTATE_PEAKS:MACS2_CALLPEAK' {\n ext.args = [\n '--keep-dup all',\n '--nomodel',\n params.narrow_peak ? '' : \"--broad --broad-cutoff ${params.broad_cutoff}\",\n params.save_macs_pileup ? '--bdg --SPMR' : '',\n ].join(' ').trim()\n ext.prefix = { \"${meta.id}.mRp.clN\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: '.*:MERGED_REPLICATE_CALL_ANNOTATE_PEAKS:FRIP_SCORE' {\n ext.args = '-bed -c -f 0.20'\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/qc\" },\n enabled: false\n ]\n }\n\n withName: '.*:MERGED_REPLICATE_CALL_ANNOTATE_PEAKS:MULTIQC_CUSTOM_PEAKS' {\n ext.prefix = { \"${meta.id}.mRp.clN_peaks\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/qc\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n\n if (!params.skip_peak_annotation ) {\n process {\n withName: '.*:MERGED_REPLICATE_CALL_ANNOTATE_PEAKS:HOMER_ANNOTATEPEAKS' {\n ext.args = '-gid'\n ext.prefix = { \"${meta.id}.mRp.clN_peaks\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n\n if (!params.skip_peak_qc) {\n process {\n withName: '.*:MERGED_REPLICATE_CALL_ANNOTATE_PEAKS:PLOT_MACS2_QC' {\n ext.args = '-o ./ -p macs2_peak.mRp.clN'\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/qc\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: '.*:MERGED_REPLICATE_CALL_ANNOTATE_PEAKS:PLOT_HOMER_ANNOTATEPEAKS' {\n ext.args = '-o ./'\n ext.prefix = 'macs2_annotatePeaks.mRp.clN'\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/qc\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n }\n }\n\n if (!params.skip_consensus_peaks) {\n process {\n withName: '.*:MERGED_REPLICATE_CONSENSUS_PEAKS:MACS2_CONSENSUS' {\n ext.prefix = \"consensus_peaks.mRp.clN\"\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/consensus\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n\n withName: '.*:MERGED_REPLICATE_CONSENSUS_PEAKS:SUBREAD_FEATURECOUNTS' {\n ext.args = '-F SAF -O --fracOverlap 0.2'\n ext.prefix = \"consensus_peaks.mRp.clN\"\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/consensus\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n\n if (!params.skip_deseq2_qc) {\n process {\n withName: '.*:MERGED_REPLICATE_CONSENSUS_PEAKS:DESEQ2_QC' {\n ext.args = [\n '--id_col 1',\n '--sample_suffix \\'.mLb.clN.sorted.bam\\'',\n '--count_col 7',\n params.deseq2_vst ? '--vst TRUE' : ''\n ].join(' ').trim()\n ext.prefix = { \"${meta.id}.mRp.clN\" }\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/consensus/deseq2\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n }\n }\n\n if (!params.skip_peak_annotation) {\n process {\n withName: '.*:MERGED_REPLICATE_CONSENSUS_PEAKS:HOMER_ANNOTATEPEAKS' {\n ext.args = '-gid'\n ext.prefix = \"consensus_peaks.mRp.clN\"\n publishDir = [\n path: { \"${params.outdir}/${params.aligner}/merged_replicate/macs2/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}/consensus\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n }\n}\n\nif (!params.skip_igv) {\n process {\n withName: 'IGV' {\n publishDir = [\n [\n path: { \"${params.outdir}/igv/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}\" },\n mode: params.publish_dir_mode,\n pattern: '*.{txt,xml}'\n ],\n [\n path: { \"${params.outdir}/genome\" },\n mode: params.publish_dir_mode,\n pattern: '*.{fa,fasta,fai}'\n ]\n ]\n }\n }\n}\n\nif (!params.skip_multiqc) {\n process {\n withName: 'MULTIQC' {\n ext.args = params.multiqc_title ? \"--title \\\"$params.multiqc_title\\\"\" : ''\n publishDir = [\n path: { \"${params.outdir}/multiqc/${params.narrow_peak ? '/narrow_peak' : '/broad_peak'}\" },\n mode: params.publish_dir_mode,\n saveAs: { filename -> filename.equals('versions.yml') ? null : filename }\n ]\n }\n }\n}\n" }, { "path": "conf/test.config", "content": "/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Nextflow config file for running minimal tests\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Defines input files and everything required to run a fast and simple pipeline test.\n\n Use as follows:\n nextflow run nf-core/atacseq -profile test, --outdir \n\n----------------------------------------------------------------------------------------\n*/\n\nparams {\n config_profile_name = 'Test profile'\n config_profile_description = 'Minimal test dataset to check pipeline function'\n\n // Limit resources so that this can run on GitHub Actions\n max_cpus = 2\n max_memory = '6.GB'\n max_time = '6.h'\n\n // Input data\n input = 'https://raw.githubusercontent.com/nf-core/test-datasets/atacseq/samplesheet/v2.0/samplesheet_test.csv'\n read_length = 50\n\n // Genome references\n mito_name = 'MT'\n fasta = 'https://raw.githubusercontent.com/nf-core/test-datasets/atacseq/reference/genome.fa'\n gtf = 'https://raw.githubusercontent.com/nf-core/test-datasets/atacseq/reference/genes.gtf'\n\n // For speed to avoid CI time-out\n fingerprint_bins = 100\n}\n" }, { "path": "conf/test_controls.config", "content": "/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Nextflow config file for running minimal tests with control samples\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Defines input files and everything required to run a fast and simple pipeline test.\n\n Use as follows:\n nextflow run nf-core/atacseq -profile test_controls, --outdir \n\n----------------------------------------------------------------------------------------\n*/\n\nparams {\n config_profile_name = 'Test profile with controls'\n config_profile_description = 'Minimal test dataset to check pipeline function'\n\n // Limit resources so that this can run on GitHub Actions\n max_cpus = 2\n max_memory = '6.GB'\n max_time = '6.h'\n\n // Input data\n input = 'https://raw.githubusercontent.com/nf-core/test-datasets/atacseq/samplesheet/v2.1/samplesheet_test_controls.csv'\n read_length = 50\n\n // Genome references\n mito_name = 'MT'\n fasta = 'https://raw.githubusercontent.com/nf-core/test-datasets/atacseq/reference/genome.fa'\n gtf = 'https://raw.githubusercontent.com/nf-core/test-datasets/atacseq/reference/genes.gtf'\n\n // For speed to avoid CI time-out\n fingerprint_bins = 100\n}\n" }, { "path": "conf/test_full.config", "content": "/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Nextflow config file for running full-size tests\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Defines input files and everything required to run a full size pipeline test.\n\n Use as follows:\n nextflow run nf-core/atacseq -profile test_full, --outdir \n\n----------------------------------------------------------------------------------------\n*/\n\nparams {\n config_profile_name = 'Full test profile'\n config_profile_description = 'Full test dataset to check pipeline function'\n\n // Input data\n input = 'https://raw.githubusercontent.com/nf-core/test-datasets/atacseq/samplesheet/v2.0/samplesheet_full.csv'\n\n // Used to calculate --macs_gsize\n read_length = 50\n\n // Genome references\n genome = 'hg19'\n}\n" }, { "path": "docs/README.md", "content": "# nf-core/atacseq: Documentation\n\nThe nf-core/atacseq documentation is split into the following pages:\n\n- [Usage](usage.md)\n - An overview of how the pipeline works, how to run it and a description of all of the different command-line flags.\n- [Output](output.md)\n - An overview of the different results produced by the pipeline and how to interpret them.\n\nYou can find a lot more documentation about installing, configuring and running nf-core pipelines on the website: [https://nf-co.re](https://nf-co.re)\n" }, { "path": "docs/output.md", "content": "# ![nf-core/atacseq](images/nf-core-atacseq_logo.png)\n\n## Introduction\n\nThis document describes the output produced by the pipeline. Most of the plots are taken from the MultiQC report, which summarises results at the end of the pipeline.\n\n## Pipeline overview\n\nThe pipeline is built using [Nextflow](https://www.nextflow.io/). See [`main README.md`](../README.md) for a condensed overview of the steps in the pipeline, and the bioinformatics tools used at each step.\n\nSee [Illumina website](https://emea.illumina.com/science/sequencing-method-explorer/kits-and-arrays/atac-seq.html) for more information regarding the ATAC-seq protocol, and for an extensive list of publications.\n\nThe directories listed below will be created in the output directory after the pipeline has finished. All paths are relative to the top-level results directory.\n\n## Library-level analysis\n\nThe initial QC and alignments are performed at the library-level e.g. if the same library has been sequenced more than once to increase sequencing depth. This has the advantage of being able to assess each library individually, and the ability to process multiple libraries from the same sample in parallel.\n\n### Raw read QC\n\n
\nOutput files\n\n- `fastqc/`\n - `*_fastqc.html`: FastQC report containing quality metrics for read 1 (_and read2 if paired-end_) **before** adapter trimming.\n- `fastqc/zips/`\n - `*_fastqc.zip`: Zip archive containing the FastQC report, tab-delimited data file and plot images.\n\n
\n\n[FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/) gives general quality metrics about your reads. It provides information about the quality score distribution across your reads, the per base sequence content (%A/C/G/T). You get information about adapter contamination and other overrepresented sequences. For further reading and documentation see the [FastQC help pages](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/).\n\n### Adapter trimming\n\n
\nOutput files\n\n- `trimgalore/`\n - `*fastq.gz`: If `--save_trimmed` is specified, FastQ files **after** adapter trimming will be placed in this directory.\n- `trimgalore/logs/`\n - `*.log`: Log file generated by Trim Galore!.\n- `trimgalore/fastqc/`\n - `*_fastqc.html`: FastQC report containing quality metrics for read 1 (_and read2 if paired-end_) **after** adapter trimming.\n- `trimgalore/fastqc/zips/`\n - `*_fastqc.zip`: Zip archive containing the FastQC report, tab-delimited data file and plot images.\n\n
\n\n[Trim Galore!](https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) is a wrapper tool around Cutadapt and FastQC to consistently apply quality and adapter trimming to FastQ files. By default, Trim Galore! will automatically detect and trim the appropriate adapter sequence. For most ATAC-seq datasets this will be the Nextera adapter sequence 'CTGTCTCTTATA'. See [`usage.md`](usage.md) for more details about the trimming options.\n\n![MultiQC - Cutadapt trimmed sequence plot](images/mqc_cutadapt_plot.png)\n\n### Alignment\n\nThe pipeline has been written in a way where all the files generated downstream of the alignment are placed in the same directory as specified by `--aligner` e.g. if `--aligner bwa` is specified then all the downstream results will be placed in the `bwa/` directory. This helps with organising the directory structure and more importantly, allows the end-user to get the results from multiple aligners by simply re-running the pipeline with a different `--aligner` option along the `-resume` parameter. It also means that results won't be overwritten when resuming the pipeline and can be used for benchmarking between alignment algorithms if required. Thus, `` in the directory structure below corresponds to the aligner set when running the pipeline.\n\n
\nOutput files\n\n- `/library/`\n - `*.bam`: The files resulting from the alignment of individual libraries are not saved by default so this directory will not be present in your results. You can override this behaviour with the use of the `--save_align_intermeds` flag in which case it will contain the coordinate sorted alignment files in [`*.bam`](https://samtools.github.io/hts-specs/SAMv1.pdf) format.\n- `/library/samtools_stats/`\n - SAMtools `*.flagstat`, `*.idxstats` and `*.stats` files generated from the alignment files.\n\n> **NB:** File names in the resulting directory (i.e. `/library/`) will have the '`.Lb.`' suffix.\n\n
\n\nAdapter-trimmed reads are mapped to the reference assembly using the aligner set by the `--aligner` parameter. Available aligners are [BWA](http://bio-bwa.sourceforge.net/bwa.shtml) (default), [Bowtie 2](http://bowtie-bio.sourceforge.net/bowtie2/index.shtml), [Chromap](https://github.com/haowenz/chromap) and [STAR](https://github.com/alexdobin/STAR). A genome index is required to run any of this aligners so if this is not provided explicitly using the corresponding parameter (e.g. `--bwa_index`), then it will be created automatically from the genome fasta input. The index creation process can take a while for larger genomes so it is possible to use the `--save_reference` parameter to save the indices for future pipeline runs, reducing processing times.\n\n![MultiQC - SAMtools stats plot](images/mqc_samtools_stats_plot.png)\n\n![MultiQC - SAMtools idxstats plot](images/mqc_samtools_idxstats_plot.png)\n\n> **NB:** Currently, paired-end files produced by `Chromap` are excluded from downstream analysis due to [this](https://github.com/nf-core/chipseq/issues/291) issue. Single-end files are processed normally.\n\n## Merged library-level analysis\n\nThe library-level alignments associated with the same sample are merged and subsequently used for the downstream analyses.\n\n#### Unmapped reads\n\nThe `--save_unaligned` parameter enables to obtain FastQ files containing unmapped reads (only available for STAR and Bowtie2).\n\n
\nOutput files\n- `/library/unmapped/`\n - `*.fastq.gz`: If `--save_unaligned` is specified, FastQ files containing unmapped reads will be placed in this directory.\n\n
\n\n#### STAR logs\n\n
\nOutput files\n\n- `star/library/log/`\n - `*.SJ.out.tab`: File containing filtered splice junctions detected after mapping the reads.\n - `*.Log.final.out`: STAR alignment report containing the mapping results summary.\n - `*.Log.out` and `*.Log.progress.out`: STAR log files containing detailed information about the run. Typically only useful for debugging purposes.\n\n
\n\n## Merged library-level analysis\n\nThe library-level alignments associated with the same sample are merged and subsequently used for the downstream analyses.\n\n### Alignment merging, duplicate marking, filtering and QC\n\n
\nOutput files\n\n- `/merged_library/`\n - `*.bam`: Merged library-level, coordinate sorted `*.bam` files after the marking of duplicates, and filtering based on various criteria. The file suffix for the final filtered files will be `*.mLb.clN.*`. If you specify the `--save_align_intermeds` parameter then two additional sets of files will be present. These represent the unfiltered alignments with duplicates marked (`*.mLb.mkD.*`), and in the case of paired-end datasets the filtered alignments before the removal of orphan read pairs (`*.mLb.flT.*`).\n- `/merged_library/samtools_stats/`\n - SAMtools `*.flagstat`, `*.idxstats` and `*.stats` files generated from the alignment files.\n- `/merged_library/picard_metrics/`\n - `*_metrics`: Alignment QC files from picard CollectMultipleMetrics.\n - `*.metrics.txt`: Metrics file from MarkDuplicates.\n- `/merged_library/picard_metrics/pdf/`\n - `*.pdf`: Alignment QC plot files from picard CollectMultipleMetrics.\n- `/merged_library/preseq/`\n - `*.lc_extrap.txt`: Preseq expected future yield file.\n\n> **NB:** File names in the resulting directory (i.e. `/merged_library/`) will have the '`.mLb.`' suffix.\n\n
\n\n[Picard MergeSamFiles and MarkDuplicates](https://broadinstitute.github.io/picard/command-line-overview.html) are used in combination to merge the alignments, and for the marking of duplicates, respectively. If you only have one library for any given replicate then the merging step is not carried out because the library-level and merged library-level BAM files will be exactly the same.\n\n![MultiQC - Picard deduplication stats plot](images/mqc_picard_deduplication_plot.png)\n\nRead duplicate marking is carried out using the Picard MarkDuplicates command. Duplicate reads are generally removed from the aligned reads to mitigate for fragments in the library that may have been sequenced more than once due to PCR biases. There is an option to keep duplicate reads with the `--keep_dups` parameter but its generally recommended to remove them to avoid the wrong interpretation of the results. A similar option has been provided to keep reads that are multi-mapped - `--keep_multi_map`. Other steps have been incorporated into the pipeline to filter the resulting alignments - see [`main README.md`](../README.md) for a more comprehensive listing, and the tools used at each step. A selection of alignment-based QC metrics generated by Picard CollectMultipleMetrics and MarkDuplicates will be included in the MultiQC report.\n\n![MultiQC - Picard insert size plot](images/mqc_picard_insert_size_plot.png)\n\nCertain cell types and tissues yield an enormous fraction (typically 20–80%) of unusable sequences of mitochondrial origin. This is a known problem that is specific to ATAC-seq library preps - see [Montefiori et al. 2017](https://www.nature.com/articles/s41598-017-02547-w). There is an option to keep these reads using the `--keep_mito` parameter but its generally recommended to remove these in order to get a more reliable assessment of the duplication rate from the rest of the genome, and to avoid any biases in the downstream analyses.\n\nThe [Preseq](http://smithlabresearch.org/software/preseq/) package is aimed at predicting and estimating the complexity of a genomic sequencing library, equivalent to predicting and estimating the number of redundant reads from a given sequencing depth and how many will be expected from additional sequencing using an initial sequencing experiment. The estimates can then be used to examine the utility of further sequencing, optimize the sequencing depth, or to screen multiple libraries to avoid low complexity samples. The dashed line shows a perfectly complex library where total reads = unique reads. Note that these are predictive numbers only, not absolute. The MultiQC plot can sometimes give extreme sequencing depth on the X axis - click and drag from the left side of the plot to zoom in on more realistic numbers.\n\n![MultiQC - Preseq library complexity plot](images/mqc_preseq_plot.png)\n\n### Normalised bigWig files\n\n
\nOutput files\n\n- `/merged_library/bigwig/`\n - `*.bigWig`: Normalised bigWig files scaled to 1 million mapped reads.\n\n
\n\nThe [bigWig](https://genome.ucsc.edu/goldenpath/help/bigWig.html) format is in an indexed binary format useful for displaying dense, continuous data in Genome Browsers such as the [UCSC](https://genome.ucsc.edu/cgi-bin/hgTracks) and [IGV](http://software.broadinstitute.org/software/igv/). This mitigates the need to load the much larger BAM files for data visualisation purposes which will be slower and result in memory issues. The coverage values represented in the bigWig file can also be normalised in order to be able to compare the coverage across multiple samples - this is not possible with BAM files. The bigWig format is also supported by various bioinformatics software for downstream processing such as meta-profile plotting.\n\n### Coverage QC\n\n
\nOutput files\n\n- `/merged_library/deeptools/plotfingerprint/`\n - `*.plotFingerprint.pdf`, `*.plotFingerprint.qcmetrics.txt`, `*.plotFingerprint.raw.txt`: plotFingerprint output files.\n- `/merged_library/deeptools/plotprofile/`\n - `*.computeMatrix.mat.gz`, `*.computeMatrix.vals.mat.tab`, `*.plotProfile.pdf`, `*.plotProfile.tab`, `*.plotHeatmap.pdf`, `*.plotHeatmap.mat.tab`: plotProfile output files.\n\n
\n\n[deepTools](https://deeptools.readthedocs.io/en/develop/content/list_of_tools.html) plotFingerprint is a useful QC for ATAC-seq data in order to see the relative enrichment of the samples in the experiment on a genome-wide basis (see [plotFingerprint docs](https://deeptools.readthedocs.io/en/develop/content/tools/plotFingerprint.html)).\n\n![MultiQC - deepTools plotFingerprint plot](images/mqc_deeptools_plotFingerprint_plot.png)\n\nThe results from deepTools plotProfile gives you a quick visualisation for the genome-wide enrichment of your samples at the TSS, and across the gene body. During the downstream analysis, you may want to refine the features/genes used to generate these plots in order to see a more specific condition-related effect.\n\n![MultiQC - deepTools plotProfile plot](images/mqc_deeptools_plotProfile_plot.png)\n\n### Call peaks\n\n
\nOutput files\n\n- `/merged_library/macs2//`\n - `*.xls`, `*.broadPeak` or `*.narrowPeak`, `*.gappedPeak`, `*summits.bed`: MACS2 output files - the files generated will depend on whether MACS2 has been run in _narrowPeak_ or _broadPeak_ mode.\n - `*.annotatePeaks.txt`: HOMER peak-to-gene annotation file.\n- `/merged_library/macs2//qc/`\n - `macs_peak.plots.pdf`: QC plots for MACS2 peaks.\n - `macs_annotatePeaks.plots.pdf`: QC plots for peak-to-gene feature annotation.\n - `*.FRiP_mqc.tsv`, `*.count_mqc.tsv`, `macs_annotatePeaks.summary_mqc.tsv`: MultiQC custom-content files for FRiP score, peak count and peak-to-gene ratios.\n\n> **NB:** `` in the directory structure above corresponds to the type of peak that you have specified to call with MACS2 i.e. `broad_peak` or `narrow_peak`. If you so wish, you can call both narrow and broad peaks without redoing the preceding steps in the pipeline such as the alignment and filtering. For example, if you already have broad peaks then just add `--narrow_peak -resume` to the command you used to run the pipeline, and these will be called too! However, resuming the pipeline will only be possible if you have not deleted the `work/` directory generated by the pipeline.\n\n
\n\n[MACS2](https://github.com/taoliu/MACS) is one of the most popular peak-calling algorithms for ChIP-seq data. For ATAC-seq data we are also looking for genome-wide regions of enrichment but in this case without comparison to a standard control sample (e.g. input DNA). By default, the peaks are called with the MACS2 `--broad` parameter. If, however, you would like to call narrow peaks then please provide the `--narrow_peak` parameter when running the pipeline. See [MACS2 outputs](https://github.com/taoliu/MACS#output-files) for a description of the output files generated by MACS2.\n\n![MultiQC - MACS2 total peak count plot](images/mqc_macs2_peak_count_plot.png)\n\n[HOMER annotatePeaks.pl](http://homer.ucsd.edu/homer/ngs/annotation.html) is used to annotate the peaks relative to known genomic features. HOMER is able to use the `--gtf` annotation file which is provided to the pipeline. Please note that some of the output columns will be blank because the annotation is not provided using HOMER's in-built database format. However, the more important fields required for downstream analysis will be populated i.e. _Annotation_, _Distance to TSS_ and _Nearest Promoter ID_.\n\n![MultiQC - HOMER annotatePeaks peak-to-gene feature ratio plot](images/mqc_annotatePeaks_feature_percentage_plot.png)\n\nVarious QC plots per sample including number of peaks, fold-change distribution, [FRiP score](https://genome.cshlp.org/content/22/9/1813.full.pdf+html) and peak-to-gene feature annotation are also generated by the pipeline. Where possible these have been integrated into the MultiQC report.\n\n![MultiQC - MACS2 peaks FRiP score plot](images/mqc_frip_score_plot.png)\n\n### Create and quantify consensus set of peaks\n\n
\nOutput files\n\n- `/merged_library/macs2//consensus/`\n - `*.bed`: Consensus peak-set across all samples in BED format.\n - `*.saf`: Consensus peak-set across all samples in SAF format. Required by featureCounts for read quantification.\n - `*.featureCounts.txt`: Read counts across all samples relative to consensus peak-set.\n - `*.annotatePeaks.txt`: HOMER peak-to-gene annotation file for consensus peaks.\n - `*.boolean.annotatePeaks.txt`: Spreadsheet representation of consensus peak-set across samples **with** gene annotation columns. The columns from individual peak files are included in this file along with the ability to filter peaks based on their presence or absence in multiple replicates/conditions.\n - `*.boolean.txt`: Spreadsheet representation of consensus peak-set across samples **without** gene annotation columns. Same as file above but without annotation columns.\n - `*.boolean.intersect.plot.pdf`, `*.boolean.intersect.txt`: [UpSetR](https://cran.r-project.org/web/packages/UpSetR/README.html) files to illustrate peak intersection.\n\n
\n\nIn order to perform the differential accessibility analysis we need to be able to carry out the read quantification for the same intervals across **all** of the samples in the experiment. To this end, the individual peak-sets called per sample have to be merged together in order to create a consensus set of peaks.\n\nUsing the consensus peaks it is possible to assess the degree of overlap between the peaks from a set of samples e.g. _Which consensus peaks contain peaks that are common/unique to a given set of samples?_. This may be useful for downstream filtering of peaks based on whether they are called in multiple replicates/conditions. Please note that it is possible for a consensus peak to contain multiple peaks from the same sample. Unfortunately, this is sample-dependent but the files generated by the pipeline do have columns that report such instances and allow you to factor them into any further analysis.\n\n![R - UpSetR peak intersection plot](images/r_upsetr_intersect_plot.png)\n\nBy default, the peak-sets are not filtered, therefore, the consensus peaks will be generated across the union set of peaks from all samples. However, you can increment the `--min_reps_consensus` parameter appropriately if you are confident you have good reproducibility amongst your replicates to create a \"reproducible\" set of consensus of peaks. In future iterations of the pipeline more formal analyses such as [IDR](https://projecteuclid.org/euclid.aoas/1318514284) may be implemented to obtain reproducible and high confidence peak-sets with which to perform this sort of analysis.\n\nThe [featureCounts](http://bioinf.wehi.edu.au/featureCounts/) tool is used to count the number of reads relative to the consensus peak-set across all of the samples. This essentially generates a file containing a matrix where the rows represent the consensus intervals, the columns represent all of the samples in the experiment, and the values represent the raw read counts.\n\n![MultiQC - featureCounts consensus peak read assignment plot](images/mqc_featureCounts_assignment_plot.png)\n\n### Read counting and differential accessibility analysis\n\n
\nOutput files\n\n- `/merged_library/macs2//consensus/deseq2/`\n - `*.plots.pdf`: File containing PCA and hierarchical clustering plots.\n - `*.dds.RData`: File containing R `DESeqDataSet` object generated by DESeq2, with either\n an rlog or vst `assay` storing the variance-stabilised data.\n - `*.rds`: Alternative version of the RData file suitable for\n `readRDS` to give user control of the eventual object name.\n - `*pca.vals.txt`: Matrix of values for the first 2 principal components.\n - `*.sample.dists.txt`: Sample distance matrix.\n - `R_sessionInfo.log`: File containing information about R, the OS and attached or loaded packages.\n- `/merged_library/macs2//consensus/sizeFactors/`\n - `*.txt`, `*.RData`: Files containing DESeq2 sizeFactors per sample.\n\n
\n\n[DESeq2](https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html) is more commonly used to perform differential expression analysis for RNA-seq datasets. However, it can also be used for ATAC-seq differential accessibility analysis, in which case you can imagine that instead of counts per gene for RNA-seq data we now have counts per accessible region.\n\n**This pipeline uses a standardised DESeq2 analysis script to get an idea of the reproducibility within the experiment, and to assess the overall differential accessibility. Please note that this will not suit every experimental design, and if there are other problems with the experiment then it may not work as well as expected.**\n\nThe script included in the pipeline uses DESeq2 to normalise read counts across all of the provided samples in order to create a PCA plot and a clustered heatmap showing pairwise Euclidean distances between the samples in the experiment. These help to show the similarity between groups of samples and can reveal batch effects and other potential issues with the experiment.\n\nBy default, the pipeline uses the `vst` transformation which is more suited to larger experiments. You can set the parameter `--deseq2_vst false` if you wish to use the DESeq2 native `rlog` option. See [DESeq2 docs](http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#data-transformations-and-visualization) for a more detailed explanation.\n\n![MultiQC - DESeq2 PCA plot](images/mqc_deseq2_pca_plot.png)\n\n

\"MultiQC

\n\n### ataqv\n\n
\nOutput files\n\n- `/merged_library/ataqv//`\n - `.json`: JSON files containing ATAC-seq specific metrics for each sample.\n- `/merged_library/ataqv//html/`\n - Folder containing ataqv results aggregated across all samples for visualisation via an internet browser.\n\n
\n\n[ataqv](https://parkerlab.github.io/ataqv/) is a toolkit for measuring and comparing ATAC-seq results. It was written to help understand how well ATAC-seq assays have worked, and to make it easier to spot differences that might be caused by library prep or sequencing. Please see [ataqv homepage](https://parkerlab.github.io/ataqv/) for documentation and an example report.\n\n## Merged replicate-level analysis\n\nThe alignments associated with all of the replicates from the same experimental condition can also be merged. This can be useful to increase the coverage for peak-calling and for other analyses that require high sequencing depth such as [motif footprinting](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3959825/). The analysis steps and directory structure for `/merged_library/` and `/merged_replicate/` are almost identical.\n\nFile names in the resulting directory (i.e. `/merged_replicate/`) will have the '`.mRp.`' suffix.\n\nYou can skip this portion of the analysis by specifying the `--skip_merge_replicates` parameter.\n\n> **NB:** Merged library-level alignments will be used for read counting relative to the consensus merged replicate-level peakset. This is the only way in which differential analysis can be performed at the merged replicate-level.\n\n## Aggregate analysis\n\n### Present QC for the raw read, alignment, peak and differential accessibility results\n\n
\nOutput files\n\n- `multiqc//`\n - `multiqc_report.html`: A standalone HTML file that can be viewed in your web browser.\n - `multiqc_data/`: Directory containing parsed statistics from the different tools used in the pipeline.\n - `multiqc_plots/`: Directory containing static images from the report in various formats.\n\n
\n\n[MultiQC](https://multiqc.info/docs/) is a visualisation tool that generates a single HTML report summarising all samples in your project. Most of the pipeline QC results are visualised in the report and further statistics are available within the report data directory.\n\nResults generated by MultiQC collate pipeline QC from FastQC, TrimGalore, samtools flagstat, samtools idxstats, samtools stats, picard CollectMultipleMetrics, picard MarkDuplicates, Preseq, deepTools plotProfile, deepTools plotFingerprint and featureCounts. The default [`multiqc config file`](../assets/multiqc_config.yaml) also contains the provision for loading custom-content to report peak counts, FRiP scores, peak-to-gene annnotation proportions, sample-similarity heatmaps and PCA plots.\n\nThe pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see .\n\n### Create IGV session file\n\n
\nOutput files\n\n- `igv//`\n - `igv_session.xml`: Session file that can be directly loaded into IGV.\n - `igv_files.txt`: File containing a listing of the files used to create the IGV session.\n\n
\n\nAn [IGV](https://software.broadinstitute.org/software/igv/UserGuide) session file will be created at the end of the pipeline containing the normalised bigWig tracks, per-sample peaks, consensus peaks and differential sites. This avoids having to load all of the data individually into IGV for visualisation.\n\nThe genome fasta file required for the IGV session will be the same as the one that was provided to the pipeline. This will be copied into `genome/` to overcome any loading issues. If you prefer to use another path or an in-built genome provided by IGV just change the `genome` entry in the second-line of the session file.\n\nThe file paths in the IGV session file will only work if the results are kept in the same place on your storage. If the results are moved or for example, if you prefer to load the data over the web then just replace the file paths with others that are more appropriate.\n\nOnce installed, open IGV, go to `File > Open Session` and select the `igv_session.xml` file for loading.\n\n![IGV screenshot](images/igv_screenshot.png)\n\n> **NB:** If you are not using an in-built genome provided by IGV you will need to load the annotation yourself e.g. in .gtf and/or .bed format.\n\n## Other results\n\n### Reference genome files\n\n
\nOutput files\n\n- `genome/`\n - A number of genome-specific files are generated by the pipeline in order to aid in the filtering of the data, and because they are required by standard tools such as BEDTools. These can be found in this directory along with the genome fasta file which is required by IGV. If using a genome from AWS iGenomes and if it exists a `README.txt` file containing information about the annotation version will also be saved in this directory.\n- `genome/index/`\n\n - `bwa/`: Directory containing BWA indices.\n - `bowtie2/`: Directory containing BOWTIE2 indices.\n - `chromap/`: Directory containing Chromap indices.\n - `star/`: Directory containing STAR indices.\n\n - If the `--save_reference` parameter is provided then the alignment indices generated by the pipeline will be saved in this directory. This can be quite a time-consuming process so it permits their reuse for future runs of the pipeline or for other purposes.\n\n
\n\nReference genome-specific files can be useful to keep for the downstream processing of the results.\n\n### Pipeline information\n\n
\nOutput files\n\n- `pipeline_info/`\n - Reports generated by Nextflow: `execution_report.html`, `execution_timeline.html`, `execution_trace.txt` and `pipeline_dag.dot`/`pipeline_dag.svg`.\n - Reports generated by the pipeline: `pipeline_report.html`, `pipeline_report.txt` and `software_versions.yml`. The `pipeline_report*` files will only be present if the `--email` / `--email_on_fail` parameter's are used when running the pipeline.\n - Reformatted samplesheet files used as input to the pipeline: `samplesheet.valid.csv`.\n\n
\n\n[Nextflow](https://www.nextflow.io/docs/latest/tracing.html) provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage.\n" }, { "path": "docs/usage.md", "content": "# nf-core/atacseq: Usage\n\n## :warning: Please read this documentation on the nf-core website: [https://nf-co.re/atacseq/usage](https://nf-co.re/atacseq/usage)\n\n> _Documentation of pipeline parameters is generated automatically from the pipeline schema and can no longer be found in markdown files._\n\n## Samplesheet input\n\nYou will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 4 columns, and a header row as shown in the examples below.\n\n```bash\n--input '[path to samplesheet file]'\n```\n\n### Multiple replicates\n\nThe `sample` identifier is the same when you have multiple biological replicates from the same experimental group, just increment the `replicate` identifier appropriately. The first replicate value for any given experimental group must be 1. Below is an example for a single experimental group in triplicate:\n\n```console\nsample,fastq_1,fastq_2,replicate\nCONTROL,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz,1\nCONTROL,AEG588A1_S1_L003_R1_001.fastq.gz,AEG588A1_S1_L003_R2_001.fastq.gz,2\nCONTROL,AEG588A1_S1_L004_R1_001.fastq.gz,AEG588A1_S1_L004_R2_001.fastq.gz,3\n```\n\nThe pipeline will automatically append the `&_REP` suffix to the sample name within the pipeline e.g. `CONTROL_REP1`, `CONTROL_REP2` and `CONTROL_REP3` using the example above. If you don't have replicates you can set the `replicate` value to 1 for all of your samples.\n\n### Multiple runs of the same sample\n\nThe `sample` and `replicate` identifiers have to be the same when you have re-sequenced the same sample more than once e.g. to increase sequencing depth. The pipeline will perform the alignments in parallel, and subsequently merge them before further analysis. Below is an example a sample sequenced across 3 lanes:\n\n```console\nsample,fastq_1,fastq_2,replicate\nCONTROL,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz,1\nCONTROL,AEG588A1_S1_L003_R1_001.fastq.gz,AEG588A1_S1_L003_R2_001.fastq.gz,1\nCONTROL,AEG588A1_S1_L004_R1_001.fastq.gz,AEG588A1_S1_L004_R2_001.fastq.gz,1\n```\n\nThe pipeline will automatically append the `*_T` suffix to the sample name within the pipeline e.g. `CONTROL_REP1_T1`, `CONTROL_REP1_T2` and `CONTROL_REP1_T3` using the example above.\n\n### Control data\n\nIf controls are to be used for peak calling use the parameter `--with_control`. In this case, the samplesheet file needs the additional columns `control` and `control_replicate`. These should be the sample identifier and sample replicate for the controls.\n\n### Full samplesheet\n\nThe pipeline will auto-detect whether a sample is single- or paired-end using the information provided in the samplesheet. The samplesheet can have as many columns as you desire, however, there is a strict requirement for the first 4 columns to match those defined in the table below.\n\nA final samplesheet file consisting of both single- and paired-end data may look something like the one below. This is for 7 samples, where we have biological triplicates for both the `CONTROL` and `TREATMENT` groups, and the third replicate in the `TREATMENT` group has been a technical replicate as a result of being sequenced twice.\n\n```console\nsample,fastq_1,fastq_2,replicate,control,control_replicate\nCONTROL,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz,1,,\nCONTROL,AEG588A2_S2_L002_R1_001.fastq.gz,AEG588A2_S2_L002_R2_001.fastq.gz,2,,\nCONTROL,AEG588A3_S3_L002_R1_001.fastq.gz,AEG588A3_S3_L002_R2_001.fastq.gz,3,,\nTREATMENT,AEG588A4_S4_L003_R1_001.fastq.gz,,1,CONTROL,1\nTREATMENT,AEG588A5_S5_L003_R1_001.fastq.gz,,2,CONTROL,2\nTREATMENT,AEG588A6_S6_L003_R1_001.fastq.gz,,3,CONTROL,3\nTREATMENT,AEG588A6_S6_L004_R1_001.fastq.gz,,3,CONTROL,3\n```\n\n| Column | Description |\n| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `sample` | Custom sample name. This entry will be identical for multiple sequencing libraries/runs from the same sample. Spaces in sample names are automatically converted to underscores (`_`). |\n| `fastq_1` | Full path to FastQ file for Illumina short reads 1. File has to be gzipped and have the extension \".fastq.gz\" or \".fq.gz\". |\n| `fastq_2` | Full path to FastQ file for Illumina short reads 2. File has to be gzipped and have the extension \".fastq.gz\" or \".fq.gz\". |\n| `replicate` | Integer representing replicate number. This will be identical for re-sequenced libraries. Must start from `1..`. |\n| `control` | Sample name for control sample. |\n| `control_replicate` | Integer representing replicate number of the control sample |\n\nExample sheets [without controls](../assets/samplesheet.csv) and [with controls](../assets/samplesheet_with_control.csv) have been provided with the pipeline.\n\n## Reference genome files\n\nThe minimum reference genome requirements are a FASTA and GTF file, all other files required to run the pipeline can be generated from these files. However, it is more storage and compute friendly if you are able to re-use reference genome files as efficiently as possible. It is recommended to use the `--save_reference` parameter if you are using the pipeline to build new indices (e.g. those unavailable on [AWS iGenomes](https://nf-co.re/usage/reference_genomes)) so that you can save them somewhere locally. The index building step can be quite a time-consuming process and it permits their reuse for future runs of the pipeline to save disk space. You can then either provide the appropriate reference genome files on the command-line via the appropriate parameters (e.g. `--bwa_index '/path/to/bwa/index/'`) or via a custom config file.\n\n- If `--genome` is provided then the FASTA and GTF files (and existing indices) will be automatically obtained from AWS-iGenomes unless these have already been downloaded locally in the path specified by `--igenomes_base`.\n- If `--gene_bed` is not provided then it will be generated from the GTF file.\n\n> **NB:** Compressed reference files are also supported by the pipeline i.e. standard files with the `.gz` extension and indices folders with the `tar.gz` extension.\n\n## Blacklist bed files\n\nThe blacklist bed files where obtained using the commands below:\n\n```console\ncd ..\nmkdir -p v1.0\ncd v1.0\nwget -L https://www.encodeproject.org/files/ENCFF001TDO/@@download/ENCFF001TDO.bed.gz && gunzip ENCFF001TDO.bed.gz && mv ENCFF001TDO.bed hg19-blacklist.v1.bed\n\nmkdir -p assets/blacklists/v2.0/\ncd assets/blacklists/v2.0/\nwget -L https://raw.githubusercontent.com/Boyle-Lab/Blacklist/master/lists/ce10-blacklist.v2.bed.gz && gunzip ce10-blacklist.v2.bed.gz\nwget -L https://raw.githubusercontent.com/Boyle-Lab/Blacklist/master/lists/ce11-blacklist.v2.bed.gz && gunzip ce11-blacklist.v2.bed.gz\nwget -L https://raw.githubusercontent.com/Boyle-Lab/Blacklist/master/lists/dm3-blacklist.v2.bed.gz && gunzip dm3-blacklist.v2.bed.gz\nwget -L https://raw.githubusercontent.com/Boyle-Lab/Blacklist/master/lists/dm6-blacklist.v2.bed.gz && gunzip dm6-blacklist.v2.bed.gz\nwget -L https://raw.githubusercontent.com/Boyle-Lab/Blacklist/master/lists/hg19-blacklist.v2.bed.gz && gunzip hg19-blacklist.v2.bed.gz\nwget -L https://raw.githubusercontent.com/Boyle-Lab/Blacklist/master/lists/hg38-blacklist.v2.bed.gz && gunzip hg38-blacklist.v2.bed.gz\nwget -L https://raw.githubusercontent.com/Boyle-Lab/Blacklist/master/lists/mm10-blacklist.v2.bed.gz && gunzip mm10-blacklist.v2.bed.gz\n\ncd ..\nmkdir -p v3.0\ncd v3.0\nwget -L https://www.encodeproject.org/files/ENCFF356LFX/@@download/ENCFF356LFX.bed.gz && gunzip ENCFF356LFX.bed.gz && mv ENCFF356LFX.bed hg38-blacklist.v3.bed\n```\n\n> **NB:** A detailed description of the different versions of the files can be found [here](https://sites.google.com/site/anshulkundaje/projects/blacklists). Also, to to see which blacklist bed files are assigned by default to the respective reference genome check the [igenomes.config](https://github.com/nf-core/chipseq/blob/master/conf/igenomes.config).\n\n## Running the pipeline\n\nThe typical command for running the pipeline is as follows:\n\n```bash\nnextflow run nf-core/atacseq --input ./samplesheet.csv --outdir ./results --genome GRCh37 --read_length 150 -profile docker\n```\n\nThis will launch the pipeline with the `docker` configuration profile. See below for more information about profiles.\n\nNote that the pipeline will create the following files in your working directory:\n\n```bash\nwork # Directory containing the nextflow working files\n # Finished results in specified location (defined with --outdir)\n.nextflow_log # Log file from Nextflow\n# Other nextflow hidden files, eg. history of pipeline runs and old logs.\n```\n\nIf you wish to repeatedly use the same parameters for multiple runs, rather than specifying each flag in the command, you can specify these in a params file.\n\nPipeline settings can be provided in a `yaml` or `json` file via `-params-file `.\n\n> ⚠️ Do not use `-c ` to specify parameters as this will result in errors. Custom config files specified with `-c` must only be used for [tuning process resource specifications](https://nf-co.re/docs/usage/configuration#tuning-workflow-resources), other infrastructural tweaks (such as output directories), or module arguments (args).\n\nThe above pipeline run specified with a params file in yaml format:\n\n```bash\nnextflow run nf-core/atacseq -profile docker -params-file params.yaml\n```\n\nwith `params.yaml` containing:\n\n```yaml\ninput: './samplesheet.csv'\noutdir: './results/'\ngenome: 'GRCh37'\nread_length: 150\n<...>\n```\n\nYou can also generate such `YAML`/`JSON` files via [nf-core/launch](https://nf-co.re/launch).\n\n### Updating the pipeline\n\nWhen you run the above command, Nextflow automatically pulls the pipeline code from GitHub and stores it as a cached version. When running the pipeline after this, it will always use the cached version if available - even if the pipeline has been updated since. To make sure that you're running the latest version of the pipeline, make sure that you regularly update the cached version of the pipeline:\n\n```bash\nnextflow pull nf-core/atacseq\n```\n\n### Reproducibility\n\nIt is a good idea to specify a pipeline version when running the pipeline on your data. This ensures that a specific version of the pipeline code and software are used when you run your pipeline. If you keep using the same tag, you'll be running the same version of the pipeline, even if there have been changes to the code since.\n\nFirst, go to the [nf-core/atacseq releases page](https://github.com/nf-core/atacseq/releases) and find the latest pipeline version - numeric only (eg. `1.3.1`). Then specify this when running the pipeline with `-r` (one hyphen) - eg. `-r 1.3.1`. Of course, you can switch to another version by changing the number after the `-r` flag.\n\nThis version number will be logged in reports when you run the pipeline, so that you'll know what you used when you look back in the future. For example, at the bottom of the MultiQC reports.\n\nTo further assist in reproducbility, you can use share and re-use [parameter files](#running-the-pipeline) to repeat pipeline runs with the same settings without having to write out a command with every single parameter.\n\n> 💡 If you wish to share such profile (such as upload as supplementary material for academic publications), make sure to NOT include cluster specific paths to files, nor institutional specific profiles.\n\n## Core Nextflow arguments\n\n> **NB:** These options are part of Nextflow and use a _single_ hyphen (pipeline parameters use a double-hyphen).\n\n### `-profile`\n\nUse this parameter to choose a configuration profile. Profiles can give configuration presets for different compute environments.\n\nSeveral generic profiles are bundled with the pipeline which instruct the pipeline to use software packaged using different methods (Docker, Singularity, Podman, Shifter, Charliecloud, Apptainer, Conda) - see below.\n\n> We highly recommend the use of Docker or Singularity containers for full pipeline reproducibility, however when this is not possible, Conda is also supported.\n\nThe pipeline also dynamically loads configurations from [https://github.com/nf-core/configs](https://github.com/nf-core/configs) when it runs, making multiple config profiles for various institutional clusters available at run time. For more information and to see if your system is available in these configs please see the [nf-core/configs documentation](https://github.com/nf-core/configs#documentation).\n\nNote that multiple profiles can be loaded, for example: `-profile test,docker` - the order of arguments is important!\nThey are loaded in sequence, so later profiles can overwrite earlier profiles.\n\nIf `-profile` is not specified, the pipeline will run locally and expect all software to be installed and available on the `PATH`. This is _not_ recommended, since it can lead to different results on different machines dependent on the computer enviroment.\n\n- `test`\n - A profile with a complete configuration for automated testing\n - Includes links to test data so needs no other parameters\n- `docker`\n - A generic configuration profile to be used with [Docker](https://docker.com/)\n- `singularity`\n - A generic configuration profile to be used with [Singularity](https://sylabs.io/docs/)\n- `podman`\n - A generic configuration profile to be used with [Podman](https://podman.io/)\n- `shifter`\n - A generic configuration profile to be used with [Shifter](https://nersc.gitlab.io/development/shifter/how-to-use/)\n- `charliecloud`\n - A generic configuration profile to be used with [Charliecloud](https://hpc.github.io/charliecloud/)\n- `apptainer`\n - A generic configuration profile to be used with [Apptainer](https://apptainer.org/)\n- `conda`\n - A generic configuration profile to be used with [Conda](https://conda.io/docs/). Please only use Conda as a last resort i.e. when it's not possible to run the pipeline with Docker, Singularity, Podman, Shifter, Charliecloud, or Apptainer.\n\n### `-resume`\n\nSpecify this when restarting a pipeline. Nextflow will use cached results from any pipeline steps where the inputs are the same, continuing from where it got to previously. For input to be considered the same, not only the names must be identical but the files' contents as well. For more info about this parameter, see [this blog post](https://www.nextflow.io/blog/2019/demystifying-nextflow-resume.html).\n\nYou can also supply a run name to resume a specific run: `-resume [run-name]`. Use the `nextflow log` command to show previous run names.\n\n### `-c`\n\nSpecify the path to a specific config file (this is a core Nextflow command). See the [nf-core website documentation](https://nf-co.re/usage/configuration) for more information.\n\n## Custom configuration\n\n### Resource requests\n\nWhilst the default requirements set within the pipeline will hopefully work for most people and with most input data, you may find that you want to customise the compute resources that the pipeline requests. Each step in the pipeline has a default set of requirements for number of CPUs, memory and time. For most of the steps in the pipeline, if the job exits with any of the error codes specified [here](https://github.com/nf-core/rnaseq/blob/4c27ef5610c87db00c3c5a3eed10b1d161abf575/conf/base.config#L18) it will automatically be resubmitted with higher requests (2 x original, then 3 x original). If it still fails after the third attempt then the pipeline execution is stopped.\n\nTo change the resource requests, please see the [max resources](https://nf-co.re/docs/usage/configuration#max-resources) and [tuning workflow resources](https://nf-co.re/docs/usage/configuration#tuning-workflow-resources) section of the nf-core website.\n\n### Custom Containers\n\nIn some cases you may wish to change which container or conda environment a step of the pipeline uses for a particular tool. By default nf-core pipelines use containers and software from the [biocontainers](https://biocontainers.pro/) or [bioconda](https://bioconda.github.io/) projects. However in some cases the pipeline specified version maybe out of date.\n\nTo use a different container from the default container or conda environment specified in a pipeline, please see the [updating tool versions](https://nf-co.re/docs/usage/configuration#updating-tool-versions) section of the nf-core website.\n\n### Custom Tool Arguments\n\nA pipeline might not always support every possible argument or option of a particular tool used in pipeline. Fortunately, nf-core pipelines provide some freedom to users to insert additional parameters that the pipeline does not include by default.\n\nTo learn how to provide additional arguments to a particular tool of the pipeline, please see the [customising tool arguments](https://nf-co.re/docs/usage/configuration#customising-tool-arguments) section of the nf-core website.\n\n### nf-core/configs\n\nIn most cases, you will only need to create a custom config as a one-off but if you and others within your organisation are likely to be running nf-core pipelines regularly and need to use the same settings regularly it may be a good idea to request that your custom config file is uploaded to the `nf-core/configs` git repository. Before you do this please can you test that the config file works with your pipeline of choice using the `-c` parameter. You can then create a pull request to the `nf-core/configs` repository with the addition of your config file, associated documentation file (see examples in [`nf-core/configs/docs`](https://github.com/nf-core/configs/tree/master/docs)), and amending [`nfcore_custom.config`](https://github.com/nf-core/configs/blob/master/nfcore_custom.config) to include your custom profile.\n\nSee the main [Nextflow documentation](https://www.nextflow.io/docs/latest/config.html) for more information about creating your own configuration files.\n\nIf you have any questions or issues please send us a message on [Slack](https://nf-co.re/join/slack) on the [`#configs` channel](https://nfcore.slack.com/channels/configs).\n\n## Azure Resource Requests\n\nTo be used with the `azurebatch` profile by specifying the `-profile azurebatch`.\nWe recommend providing a compute `params.vm_type` of `Standard_D16_v3` VMs by default but these options can be changed if required.\n\nNote that the choice of VM size depends on your quota and the overall workload during the analysis.\nFor a thorough list, please refer the [Azure Sizes for virtual machines in Azure](https://docs.microsoft.com/en-us/azure/virtual-machines/sizes).\n\n## Running in the background\n\nNextflow handles job submissions and supervises the running jobs. The Nextflow process must run until the pipeline is finished.\n\nThe Nextflow `-bg` flag launches Nextflow in the background, detached from your terminal so that the workflow does not stop if you log out of your session. The logs are saved to a file.\n\nAlternatively, you can use `screen` / `tmux` or similar tool to create a detached session which you can log back into at a later time.\nSome HPC setups also allow you to run nextflow within a cluster job submitted your job scheduler (from where it submits more jobs).\n\n## Nextflow memory requirements\n\nIn some cases, the Nextflow Java virtual machines can start to request a large amount of memory.\nWe recommend adding the following line to your environment to limit this (typically in `~/.bashrc` or `~./bash_profile`):\n\n```bash\nNXF_OPTS='-Xms1g -Xmx4g'\n```\n" }, { "path": "lib/NfcoreTemplate.groovy", "content": "//\n// This file holds several functions used within the nf-core pipeline template.\n//\n\nimport org.yaml.snakeyaml.Yaml\n\nclass NfcoreTemplate {\n\n //\n // Check AWS Batch related parameters have been specified correctly\n //\n public static void awsBatch(workflow, params) {\n if (workflow.profile.contains('awsbatch')) {\n // Check params.awsqueue and params.awsregion have been set if running on AWSBatch\n assert (params.awsqueue && params.awsregion) : \"Specify correct --awsqueue and --awsregion parameters on AWSBatch!\"\n // Check outdir paths to be S3 buckets if running on AWSBatch\n assert params.outdir.startsWith('s3:') : \"Outdir not on S3 - specify S3 Bucket to run on AWSBatch!\"\n }\n }\n\n //\n // Warn if a -profile or Nextflow config has not been provided to run the pipeline\n //\n public static void checkConfigProvided(workflow, log) {\n if (workflow.profile == 'standard' && workflow.configFiles.size() <= 1) {\n log.warn \"[$workflow.manifest.name] You are attempting to run the pipeline without any custom configuration!\\n\\n\" +\n \"This will be dependent on your local compute environment but can be achieved via one or more of the following:\\n\" +\n \" (1) Using an existing pipeline profile e.g. `-profile docker` or `-profile singularity`\\n\" +\n \" (2) Using an existing nf-core/configs for your Institution e.g. `-profile crick` or `-profile uppmax`\\n\" +\n \" (3) Using your own local custom config e.g. `-c /path/to/your/custom.config`\\n\\n\" +\n \"Please refer to the quick start section and usage docs for the pipeline.\\n \"\n }\n }\n\n //\n // Generate version string\n //\n public static String version(workflow) {\n String version_string = \"\"\n\n if (workflow.manifest.version) {\n def prefix_v = workflow.manifest.version[0] != 'v' ? 'v' : ''\n version_string += \"${prefix_v}${workflow.manifest.version}\"\n }\n\n if (workflow.commitId) {\n def git_shortsha = workflow.commitId.substring(0, 7)\n version_string += \"-g${git_shortsha}\"\n }\n\n return version_string\n }\n\n //\n // Construct and send completion email\n //\n public static void email(workflow, params, summary_params, projectDir, log, multiqc_report=[]) {\n\n // Set up the e-mail variables\n def subject = \"[$workflow.manifest.name] Successful: $workflow.runName\"\n if (!workflow.success) {\n subject = \"[$workflow.manifest.name] FAILED: $workflow.runName\"\n }\n\n def summary = [:]\n for (group in summary_params.keySet()) {\n summary << summary_params[group]\n }\n\n def misc_fields = [:]\n misc_fields['Date Started'] = workflow.start\n misc_fields['Date Completed'] = workflow.complete\n misc_fields['Pipeline script file path'] = workflow.scriptFile\n misc_fields['Pipeline script hash ID'] = workflow.scriptId\n if (workflow.repository) misc_fields['Pipeline repository Git URL'] = workflow.repository\n if (workflow.commitId) misc_fields['Pipeline repository Git Commit'] = workflow.commitId\n if (workflow.revision) misc_fields['Pipeline Git branch/tag'] = workflow.revision\n misc_fields['Nextflow Version'] = workflow.nextflow.version\n misc_fields['Nextflow Build'] = workflow.nextflow.build\n misc_fields['Nextflow Compile Timestamp'] = workflow.nextflow.timestamp\n\n def email_fields = [:]\n email_fields['version'] = NfcoreTemplate.version(workflow)\n email_fields['runName'] = workflow.runName\n email_fields['success'] = workflow.success\n email_fields['dateComplete'] = workflow.complete\n email_fields['duration'] = workflow.duration\n email_fields['exitStatus'] = workflow.exitStatus\n email_fields['errorMessage'] = (workflow.errorMessage ?: 'None')\n email_fields['errorReport'] = (workflow.errorReport ?: 'None')\n email_fields['commandLine'] = workflow.commandLine\n email_fields['projectDir'] = workflow.projectDir\n email_fields['summary'] = summary << misc_fields\n\n // On success try attach the multiqc report\n def mqc_report = null\n try {\n if (workflow.success) {\n mqc_report = multiqc_report.getVal()\n if (mqc_report.getClass() == ArrayList && mqc_report.size() >= 1) {\n if (mqc_report.size() > 1) {\n log.warn \"[$workflow.manifest.name] Found multiple reports from process 'MULTIQC', will use only one\"\n }\n mqc_report = mqc_report[0]\n }\n }\n } catch (all) {\n if (multiqc_report) {\n log.warn \"[$workflow.manifest.name] Could not attach MultiQC report to summary email\"\n }\n }\n\n // Check if we are only sending emails on failure\n def email_address = params.email\n if (!params.email && params.email_on_fail && !workflow.success) {\n email_address = params.email_on_fail\n }\n\n // Render the TXT template\n def engine = new groovy.text.GStringTemplateEngine()\n def tf = new File(\"$projectDir/assets/email_template.txt\")\n def txt_template = engine.createTemplate(tf).make(email_fields)\n def email_txt = txt_template.toString()\n\n // Render the HTML template\n def hf = new File(\"$projectDir/assets/email_template.html\")\n def html_template = engine.createTemplate(hf).make(email_fields)\n def email_html = html_template.toString()\n\n // Render the sendmail template\n def max_multiqc_email_size = (params.containsKey('max_multiqc_email_size') ? params.max_multiqc_email_size : 0) as nextflow.util.MemoryUnit\n def smail_fields = [ email: email_address, subject: subject, email_txt: email_txt, email_html: email_html, projectDir: \"$projectDir\", mqcFile: mqc_report, mqcMaxSize: max_multiqc_email_size.toBytes() ]\n def sf = new File(\"$projectDir/assets/sendmail_template.txt\")\n def sendmail_template = engine.createTemplate(sf).make(smail_fields)\n def sendmail_html = sendmail_template.toString()\n\n // Send the HTML e-mail\n Map colors = logColours(params.monochrome_logs)\n if (email_address) {\n try {\n if (params.plaintext_email) { throw GroovyException('Send plaintext e-mail, not HTML') }\n // Try to send HTML e-mail using sendmail\n [ 'sendmail', '-t' ].execute() << sendmail_html\n log.info \"-${colors.purple}[$workflow.manifest.name]${colors.green} Sent summary e-mail to $email_address (sendmail)-\"\n } catch (all) {\n // Catch failures and try with plaintext\n def mail_cmd = [ 'mail', '-s', subject, '--content-type=text/html', email_address ]\n if ( mqc_report.size() <= max_multiqc_email_size.toBytes() ) {\n mail_cmd += [ '-A', mqc_report ]\n }\n mail_cmd.execute() << email_html\n log.info \"-${colors.purple}[$workflow.manifest.name]${colors.green} Sent summary e-mail to $email_address (mail)-\"\n }\n }\n\n // Write summary e-mail HTML to a file\n def output_d = new File(\"${params.outdir}/pipeline_info/\")\n if (!output_d.exists()) {\n output_d.mkdirs()\n }\n def output_hf = new File(output_d, \"pipeline_report.html\")\n output_hf.withWriter { w -> w << email_html }\n def output_tf = new File(output_d, \"pipeline_report.txt\")\n output_tf.withWriter { w -> w << email_txt }\n }\n\n //\n // Construct and send a notification to a web server as JSON\n // e.g. Microsoft Teams and Slack\n //\n public static void IM_notification(workflow, params, summary_params, projectDir, log) {\n def hook_url = params.hook_url\n\n def summary = [:]\n for (group in summary_params.keySet()) {\n summary << summary_params[group]\n }\n\n def misc_fields = [:]\n misc_fields['start'] = workflow.start\n misc_fields['complete'] = workflow.complete\n misc_fields['scriptfile'] = workflow.scriptFile\n misc_fields['scriptid'] = workflow.scriptId\n if (workflow.repository) misc_fields['repository'] = workflow.repository\n if (workflow.commitId) misc_fields['commitid'] = workflow.commitId\n if (workflow.revision) misc_fields['revision'] = workflow.revision\n misc_fields['nxf_version'] = workflow.nextflow.version\n misc_fields['nxf_build'] = workflow.nextflow.build\n misc_fields['nxf_timestamp'] = workflow.nextflow.timestamp\n\n def msg_fields = [:]\n msg_fields['version'] = NfcoreTemplate.version(workflow)\n msg_fields['runName'] = workflow.runName\n msg_fields['success'] = workflow.success\n msg_fields['dateComplete'] = workflow.complete\n msg_fields['duration'] = workflow.duration\n msg_fields['exitStatus'] = workflow.exitStatus\n msg_fields['errorMessage'] = (workflow.errorMessage ?: 'None')\n msg_fields['errorReport'] = (workflow.errorReport ?: 'None')\n msg_fields['commandLine'] = workflow.commandLine.replaceFirst(/ +--hook_url +[^ ]+/, \"\")\n msg_fields['projectDir'] = workflow.projectDir\n msg_fields['summary'] = summary << misc_fields\n\n // Render the JSON template\n def engine = new groovy.text.GStringTemplateEngine()\n // Different JSON depending on the service provider\n // Defaults to \"Adaptive Cards\" (https://adaptivecards.io), except Slack which has its own format\n def json_path = hook_url.contains(\"hooks.slack.com\") ? \"slackreport.json\" : \"adaptivecard.json\"\n def hf = new File(\"$projectDir/assets/${json_path}\")\n def json_template = engine.createTemplate(hf).make(msg_fields)\n def json_message = json_template.toString()\n\n // POST\n def post = new URL(hook_url).openConnection();\n post.setRequestMethod(\"POST\")\n post.setDoOutput(true)\n post.setRequestProperty(\"Content-Type\", \"application/json\")\n post.getOutputStream().write(json_message.getBytes(\"UTF-8\"));\n def postRC = post.getResponseCode();\n if (! postRC.equals(200)) {\n log.warn(post.getErrorStream().getText());\n }\n }\n\n //\n // Print pipeline summary on completion\n //\n public static void summary(workflow, params, log) {\n Map colors = logColours(params.monochrome_logs)\n if (workflow.success) {\n if (workflow.stats.ignoredCount == 0) {\n log.info \"-${colors.purple}[$workflow.manifest.name]${colors.green} Pipeline completed successfully${colors.reset}-\"\n } else {\n log.info \"-${colors.purple}[$workflow.manifest.name]${colors.yellow} Pipeline completed successfully, but with errored process(es) ${colors.reset}-\"\n }\n } else {\n log.info \"-${colors.purple}[$workflow.manifest.name]${colors.red} Pipeline completed with errors${colors.reset}-\"\n }\n }\n\n //\n // ANSII Colours used for terminal logging\n //\n public static Map logColours(Boolean monochrome_logs) {\n Map colorcodes = [:]\n\n // Reset / Meta\n colorcodes['reset'] = monochrome_logs ? '' : \"\\033[0m\"\n colorcodes['bold'] = monochrome_logs ? '' : \"\\033[1m\"\n colorcodes['dim'] = monochrome_logs ? '' : \"\\033[2m\"\n colorcodes['underlined'] = monochrome_logs ? '' : \"\\033[4m\"\n colorcodes['blink'] = monochrome_logs ? '' : \"\\033[5m\"\n colorcodes['reverse'] = monochrome_logs ? '' : \"\\033[7m\"\n colorcodes['hidden'] = monochrome_logs ? '' : \"\\033[8m\"\n\n // Regular Colors\n colorcodes['black'] = monochrome_logs ? '' : \"\\033[0;30m\"\n colorcodes['red'] = monochrome_logs ? '' : \"\\033[0;31m\"\n colorcodes['green'] = monochrome_logs ? '' : \"\\033[0;32m\"\n colorcodes['yellow'] = monochrome_logs ? '' : \"\\033[0;33m\"\n colorcodes['blue'] = monochrome_logs ? '' : \"\\033[0;34m\"\n colorcodes['purple'] = monochrome_logs ? '' : \"\\033[0;35m\"\n colorcodes['cyan'] = monochrome_logs ? '' : \"\\033[0;36m\"\n colorcodes['white'] = monochrome_logs ? '' : \"\\033[0;37m\"\n\n // Bold\n colorcodes['bblack'] = monochrome_logs ? '' : \"\\033[1;30m\"\n colorcodes['bred'] = monochrome_logs ? '' : \"\\033[1;31m\"\n colorcodes['bgreen'] = monochrome_logs ? '' : \"\\033[1;32m\"\n colorcodes['byellow'] = monochrome_logs ? '' : \"\\033[1;33m\"\n colorcodes['bblue'] = monochrome_logs ? '' : \"\\033[1;34m\"\n colorcodes['bpurple'] = monochrome_logs ? '' : \"\\033[1;35m\"\n colorcodes['bcyan'] = monochrome_logs ? '' : \"\\033[1;36m\"\n colorcodes['bwhite'] = monochrome_logs ? '' : \"\\033[1;37m\"\n\n // Underline\n colorcodes['ublack'] = monochrome_logs ? '' : \"\\033[4;30m\"\n colorcodes['ured'] = monochrome_logs ? '' : \"\\033[4;31m\"\n colorcodes['ugreen'] = monochrome_logs ? '' : \"\\033[4;32m\"\n colorcodes['uyellow'] = monochrome_logs ? '' : \"\\033[4;33m\"\n colorcodes['ublue'] = monochrome_logs ? '' : \"\\033[4;34m\"\n colorcodes['upurple'] = monochrome_logs ? '' : \"\\033[4;35m\"\n colorcodes['ucyan'] = monochrome_logs ? '' : \"\\033[4;36m\"\n colorcodes['uwhite'] = monochrome_logs ? '' : \"\\033[4;37m\"\n\n // High Intensity\n colorcodes['iblack'] = monochrome_logs ? '' : \"\\033[0;90m\"\n colorcodes['ired'] = monochrome_logs ? '' : \"\\033[0;91m\"\n colorcodes['igreen'] = monochrome_logs ? '' : \"\\033[0;92m\"\n colorcodes['iyellow'] = monochrome_logs ? '' : \"\\033[0;93m\"\n colorcodes['iblue'] = monochrome_logs ? '' : \"\\033[0;94m\"\n colorcodes['ipurple'] = monochrome_logs ? '' : \"\\033[0;95m\"\n colorcodes['icyan'] = monochrome_logs ? '' : \"\\033[0;96m\"\n colorcodes['iwhite'] = monochrome_logs ? '' : \"\\033[0;97m\"\n\n // Bold High Intensity\n colorcodes['biblack'] = monochrome_logs ? '' : \"\\033[1;90m\"\n colorcodes['bired'] = monochrome_logs ? '' : \"\\033[1;91m\"\n colorcodes['bigreen'] = monochrome_logs ? '' : \"\\033[1;92m\"\n colorcodes['biyellow'] = monochrome_logs ? '' : \"\\033[1;93m\"\n colorcodes['biblue'] = monochrome_logs ? '' : \"\\033[1;94m\"\n colorcodes['bipurple'] = monochrome_logs ? '' : \"\\033[1;95m\"\n colorcodes['bicyan'] = monochrome_logs ? '' : \"\\033[1;96m\"\n colorcodes['biwhite'] = monochrome_logs ? '' : \"\\033[1;97m\"\n\n return colorcodes\n }\n\n //\n // Does what is says on the tin\n //\n public static String dashedLine(monochrome_logs) {\n Map colors = logColours(monochrome_logs)\n return \"-${colors.dim}----------------------------------------------------${colors.reset}-\"\n }\n\n //\n // nf-core logo\n //\n public static String logo(workflow, monochrome_logs) {\n Map colors = logColours(monochrome_logs)\n String workflow_version = NfcoreTemplate.version(workflow)\n String.format(\n \"\"\"\\n\n ${dashedLine(monochrome_logs)}\n ${colors.green},--.${colors.black}/${colors.green},-.${colors.reset}\n ${colors.blue} ___ __ __ __ ___ ${colors.green}/,-._.--~\\'${colors.reset}\n ${colors.blue} |\\\\ | |__ __ / ` / \\\\ |__) |__ ${colors.yellow}} {${colors.reset}\n ${colors.blue} | \\\\| | \\\\__, \\\\__/ | \\\\ |___ ${colors.green}\\\\`-._,-`-,${colors.reset}\n ${colors.green}`._,._,\\'${colors.reset}\n ${colors.purple} ${workflow.manifest.name} ${workflow_version}${colors.reset}\n ${dashedLine(monochrome_logs)}\n \"\"\".stripIndent()\n )\n }\n}\n" }, { "path": "lib/Utils.groovy", "content": "//\n// This file holds several Groovy functions that could be useful for any Nextflow pipeline\n//\n\nimport org.yaml.snakeyaml.Yaml\n\nclass Utils {\n\n //\n // When running with -profile conda, warn if channels have not been set-up appropriately\n //\n public static void checkCondaChannels(log) {\n Yaml parser = new Yaml()\n def channels = []\n try {\n def config = parser.load(\"conda config --show channels\".execute().text)\n channels = config.channels\n } catch(NullPointerException | IOException e) {\n log.warn \"Could not verify conda channel configuration.\"\n return\n }\n\n // Check that all channels are present\n // This channel list is ordered by required channel priority.\n def required_channels_in_order = ['conda-forge', 'bioconda', 'defaults']\n def channels_missing = ((required_channels_in_order as Set) - (channels as Set)) as Boolean\n\n // Check that they are in the right order\n def channel_priority_violation = false\n def n = required_channels_in_order.size()\n for (int i = 0; i < n - 1; i++) {\n channel_priority_violation |= !(channels.indexOf(required_channels_in_order[i]) < channels.indexOf(required_channels_in_order[i+1]))\n }\n\n if (channels_missing | channel_priority_violation) {\n log.warn \"~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n\" +\n \" There is a problem with your Conda configuration!\\n\\n\" +\n \" You will need to set-up the conda-forge and bioconda channels correctly.\\n\" +\n \" Please refer to https://bioconda.github.io/\\n\" +\n \" The observed channel order is \\n\" +\n \" ${channels}\\n\" +\n \" but the following channel order is required:\\n\" +\n \" ${required_channels_in_order}\\n\" +\n \"~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\"\n }\n }\n}\n" }, { "path": "lib/WorkflowAtacseq.groovy", "content": "//\n// This file holds several functions specific to the workflow/atacseq.nf in the nf-core/atacseq pipeline\n//\n\nimport nextflow.Nextflow\nimport groovy.text.SimpleTemplateEngine\n\nclass WorkflowAtacseq {\n\n //\n // Check and validate parameters\n //\n public static void initialise(params, log) {\n genomeExistsError(params, log)\n\n if (!params.fasta) {\n Nextflow.error \"Genome fasta file not specified with e.g. '--fasta genome.fa' or via a detectable config file.\"\n }\n\n if (!params.gtf && !params.gff) {\n log.error \"No GTF or GFF3 annotation specified! The pipeline requires at least one of these files.\"\n System.exit(1)\n }\n\n if (params.gtf && params.gff) {\n gtfGffWarn(log)\n }\n\n if (!params.macs_gsize) {\n macsGsizeWarn(log)\n }\n\n if (!params.read_length && !params.macs_gsize) {\n log.error \"Both '--read_length' and '--macs_gsize' not specified! Please specify either to infer MACS2 genome size for peak calling.\"\n System.exit(1)\n }\n }\n\n //\n // Get workflow summary for MultiQC\n //\n public static String paramsSummaryMultiqc(workflow, summary) {\n String summary_section = ''\n for (group in summary.keySet()) {\n def group_params = summary.get(group) // This gets the parameters of that particular group\n if (group_params) {\n summary_section += \"

$group

\\n\"\n summary_section += \"
\\n\"\n for (param in group_params.keySet()) {\n summary_section += \"
$param
${group_params.get(param) ?: 'N/A'}
\\n\"\n }\n summary_section += \"
\\n\"\n }\n }\n\n String yaml_file_text = \"id: '${workflow.manifest.name.replace('/','-')}-summary'\\n\"\n yaml_file_text += \"description: ' - this information is collected when the pipeline is started.'\\n\"\n yaml_file_text += \"section_name: '${workflow.manifest.name} Workflow Summary'\\n\"\n yaml_file_text += \"section_href: 'https://github.com/${workflow.manifest.name}'\\n\"\n yaml_file_text += \"plot_type: 'html'\\n\"\n yaml_file_text += \"data: |\\n\"\n yaml_file_text += \"${summary_section}\"\n return yaml_file_text\n }\n\n //\n // Generate methods description for MultiQC\n //\n\n public static String toolCitationText(params) {\n\n // TODO Optionally add in-text citation tools to this list.\n // Can use ternary operators to dynamically construct based conditions, e.g. params[\"run_xyz\"] ? \"Tool (Foo et al. 2023)\" : \"\",\n // Uncomment function in methodsDescriptionText to render in MultiQC report\n def citation_text = [\n \"Tools used in the workflow included:\",\n \"FastQC (Andrews 2010),\",\n \"MultiQC (Ewels et al. 2016)\",\n \".\"\n ].join(' ').trim()\n\n return citation_text\n }\n\n public static String toolBibliographyText(params) {\n\n // TODO Optionally add bibliographic entries to this list.\n // Can use ternary operators to dynamically construct based conditions, e.g. params[\"run_xyz\"] ? \"
  • Author (2023) Pub name, Journal, DOI
    • \" : \"\",\n // Uncomment function in methodsDescriptionText to render in MultiQC report\n def reference_text = [\n \"
  • Andrews S, (2010) FastQC, URL: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
    • \",\n \"
  • Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics , 32(19), 3047–3048. doi: /10.1093/bioinformatics/btw354
    • \"\n ].join(' ').trim()\n\n return reference_text\n }\n\n public static String methodsDescriptionText(run_workflow, mqc_methods_yaml, params) {\n // Convert to a named map so can be used as with familar NXF ${workflow} variable syntax in the MultiQC YML file\n def meta = [:]\n meta.workflow = run_workflow.toMap()\n meta[\"manifest_map\"] = run_workflow.manifest.toMap()\n\n // Pipeline DOI\n meta[\"doi_text\"] = meta.manifest_map.doi ? \"(doi: ${meta.manifest_map.doi})\" : \"\"\n meta[\"nodoi_text\"] = meta.manifest_map.doi ? \"\": \"
  • If available, make sure to update the text to include the Zenodo DOI of version of the pipeline used.
    • \"\n\n // Tool references\n meta[\"tool_citations\"] = \"\"\n meta[\"tool_bibliography\"] = \"\"\n\n // TODO Only uncomment below if logic in toolCitationText/toolBibliographyText has been filled!\n //meta[\"tool_citations\"] = toolCitationText(params).replaceAll(\", \\\\.\", \".\").replaceAll(\"\\\\. \\\\.\", \".\").replaceAll(\", \\\\.\", \".\")\n //meta[\"tool_bibliography\"] = toolBibliographyText(params)\n\n\n def methods_text = mqc_methods_yaml.text\n\n def engine = new SimpleTemplateEngine()\n def description_html = engine.createTemplate(methods_text).make(meta)\n\n return description_html\n }\n\n //\n // Exit pipeline if incorrect --genome key provided\n //\n private static void genomeExistsError(params, log) {\n if (params.genomes && params.genome && !params.genomes.containsKey(params.genome)) {\n def error_string = \"~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n\" +\n \" Genome '${params.genome}' not found in any config files provided to the pipeline.\\n\" +\n \" Currently, the available genome keys are:\\n\" +\n \" ${params.genomes.keySet().join(\", \")}\\n\" +\n \"~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\"\n Nextflow.error(error_string)\n }\n }\n\n //\n // Print a warning if both GTF and GFF have been provided\n //\n private static void gtfGffWarn(log) {\n log.warn \"=============================================================================\\n\" +\n \" Both '--gtf' and '--gff' parameters have been provided.\\n\" +\n \" Using GTF file as priority.\\n\" +\n \"===================================================================================\"\n }\n\n //\n // Print a warning if macs_gsize parameter has not been provided\n //\n private static void macsGsizeWarn(log) {\n log.warn \"=============================================================================\\n\" +\n \" --macs_gsize parameter has not been provided.\\n\" +\n \" It will be auto-calculated by 'khmer unique-kmers.py' using the '--read_length' parameter.\\n\" +\n \" Explicitly provide '--macs_gsize macs2_genome_size' to change this behaviour.\\n\" +\n \"===================================================================================\"\n }\n\n}\n" }, { "path": "lib/WorkflowMain.groovy", "content": "//\n// This file holds several functions specific to the main.nf workflow in the nf-core/atacseq pipeline\n//\n\nimport nextflow.Nextflow\n\nclass WorkflowMain {\n\n //\n // Citation string for pipeline\n //\n public static String citation(workflow) {\n return \"If you use ${workflow.manifest.name} for your analysis please cite:\\n\\n\" +\n \"* The pipeline\\n\" +\n \" https://doi.org/10.5281/zenodo.2634132\\n\\n\" +\n \"* The nf-core framework\\n\" +\n \" https://doi.org/10.1038/s41587-020-0439-x\\n\\n\" +\n \"* Software dependencies\\n\" +\n \" https://github.com/${workflow.manifest.name}/blob/master/CITATIONS.md\"\n }\n\n //\n // Validate parameters and print summary to screen\n //\n public static void initialise(workflow, params, log) {\n\n // Print workflow version and exit on --version\n if (params.version) {\n String workflow_version = NfcoreTemplate.version(workflow)\n log.info \"${workflow.manifest.name} ${workflow_version}\"\n System.exit(0)\n }\n\n // Check that a -profile or Nextflow config has been provided to run the pipeline\n NfcoreTemplate.checkConfigProvided(workflow, log)\n\n // Check that conda channels are set-up correctly\n if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) {\n Utils.checkCondaChannels(log)\n }\n\n // Check AWS batch settings\n NfcoreTemplate.awsBatch(workflow, params)\n }\n\n //\n // Get attribute from genome config file e.g. fasta\n //\n public static Object getGenomeAttribute(params, attribute) {\n if (params.genomes && params.genome && params.genomes.containsKey(params.genome)) {\n if (params.genomes[ params.genome ].containsKey(attribute)) {\n return params.genomes[ params.genome ][ attribute ]\n }\n }\n return null\n }\n\n //\n // Get macs genome size (macs_gsize)\n //\n public static Long getMacsGsize(params) {\n def val = null\n if (params.genomes && params.genome && params.genomes.containsKey(params.genome)) {\n if (params.genomes[ params.genome ].containsKey('macs_gsize')) {\n if (params.genomes[ params.genome ][ 'macs_gsize' ].containsKey(params.read_length.toString())) {\n val = params.genomes[ params.genome ][ 'macs_gsize' ][ params.read_length.toString() ]\n }\n }\n }\n return val\n }\n}\n" }, { "path": "main.nf", "content": "#!/usr/bin/env nextflow\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n nf-core/atacseq\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Github : https://github.com/nf-core/atacseq\n Website: https://nf-co.re/atacseq\n Slack : https://nfcore.slack.com/channels/atacseq\n----------------------------------------------------------------------------------------\n*/\n\nnextflow.enable.dsl = 2\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n GENOME PARAMETER VALUES\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\nparams.fasta = WorkflowMain.getGenomeAttribute(params, 'fasta')\nparams.bwa_index = WorkflowMain.getGenomeAttribute(params, 'bwa')\nparams.bowtie2_index = WorkflowMain.getGenomeAttribute(params, 'bowtie2')\nparams.chromap_index = WorkflowMain.getGenomeAttribute(params, 'chromap')\nparams.star_index = WorkflowMain.getGenomeAttribute(params, 'star')\nparams.gtf = WorkflowMain.getGenomeAttribute(params, 'gtf')\nparams.gff = WorkflowMain.getGenomeAttribute(params, 'gff')\nparams.gene_bed = WorkflowMain.getGenomeAttribute(params, 'gene_bed')\nparams.tss_bed = WorkflowMain.getGenomeAttribute(params, 'tss_bed')\nparams.blacklist = WorkflowMain.getGenomeAttribute(params, 'blacklist')\nparams.mito_name = WorkflowMain.getGenomeAttribute(params, 'mito_name')\nparams.macs_gsize = WorkflowMain.getMacsGsize(params)\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n VALIDATE & PRINT PARAMETER SUMMARY\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\ninclude { validateParameters; paramsHelp } from 'plugin/nf-validation'\n\n// Print help message if needed\nif (params.help) {\n def logo = NfcoreTemplate.logo(workflow, params.monochrome_logs)\n def citation = '\\n' + WorkflowMain.citation(workflow) + '\\n'\n def String command = \"nextflow run ${workflow.manifest.name} --input samplesheet.csv --genome GRCh37 -profile docker\"\n log.info logo + paramsHelp(command) + citation + NfcoreTemplate.dashedLine(params.monochrome_logs)\n System.exit(0)\n}\n\n// Validate input parameters\nif (params.validate_params) {\n validateParameters()\n}\n\nWorkflowMain.initialise(workflow, params, log)\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n NAMED WORKFLOW FOR PIPELINE\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\ninclude { ATACSEQ } from './workflows/atacseq'\n\n//\n// WORKFLOW: Run main nf-core/atacseq analysis pipeline\n//\nworkflow NFCORE_ATACSEQ {\n ATACSEQ ()\n}\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n RUN ALL WORKFLOWS\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\n//\n// WORKFLOW: Execute a single named workflow for the pipeline\n// See: https://github.com/nf-core/rnaseq/issues/619\n//\nworkflow {\n NFCORE_ATACSEQ ()\n}\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n THE END\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n" }, { "path": "modules/local/bam_remove_orphans.nf", "content": "process BAM_REMOVE_ORPHANS {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::pysam=0.19.0 bioconda::samtools=1.15.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-57736af1eb98c01010848572c9fec9fff6ffaafd:402e865b8f6af2f3e58c6fc8d57127ff0144b2c7-0' :\n 'biocontainers/mulled-v2-57736af1eb98c01010848572c9fec9fff6ffaafd:402e865b8f6af2f3e58c6fc8d57127ff0144b2c7-0' }\"\n\n input:\n tuple val(meta), path(bam)\n\n output:\n tuple val(meta), path(\"*.bam\"), emit: bam\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script: // This script is bundled with the pipeline, in nf-core/atacseq/bin/\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n if (!meta.single_end) {\n \"\"\"\n bampe_rm_orphan.py \\\\\n $bam \\\\\n ${prefix}.bam \\\\\n $args\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n } else {\n \"\"\"\n ln -s $bam ${prefix}.bam\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n }\n}\n" }, { "path": "modules/local/bamtools_filter.nf", "content": "process BAMTOOLS_FILTER {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::bamtools=2.5.2 bioconda::samtools=1.15.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-0560a8046fc82aa4338588eca29ff18edab2c5aa:5687a7da26983502d0a8a9a6b05ed727c740ddc4-0' :\n 'biocontainers/mulled-v2-0560a8046fc82aa4338588eca29ff18edab2c5aa:5687a7da26983502d0a8a9a6b05ed727c740ddc4-0' }\"\n\n input:\n tuple val(meta), path(bam), path(bai)\n path bed\n path bamtools_filter_se_config\n path bamtools_filter_pe_config\n\n output:\n tuple val(meta), path(\"*.bam\"), emit: bam\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def blacklist = bed ? \"-L $bed\" : ''\n def config = meta.single_end ? bamtools_filter_se_config : bamtools_filter_pe_config\n \"\"\"\n samtools view \\\\\n $args \\\\\n $blacklist \\\\\n -b $bam \\\\\n | bamtools filter \\\\\n -out ${prefix}.bam \\\\\n -script $config\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n bamtools: \\$(echo \\$(bamtools --version 2>&1) | sed 's/^.*bamtools //; s/Part .*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/bedtools_genomecov.nf", "content": "process BEDTOOLS_GENOMECOV {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::bedtools=2.30.0\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/bedtools:2.30.0--hc088bd4_0':\n 'biocontainers/bedtools:2.30.0--hc088bd4_0' }\"\n\n input:\n tuple val(meta), path(bam), path(flagstat)\n\n output:\n tuple val(meta), path(\"*.bedGraph\"), emit: bedgraph\n tuple val(meta), path(\"*.txt\") , emit: scale_factor\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def pe = meta.single_end ? '' : '-pc'\n \"\"\"\n SCALE_FACTOR=\\$(grep '[0-9] mapped (' $flagstat | awk '{print 1000000/\\$1}')\n echo \\$SCALE_FACTOR > ${prefix}.scale_factor.txt\n\n bedtools \\\\\n genomecov \\\\\n -ibam $bam \\\\\n -bg \\\\\n -scale \\$SCALE_FACTOR \\\\\n $pe \\\\\n $args \\\\\n > tmp.bg\n\n bedtools sort -i tmp.bg > ${prefix}.bedGraph\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bedtools: \\$(bedtools --version | sed -e \"s/bedtools v//g\")\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/deseq2_qc.nf", "content": "process DESEQ2_QC {\n tag \"$meta.id\"\n label 'process_medium'\n\n // (Bio)conda packages have intentionally not been pinned to a specific version\n // This was to avoid the pipeline failing due to package conflicts whilst creating the environment when using -profile conda\n conda \"conda-forge::r-base bioconda::bioconductor-deseq2 bioconda::bioconductor-biocparallel bioconda::bioconductor-tximport bioconda::bioconductor-complexheatmap conda-forge::r-optparse conda-forge::r-ggplot2 conda-forge::r-rcolorbrewer conda-forge::r-pheatmap\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-8849acf39a43cdd6c839a369a74c0adc823e2f91:ab110436faf952a33575c64dd74615a84011450b-0' :\n 'biocontainers/mulled-v2-8849acf39a43cdd6c839a369a74c0adc823e2f91:ab110436faf952a33575c64dd74615a84011450b-0' }\"\n\n input:\n tuple val(meta), path(counts)\n path deseq2_pca_header\n path deseq2_clustering_header\n\n output:\n path \"*.pdf\" , optional:true, emit: pdf\n path \"*.RData\" , optional:true, emit: rdata\n path \"*.rds\" , optional:true, emit: rds\n path \"*pca.vals.txt\" , optional:true, emit: pca_txt\n path \"*pca.vals_mqc.tsv\" , optional:true, emit: pca_multiqc\n path \"*sample.dists.txt\" , optional:true, emit: dists_txt\n path \"*sample.dists_mqc.tsv\", optional:true, emit: dists_multiqc\n path \"*.log\" , optional:true, emit: log\n path \"size_factors\" , optional:true, emit: size_factors\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n deseq2_qc.r \\\\\n --count_file $counts \\\\\n --outdir ./ \\\\\n --outprefix $prefix \\\\\n --cores $task.cpus \\\\\n $args\n\n sed 's/deseq2_pca/deseq2_pca_${task.index}/g' <$deseq2_pca_header >tmp.txt\n sed -i -e 's/DESeq2 /${meta.id} DESeq2 /g' tmp.txt\n cat tmp.txt ${prefix}.pca.vals.txt > ${prefix}.pca.vals_mqc.tsv\n\n sed 's/deseq2_clustering/deseq2_clustering_${task.index}/g' <$deseq2_clustering_header >tmp.txt\n sed -i -e 's/DESeq2 /${meta.id} DESeq2 /g' tmp.txt\n cat tmp.txt ${prefix}.sample.dists.txt > ${prefix}.sample.dists_mqc.tsv\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n r-base: \\$(echo \\$(R --version 2>&1) | sed 's/^.*R version //; s/ .*\\$//')\n bioconductor-deseq2: \\$(Rscript -e \"library(DESeq2); cat(as.character(packageVersion('DESeq2')))\")\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/frip_score.nf", "content": "process FRIP_SCORE {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::bedtools=2.30.0 bioconda::samtools=1.15.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-8186960447c5cb2faa697666dc1e6d919ad23f3e:3127fcae6b6bdaf8181e21a26ae61231030a9fcb-0':\n 'biocontainers/mulled-v2-8186960447c5cb2faa697666dc1e6d919ad23f3e:3127fcae6b6bdaf8181e21a26ae61231030a9fcb-0' }\"\n\n input:\n tuple val(meta), path(bam), path(peak)\n\n output:\n tuple val(meta), path(\"*.txt\"), emit: txt\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n READS_IN_PEAKS=\\$(intersectBed -a $bam -b $peak $args | awk -F '\\t' '{sum += \\$NF} END {print sum}')\n samtools flagstat $bam > ${bam}.flagstat\n grep 'mapped (' ${bam}.flagstat | grep -v \"primary\" | awk -v a=\"\\$READS_IN_PEAKS\" -v OFS='\\t' '{print \"${prefix}\", a/\\$1}' > ${prefix}.FRiP.txt\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bedtools: \\$(bedtools --version | sed -e \"s/bedtools v//g\")\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/genome_blacklist_regions.nf", "content": "process GENOME_BLACKLIST_REGIONS {\n tag \"$sizes\"\n\n conda \"bioconda::bedtools=2.30.0\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/bedtools:2.30.0--hc088bd4_0':\n 'biocontainers/bedtools:2.30.0--hc088bd4_0' }\"\n\n input:\n path sizes\n path blacklist\n val mito_name\n val keep_mito\n\n output:\n path '*.bed' , emit: bed\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def file_out = \"${sizes.simpleName}.include_regions.bed\"\n def name_filter = mito_name ? \"| awk '\\$1 !~ /${params.mito_name}/ {print \\$0}'\": ''\n def mito_filter = keep_mito ? '' : name_filter\n if (blacklist) {\n \"\"\"\n sortBed -i $blacklist -g $sizes | complementBed -i stdin -g $sizes $mito_filter > $file_out\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bedtools: \\$(bedtools --version | sed -e \"s/bedtools v//g\")\n END_VERSIONS\n \"\"\"\n } else {\n \"\"\"\n awk '{print \\$1, '0' , \\$2}' OFS='\\t' $sizes $mito_filter > $file_out\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bedtools: \\$(bedtools --version | sed -e \"s/bedtools v//g\")\n END_VERSIONS\n \"\"\"\n }\n}\n" }, { "path": "modules/local/get_autosomes.nf", "content": "process GET_AUTOSOMES {\n tag \"$fai\"\n\n conda \"conda-forge::python=3.8.3\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/python:3.8.3' :\n 'biocontainers/python:3.8.3' }\"\n\n input:\n path fai\n\n output:\n path '*.txt' , emit: txt\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script: // This script is bundled with the pipeline, in nf-core/atacseq/bin/\n \"\"\"\n get_autosomes.py \\\\\n $fai \\\\\n ${fai.baseName}.autosomes.txt\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n python: \\$(python --version | sed 's/Python //g')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/gtf2bed.nf", "content": "process GTF2BED {\n tag \"$gtf\"\n label 'process_low'\n\n conda \"conda-forge::perl=5.26.2\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/perl:5.26.2':\n 'biocontainers/perl:5.26.2' }\"\n\n input:\n path gtf\n\n output:\n path '*.bed' , emit: bed\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script: // This script is bundled with the pipeline, in nf-core/atacseq/bin/\n \"\"\"\n gtf2bed \\\\\n $gtf \\\\\n > ${gtf.baseName}.bed\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n perl: \\$(echo \\$(perl --version 2>&1) | sed 's/.*v\\\\(.*\\\\)) built.*/\\\\1/')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/igv.nf", "content": "process IGV {\n\n conda \"conda-forge::python=3.8.3\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/python:3.8.3':\n 'biocontainers/python:3.8.3' }\"\n\n input:\n path fasta\n path fai\n path (\"${bigwig_library_publish_dir}/*\")\n path (\"${peak_library_publish_dir}/*\")\n path (\"${consensus_library_publish_dir}/*\")\n path (\"${bigwig_replicate_publish_dir}/*\")\n path (\"${peak_replicate_publish_dir}/*\")\n path (\"${consensus_replicate_publish_dir}/*\")\n val bigwig_library_publish_dir\n val peak_library_publish_dir\n val consensus_library_publish_dir\n val bigwig_replicate_publish_dir\n val peak_replicate_publish_dir\n val consensus_replicate_publish_dir\n\n output:\n // Publish fasta file while copyTo fails when the source and destination buckets are in different regions\n path \"*files.txt\" , emit: txt\n path \"*.xml\" , emit: xml\n path fasta , emit: fasta\n path fai , emit: fai\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script: // scripts are bundled with the pipeline in nf-core/atacseq/bin/\n \"\"\"\n find * -type l -name \"*.bigWig\" -exec echo -e \"\"{}\"\\\\t0,0,178\" \\\\; | { grep \"^$bigwig_library_publish_dir\" || test \\$? = 1; } > mLb_bigwig.igv.txt\n find * -type l -name \"*Peak\" -exec echo -e \"\"{}\"\\\\t0,0,178\" \\\\; | { grep \"^$peak_library_publish_dir\" || test \\$? = 1; } > mLb_peaks.igv.txt\n find * -type l -name \"*.bed\" -exec echo -e \"\"{}\"\\\\t0,0,0\" \\\\; | { grep \"^$consensus_library_publish_dir\" || test \\$? = 1; } > mLb_bed.igv.txt\n find * -type l -name \"*.bigWig\" -exec echo -e \"\"{}\"\\\\t0,0,178\" \\\\; | { grep \"^$bigwig_replicate_publish_dir\" || test \\$? = 1; } > mRp_bigwig.igv.txt\n find * -type l -name \"*Peak\" -exec echo -e \"\"{}\"\\\\t0,0,178\" \\\\; | { grep \"^$peak_replicate_publish_dir\" || test \\$? = 1; } > mRp_peaks.igv.txt\n find * -type l -name \"*.bed\" -exec echo -e \"\"{}\"\\\\t0,0,0\" \\\\; | { grep \"^$consensus_replicate_publish_dir\" || test \\$? = 1; } > mRp_bed.igv.txt\n\n cat *.txt > igv_files.txt\n igv_files_to_session.py igv_session.xml igv_files.txt ../../genome/${fasta.getName()} --path_prefix '../../'\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n python: \\$(python --version | sed 's/Python //g')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/macs2_consensus.nf", "content": "process MACS2_CONSENSUS {\n tag \"$meta.id\"\n label 'process_long'\n\n conda \"conda-forge::biopython conda-forge::r-optparse=1.7.1 conda-forge::r-upsetr=1.4.0 bioconda::bedtools=2.30.0\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-2f48cc59b03027e31ead6d383fe1b8057785dd24:5d182f583f4696f4c4d9f3be93052811b383341f-0':\n 'biocontainers/mulled-v2-2f48cc59b03027e31ead6d383fe1b8057785dd24:5d182f583f4696f4c4d9f3be93052811b383341f-0' }\"\n\n input:\n tuple val(meta), path(peaks)\n val is_narrow_peak\n\n output:\n tuple val(meta), path(\"*.bed\") , emit: bed\n tuple val(meta), path(\"*.saf\") , emit: saf\n tuple val(meta), path(\"*.pdf\") , emit: pdf\n tuple val(meta), path(\"*.boolean.txt\") , emit: boolean_txt\n tuple val(meta), path(\"*.intersect.txt\"), emit: intersect_txt\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script: // This script is bundled with the pipeline, in nf-core/atacseq/bin/\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def peak_type = is_narrow_peak ? 'narrowPeak' : 'broadPeak'\n def mergecols = is_narrow_peak ? (2..10).join(',') : (2..9).join(',')\n def collapsecols = is_narrow_peak ? (['collapse']*9).join(',') : (['collapse']*8).join(',')\n def expandparam = is_narrow_peak ? '--is_narrow_peak' : ''\n \"\"\"\n sort -T '.' -k1,1 -k2,2n ${peaks.collect{it.toString()}.sort().join(' ')} \\\\\n | mergeBed -c $mergecols -o $collapsecols > ${prefix}.txt\n\n macs2_merged_expand.py \\\\\n ${prefix}.txt \\\\\n ${peaks.collect{it.toString()}.sort().join(',').replaceAll(\"_peaks.${peak_type}\",\"\")} \\\\\n ${prefix}.boolean.txt \\\\\n $args \\\\\n $expandparam\n\n awk -v FS='\\t' -v OFS='\\t' 'FNR > 1 { print \\$1, \\$2, \\$3, \\$4, \"0\", \"+\" }' ${prefix}.boolean.txt > ${prefix}.bed\n\n echo -e \"GeneID\\tChr\\tStart\\tEnd\\tStrand\" > ${prefix}.saf\n awk -v FS='\\t' -v OFS='\\t' 'FNR > 1 { print \\$4, \\$1, \\$2, \\$3, \"+\" }' ${prefix}.boolean.txt >> ${prefix}.saf\n\n plot_peak_intersect.r -i ${prefix}.boolean.intersect.txt -o ${prefix}.boolean.intersect.plot.pdf\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n python: \\$(python --version | sed 's/Python //g')\n r-base: \\$(echo \\$(R --version 2>&1) | sed 's/^.*R version //; s/ .*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/multiqc.nf", "content": "process MULTIQC {\n label 'process_medium'\n\n conda 'bioconda::multiqc=1.13'\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/multiqc:1.13--pyhdfd78af_0' :\n 'biocontainers/multiqc:1.13--pyhdfd78af_0' }\"\n\n input:\n path multiqc_config\n path multiqc_custom_config\n path software_versions\n path workflow_summary\n\n path ('fastqc/*')\n path ('trimgalore/fastqc/*')\n path ('trimgalore/*')\n\n path ('alignment/library/*')\n path ('alignment/library/*')\n path ('alignment/library/*')\n\n path ('alignment/merged_library/unfiltered/*')\n path ('alignment/merged_library/unfiltered/*')\n path ('alignment/merged_library/unfiltered/*')\n path ('alignment/merged_library/unfiltered/picard_metrics/*')\n\n path ('alignment/merged_library/filtered/*')\n path ('alignment/merged_library/filtered/*')\n path ('alignment/merged_library/filtered/*')\n path ('alignment/merged_library/filtered/picard_metrics/*')\n\n path ('preseq/*')\n\n path ('deeptools/*')\n path ('deeptools/*')\n\n path ('macs2/merged_library/peaks/*')\n path ('macs2/merged_library/peaks/*')\n path ('macs2/merged_library/annotation/*')\n path ('macs2/merged_library/featurecounts/*')\n\n path ('alignment/merged_replicate/*')\n path ('alignment/merged_replicate/*')\n path ('alignment/merged_replicate/*')\n path ('alignment/merged_replicate/picard_metrics/*')\n\n path ('macs2/merged_replicate/peaks/*')\n path ('macs2/merged_replicate/peaks/*')\n path ('macs2/merged_replicate/annotation/*')\n path ('macs2/merged_replicate/featurecounts/*')\n\n path ('deseq2_library/*')\n path ('deseq2_library/*')\n path ('deseq2_replicate/*')\n path ('deseq2_replicate/*')\n\n output:\n path \"*multiqc_report.html\", emit: report\n path \"*_data\" , emit: data\n path \"*_plots\" , optional:true, emit: plots\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def custom_config = params.multiqc_config ? \"--config $multiqc_custom_config\" : ''\n \"\"\"\n multiqc \\\\\n -f \\\\\n $args \\\\\n $custom_config \\\\\n .\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n multiqc: \\$( multiqc --version | sed -e \"s/multiqc, version //g\" )\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/multiqc_custom_peaks.nf", "content": "process MULTIQC_CUSTOM_PEAKS {\n tag \"$meta.id\"\n\n conda \"conda-forge::sed=4.7\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/ubuntu:20.04' :\n 'nf-core/ubuntu:20.04' }\"\n\n input:\n tuple val(meta), path(peak), path(frip)\n path peak_count_header\n path frip_score_header\n\n output:\n tuple val(meta), path(\"*.count_mqc.tsv\"), emit: count\n tuple val(meta), path(\"*.FRiP_mqc.tsv\") , emit: frip\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n cat $peak | wc -l | awk -v OFS='\\t' '{ print \"${prefix}\", \\$1 }' | cat $peak_count_header - > ${prefix}.count_mqc.tsv\n cat $frip_score_header $frip > ${prefix}.FRiP_mqc.tsv\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n sed: \\$(echo \\$(sed --version 2>&1) | sed 's/^.*GNU sed) //; s/ .*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/plot_homer_annotatepeaks.nf", "content": "process PLOT_HOMER_ANNOTATEPEAKS {\n label 'process_medium'\n\n conda \"conda-forge::r-base=4.0.3 conda-forge::r-reshape2=1.4.4 conda-forge::r-optparse=1.6.6 conda-forge::r-ggplot2=3.3.3 conda-forge::r-scales=1.1.1 conda-forge::r-viridis=0.5.1 conda-forge::r-tidyverse=1.3.0 bioconda::bioconductor-biostrings=2.58.0 bioconda::bioconductor-complexheatmap=2.6.2\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-ad9dd5f398966bf899ae05f8e7c54d0fb10cdfa7:05678da05b8e5a7a5130e90a9f9a6c585b965afa-0':\n 'biocontainers/mulled-v2-ad9dd5f398966bf899ae05f8e7c54d0fb10cdfa7:05678da05b8e5a7a5130e90a9f9a6c585b965afa-0' }\"\n\n input:\n path annos\n path mqc_header\n val suffix\n\n output:\n path '*.txt' , emit: txt\n path '*.pdf' , emit: pdf\n path '*.tsv' , emit: tsv\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script: // This script is bundled with the pipeline, in nf-core/chipseq/bin/\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"annotatepeaks\"\n \"\"\"\n plot_homer_annotatepeaks.r \\\\\n -i ${annos.join(',')} \\\\\n -s ${annos.join(',').replaceAll(\"${suffix}\",\"\")} \\\\\n -p $prefix \\\\\n $args\n\n find ./ -type f -name \"*summary.txt\" -exec cat {} \\\\; | cat $mqc_header - > ${prefix}.summary_mqc.tsv\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n r-base: \\$(echo \\$(R --version 2>&1) | sed 's/^.*R version //; s/ .*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/plot_macs2_qc.nf", "content": "process PLOT_MACS2_QC {\n label 'process_medium'\n\n conda \"conda-forge::r-base=4.0.3 conda-forge::r-reshape2=1.4.4 conda-forge::r-optparse=1.6.6 conda-forge::r-ggplot2=3.3.3 conda-forge::r-scales=1.1.1 conda-forge::r-viridis=0.5.1 conda-forge::r-tidyverse=1.3.0 bioconda::bioconductor-biostrings=2.58.0 bioconda::bioconductor-complexheatmap=2.6.2\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-ad9dd5f398966bf899ae05f8e7c54d0fb10cdfa7:05678da05b8e5a7a5130e90a9f9a6c585b965afa-0':\n 'biocontainers/mulled-v2-ad9dd5f398966bf899ae05f8e7c54d0fb10cdfa7:05678da05b8e5a7a5130e90a9f9a6c585b965afa-0' }\"\n\n input:\n path peaks\n val is_narrow_peak\n\n output:\n path '*.txt' , emit: txt\n path '*.pdf' , emit: pdf\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script: // This script is bundled with the pipeline, in nf-core/atacseq/bin/\n def args = task.ext.args ?: ''\n def peak_type = is_narrow_peak ? 'narrowPeak' : 'broadPeak'\n \"\"\"\n plot_macs2_qc.r \\\\\n -i ${peaks.join(',')} \\\\\n -s ${peaks.join(',').replaceAll(\"_peaks.${peak_type}\",\"\")} \\\\\n $args\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n r-base: \\$(echo \\$(R --version 2>&1) | sed 's/^.*R version //; s/ .*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/samplesheet_check.nf", "content": "process SAMPLESHEET_CHECK {\n tag \"$samplesheet\"\n label 'process_single'\n\n conda \"conda-forge::python=3.8.3\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/python:3.8.3' :\n 'biocontainers/python:3.8.3' }\"\n\n input:\n path samplesheet\n\n output:\n path '*.csv' , emit: csv\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script: // This script is bundled with the pipeline, in nf-core/atacseq/bin/\n def args = task.ext.args ?: ''\n \"\"\"\n check_samplesheet.py \\\\\n $samplesheet \\\\\n $args\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n python: \\$(python --version | sed 's/Python //g')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/star_align.nf", "content": "process STAR_ALIGN {\n tag \"$meta.id\"\n label 'process_high'\n\n // Note: 2.7X indices incompatible with AWS iGenomes.\n conda \"bioconda::star=2.6.1d\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/star:2.6.1d--0' :\n 'biocontainers/star:2.6.1d--0' }\"\n\n input:\n tuple val(meta), path(reads)\n path index\n val seq_center\n\n output:\n tuple val(meta), path('*d.out.bam') , emit: bam\n tuple val(meta), path('*Log.final.out') , emit: log_final\n tuple val(meta), path('*Log.out') , emit: log_out\n tuple val(meta), path('*Log.progress.out'), emit: log_progress\n path \"versions.yml\" , emit: versions\n\n tuple val(meta), path('*sortedByCoord.out.bam') , optional:true, emit: bam_sorted\n tuple val(meta), path('*toTranscriptome.out.bam'), optional:true, emit: bam_transcript\n tuple val(meta), path('*Aligned.unsort.out.bam') , optional:true, emit: bam_unsorted\n tuple val(meta), path('*fastq.gz') , optional:true, emit: fastq\n tuple val(meta), path('*.tab') , optional:true, emit: tab\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def seq_center_tag = seq_center ? \"--outSAMattrRGline ID:$prefix 'CN:$seq_center' 'SM:$prefix'\" : \"--outSAMattrRGline ID:$prefix 'SM:$prefix'\"\n def out_sam_type = (args.contains('--outSAMtype')) ? '' : '--outSAMtype BAM Unsorted'\n def mv_unsorted_bam = (args.contains('--outSAMtype BAM Unsorted SortedByCoordinate')) ? \"mv ${prefix}.Aligned.out.bam ${prefix}.Aligned.unsort.out.bam\" : ''\n \"\"\"\n STAR \\\\\n --genomeDir $index \\\\\n --readFilesIn $reads \\\\\n --runThreadN $task.cpus \\\\\n --outFileNamePrefix $prefix. \\\\\n $out_sam_type \\\\\n $seq_center_tag \\\\\n $args\n $mv_unsorted_bam\n if [ -f ${prefix}.Unmapped.out.mate1 ]; then\n mv ${prefix}.Unmapped.out.mate1 ${prefix}.unmapped_1.fastq\n gzip ${prefix}.unmapped_1.fastq\n fi\n if [ -f ${prefix}.Unmapped.out.mate2 ]; then\n mv ${prefix}.Unmapped.out.mate2 ${prefix}.unmapped_2.fastq\n gzip ${prefix}.unmapped_2.fastq\n fi\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n star: \\$(STAR --version | sed -e \"s/STAR_//g\")\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/local/star_genomegenerate.nf", "content": "process STAR_GENOMEGENERATE {\n tag \"$fasta\"\n label 'process_high'\n\n // Note: 2.7X indices incompatible with AWS iGenomes.\n conda \"bioconda::star=2.6.1d bioconda::samtools=1.10 conda-forge::gawk=5.1.0\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-1fa26d1ce03c295fe2fdcf85831a92fbcbd7e8c2:59cdd445419f14abac76b31dd0d71217994cbcc9-0' :\n 'biocontainers/mulled-v2-1fa26d1ce03c295fe2fdcf85831a92fbcbd7e8c2:59cdd445419f14abac76b31dd0d71217994cbcc9-0' }\"\n\n input:\n path fasta\n path gtf\n\n output:\n path \"star\" , emit: index\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = (task.ext.args ?: '').tokenize()\n def memory = task.memory ? \"--limitGenomeGenerateRAM ${task.memory.toBytes() - 100000000}\" : ''\n if (args.contains('--genomeSAindexNbases')) {\n \"\"\"\n mkdir star\n STAR \\\\\n --runMode genomeGenerate \\\\\n --genomeDir star/ \\\\\n --genomeFastaFiles $fasta \\\\\n --sjdbGTFfile $gtf \\\\\n --runThreadN $task.cpus \\\\\n $memory \\\\\n ${args.join(' ')}\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n star: \\$(STAR --version | sed -e \"s/STAR_//g\")\n END_VERSIONS\n \"\"\"\n } else {\n \"\"\"\n samtools faidx $fasta\n NUM_BASES=`gawk '{sum = sum + \\$2}END{if ((log(sum)/log(2))/2 - 1 > 14) {printf \"%.0f\", 14} else {printf \"%.0f\", (log(sum)/log(2))/2 - 1}}' ${fasta}.fai`\n mkdir star\n STAR \\\\\n --runMode genomeGenerate \\\\\n --genomeDir star/ \\\\\n --genomeFastaFiles $fasta \\\\\n --sjdbGTFfile $gtf \\\\\n --runThreadN $task.cpus \\\\\n --genomeSAindexNbases \\$NUM_BASES \\\\\n $memory \\\\\n ${args.join(' ')}\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n star: \\$(STAR --version | sed -e \"s/STAR_//g\")\n END_VERSIONS\n \"\"\"\n }\n}\n" }, { "path": "modules/local/tss_extract.nf", "content": "process TSS_EXTRACT {\n\n conda \"conda-forge::sed=4.7\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/ubuntu:20.04' :\n 'nf-core/ubuntu:20.04' }\"\n\n input:\n path bed\n\n output:\n path \"*.bed\" , emit: tss\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n \"\"\"\n cat $bed | awk -v FS='\\t' -v OFS='\\t' '{ if(\\$6==\"+\") \\$3=\\$2+1; else \\$2=\\$3-1; print \\$1, \\$2, \\$3, \\$4, \\$5, \\$6;}' > ${bed.baseName}.tss.bed\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n sed: \\$(echo \\$(sed --version 2>&1) | sed 's/^.*GNU sed) //; s/ .*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/ataqv/ataqv/main.nf", "content": "process ATAQV_ATAQV {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda 'bioconda::ataqv=1.3.1'\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/ataqv:1.3.1--py310ha155cf9_1' :\n 'biocontainers/ataqv:1.3.1--py310ha155cf9_1' }\"\n\n input:\n tuple val(meta), path(bam), path(bai), path(peak_file)\n val organism\n val mito_name\n path tss_file\n path excl_regs_file\n path autosom_ref_file\n\n output:\n tuple val(meta), path(\"*.ataqv.json\"), emit: json\n tuple val(meta), path(\"*.problems\") , emit: problems, optional: true\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def mito = mito_name ? \"--mitochondrial-reference-name ${mito_name}\" : ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def peak = peak_file ? \"--peak-file $peak_file\" : ''\n def tss = tss_file ? \"--tss-file $tss_file\" : ''\n def excl_regs = excl_regs_file ? \"--excluded-region-file $excl_regs_file\" : ''\n def autosom_ref = autosom_ref_file ? \"--autosomal-reference-file $autosom_ref_file\" : ''\n \"\"\"\n ataqv \\\\\n $args \\\\\n $mito \\\\\n $peak \\\\\n $tss \\\\\n $excl_regs \\\\\n $autosom_ref \\\\\n --metrics-file \"${prefix}.ataqv.json\" \\\\\n --threads $task.cpus \\\\\n --name $prefix \\\\\n $organism \\\\\n $bam\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n ataqv: \\$( ataqv --version )\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/ataqv/ataqv/meta.yml", "content": "name: ataqv_ataqv\ndescription: ataqv function of a corresponding ataqv tool\nkeywords:\n - ATAC-seq\n - qc\n - ataqv\ntools:\n - ataqv:\n description: ataqv is a toolkit for measuring and comparing ATAC-seq results. It was written to help understand how well ATAC-seq assays have worked, and to make it easier to spot differences that might be caused by library prep or sequencing.\n homepage: https://github.com/ParkerLab/ataqv/blob/master/README.rst\n documentation: https://github.com/ParkerLab/ataqv/blob/master/README.rst\n tool_dev_url: https://github.com/ParkerLab/ataqv\n doi: \"10.1016/j.cels.2020.02.009\"\n licence: [\"GPL v3\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM file\n pattern: \"*.bam\"\n - bai:\n type: file\n description: BAM index file with the same prefix as bam file. Required if tss_file input is provided.\n pattern: \"*.bam.bai\"\n - peak_file:\n type: file\n description: A BED file of peaks called for alignments in the BAM file\n pattern: \"*.bed\"\n - organism:\n type: string\n description: The subject of the experiment, which determines the list of autosomes (see \"Reference Genome Configuration\" section at https://github.com/ParkerLab/ataqv).\n - mito_name:\n type: string\n description: Name of the mitochondrial sequence.\n - tss_file:\n type: file\n description: A BED file of transcription start sites for the experiment organism. If supplied, a TSS enrichment score will be calculated according to the ENCODE data standards. This calculation requires that the BAM file of alignments be indexed.\n pattern: \"*.bed\"\n - excl_regs_file:\n type: file\n description: A BED file containing excluded regions. Peaks or TSS overlapping these will be ignored.\n pattern: \"*.bed\"\n - autosom_ref_file:\n type: file\n description: A file containing autosomal reference names, one per line. The names must match the reference names in the alignment file exactly, or the metrics based on counts of autosomal alignments will be wrong.\n\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - json:\n type: file\n description: The JSON file to which metrics will be written.\n - problems:\n type: file\n description: If given, problematic reads will be logged to a file per read group, with names derived from the read group IDs, with \".problems\" appended. If no read groups are found, the reads will be written to one file named after the BAM file.\n pattern: \"*.problems\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@i-pletenev\"\n" }, { "path": "modules/nf-core/ataqv/mkarv/main.nf", "content": "process ATAQV_MKARV {\n label 'process_medium'\n\n conda 'bioconda::ataqv=1.3.1'\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/ataqv:1.3.1--py310ha155cf9_1':\n 'biocontainers/ataqv:1.3.1--py310ha155cf9_1' }\"\n\n input:\n path \"jsons/*\"\n\n output:\n path \"html\" , emit: html\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n \"\"\"\n mkarv \\\\\n $args \\\\\n --concurrency $task.cpus \\\\\n --force \\\\\n ./html/ \\\\\n jsons/*\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n # mkarv: \\$( mkarv --version ) # Use this when version string has been fixed\n ataqv: \\$( ataqv --version )\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/ataqv/mkarv/meta.yml", "content": "name: \"ataqv_mkarv\"\ndescription: mkarv function of a corresponding ataqv tool\nkeywords:\n - ataqv\n - ATAC-seq\n - qc\n - ataqv\n - mkarv\n\ntools:\n - \"ataqv\":\n description: \"ataqv is a toolkit for measuring and comparing ATAC-seq results. It was written to help understand how well ATAC-seq assays have worked, and to make it easier to spot differences that might be caused by library prep or sequencing.\"\n homepage: \"https://github.com/ParkerLab/ataqv/blob/master/README.rst\"\n documentation: \"https://github.com/ParkerLab/ataqv/blob/master/README.rst\"\n tool_dev_url: \"https://github.com/ParkerLab/ataqv\"\n\n licence: \"['GPL v3']\"\n\ninput:\n - json:\n type: file\n description: The JSON file with ataqv metrics\n pattern: \"*.json\"\n\noutput:\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n - html:\n type: directory\n description: Web application to visualize results in HTML format\n pattern: \"*.html\"\n\nauthors:\n - \"@bjlang\"\n" }, { "path": "modules/nf-core/bowtie2/align/main.nf", "content": "process BOWTIE2_ALIGN {\n tag \"$meta.id\"\n label \"process_high\"\n\n conda \"bioconda::bowtie2=2.4.4 bioconda::samtools=1.16.1 conda-forge::pigz=2.6\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-ac74a7f02cebcfcc07d8e8d1d750af9c83b4d45a:a0ffedb52808e102887f6ce600d092675bf3528a-0' :\n 'biocontainers/mulled-v2-ac74a7f02cebcfcc07d8e8d1d750af9c83b4d45a:a0ffedb52808e102887f6ce600d092675bf3528a-0' }\"\n\n input:\n tuple val(meta) , path(reads)\n tuple val(meta2), path(index)\n val save_unaligned\n val sort_bam\n\n output:\n tuple val(meta), path(\"*.{bam,sam}\"), emit: aligned\n tuple val(meta), path(\"*.log\") , emit: log\n tuple val(meta), path(\"*fastq.gz\") , emit: fastq, optional:true\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: \"\"\n def args2 = task.ext.args2 ?: \"\"\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n\n def unaligned = \"\"\n def reads_args = \"\"\n if (meta.single_end) {\n unaligned = save_unaligned ? \"--un-gz ${prefix}.unmapped.fastq.gz\" : \"\"\n reads_args = \"-U ${reads}\"\n } else {\n unaligned = save_unaligned ? \"--un-conc-gz ${prefix}.unmapped.fastq.gz\" : \"\"\n reads_args = \"-1 ${reads[0]} -2 ${reads[1]}\"\n }\n\n def samtools_command = sort_bam ? 'sort' : 'view'\n def extension_pattern = /(--output-fmt|-O)+\\s+(\\S+)/\n def extension = (args2 ==~ extension_pattern) ? (args2 =~ extension_pattern)[0][2].toLowerCase() : \"bam\"\n\n \"\"\"\n INDEX=`find -L ./ -name \"*.rev.1.bt2\" | sed \"s/\\\\.rev.1.bt2\\$//\"`\n [ -z \"\\$INDEX\" ] && INDEX=`find -L ./ -name \"*.rev.1.bt2l\" | sed \"s/\\\\.rev.1.bt2l\\$//\"`\n [ -z \"\\$INDEX\" ] && echo \"Bowtie2 index files not found\" 1>&2 && exit 1\n\n bowtie2 \\\\\n -x \\$INDEX \\\\\n $reads_args \\\\\n --threads $task.cpus \\\\\n $unaligned \\\\\n $args \\\\\n 2> ${prefix}.bowtie2.log \\\\\n | samtools $samtools_command $args2 --threads $task.cpus -o ${prefix}.${extension} -\n\n if [ -f ${prefix}.unmapped.fastq.1.gz ]; then\n mv ${prefix}.unmapped.fastq.1.gz ${prefix}.unmapped_1.fastq.gz\n fi\n\n if [ -f ${prefix}.unmapped.fastq.2.gz ]; then\n mv ${prefix}.unmapped.fastq.2.gz ${prefix}.unmapped_2.fastq.gz\n fi\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bowtie2: \\$(echo \\$(bowtie2 --version 2>&1) | sed 's/^.*bowtie2-align-s version //; s/ .*\\$//')\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n pigz: \\$( pigz --version 2>&1 | sed 's/pigz //g' )\n END_VERSIONS\n \"\"\"\n\n stub:\n def args2 = task.ext.args2 ?: \"\"\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def extension_pattern = /(--output-fmt|-O)+\\s+(\\S+)/\n def extension = (args2 ==~ extension_pattern) ? (args2 =~ extension_pattern)[0][2].toLowerCase() : \"bam\"\n\n \"\"\"\n touch ${prefix}.${extension}\n touch ${prefix}.bowtie2.log\n touch ${prefix}.unmapped_1.fastq.gz\n touch ${prefix}.unmapped_2.fastq.gz\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bowtie2: \\$(echo \\$(bowtie2 --version 2>&1) | sed 's/^.*bowtie2-align-s version //; s/ .*\\$//')\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n pigz: \\$( pigz --version 2>&1 | sed 's/pigz //g' )\n END_VERSIONS\n \"\"\"\n\n}\n" }, { "path": "modules/nf-core/bowtie2/align/meta.yml", "content": "name: bowtie2_align\ndescription: Align reads to a reference genome using bowtie2\nkeywords:\n - align\n - map\n - fasta\n - fastq\n - genome\n - reference\ntools:\n - bowtie2:\n description: |\n Bowtie 2 is an ultrafast and memory-efficient tool for aligning\n sequencing reads to long reference sequences.\n homepage: http://bowtie-bio.sourceforge.net/bowtie2/index.shtml\n documentation: http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml\n doi: 10.1038/nmeth.1923\n licence: [\"GPL-3.0-or-later\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - reads:\n type: file\n description: |\n List of input FastQ files of size 1 and 2 for single-end and paired-end data,\n respectively.\n - meta2:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'test', single_end:false ]\n - index:\n type: file\n description: Bowtie2 genome index files\n pattern: \"*.ebwt\"\n - save_unaligned:\n type: boolean\n description: |\n Save reads that do not map to the reference (true) or discard them (false)\n (default: false)\n - sort_bam:\n type: boolean\n description: use samtools sort (true) or samtools view (false)\n pattern: \"true or false\"\noutput:\n - aligned:\n type: file\n description: Output BAM/SAM file containing read alignments\n pattern: \"*.{bam,sam}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n - fastq:\n type: file\n description: Unaligned FastQ files\n pattern: \"*.fastq.gz\"\n - log:\n type: file\n description: Aligment log\n pattern: \"*.log\"\nauthors:\n - \"@joseespinosa\"\n - \"@drpatelh\"\n" }, { "path": "modules/nf-core/bowtie2/build/main.nf", "content": "process BOWTIE2_BUILD {\n tag \"$fasta\"\n label 'process_high'\n\n conda \"bioconda::bowtie2=2.4.4\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/bowtie2:2.4.4--py39hbb4e92a_0' :\n 'biocontainers/bowtie2:2.4.4--py39hbb4e92a_0' }\"\n\n input:\n tuple val(meta), path(fasta)\n\n output:\n tuple val(meta), path('bowtie2') , emit: index\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n \"\"\"\n mkdir bowtie2\n bowtie2-build $args --threads $task.cpus $fasta bowtie2/${fasta.baseName}\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bowtie2: \\$(echo \\$(bowtie2 --version 2>&1) | sed 's/^.*bowtie2-align-s version //; s/ .*\\$//')\n END_VERSIONS\n \"\"\"\n\n stub:\n \"\"\"\n mkdir bowtie2\n touch bowtie2/${fasta.baseName}.{1..4}.bt2\n touch bowtie2/${fasta.baseName}.rev.{1,2}.bt2\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bowtie2: \\$(echo \\$(bowtie2 --version 2>&1) | sed 's/^.*bowtie2-align-s version //; s/ .*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/bowtie2/build/meta.yml", "content": "name: bowtie2_build\ndescription: Builds bowtie index for reference genome\nkeywords:\n - build\n - index\n - fasta\n - genome\n - reference\ntools:\n - bowtie2:\n description: |\n Bowtie 2 is an ultrafast and memory-efficient tool for aligning\n sequencing reads to long reference sequences.\n homepage: http://bowtie-bio.sourceforge.net/bowtie2/index.shtml\n documentation: http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml\n doi: 10.1038/nmeth.1923\n licence: [\"GPL-3.0-or-later\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'test', single_end:false ]\n - fasta:\n type: file\n description: Input genome fasta file\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'test', single_end:false ]\n - index:\n type: file\n description: Bowtie2 genome index files\n pattern: \"*.bt2\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@joseespinosa\"\n - \"@drpatelh\"\n" }, { "path": "modules/nf-core/bwa/index/main.nf", "content": "process BWA_INDEX {\n tag \"$fasta\"\n label 'process_single'\n\n conda \"bioconda::bwa=0.7.17\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/bwa:0.7.17--hed695b0_7' :\n 'biocontainers/bwa:0.7.17--hed695b0_7' }\"\n\n input:\n tuple val(meta), path(fasta)\n\n output:\n tuple val(meta), path(bwa) , emit: index\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n \"\"\"\n mkdir bwa\n bwa \\\\\n index \\\\\n $args \\\\\n -p bwa/${fasta.baseName} \\\\\n $fasta\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bwa: \\$(echo \\$(bwa 2>&1) | sed 's/^.*Version: //; s/Contact:.*\\$//')\n END_VERSIONS\n \"\"\"\n\n stub:\n \"\"\"\n mkdir bwa\n\n touch bwa/genome.amb\n touch bwa/genome.ann\n touch bwa/genome.bwt\n touch bwa/genome.pac\n touch bwa/genome.sa\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bwa: \\$(echo \\$(bwa 2>&1) | sed 's/^.*Version: //; s/Contact:.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/bwa/index/meta.yml", "content": "name: bwa_index\ndescription: Create BWA index for reference genome\nkeywords:\n - index\n - fasta\n - genome\n - reference\ntools:\n - bwa:\n description: |\n BWA is a software package for mapping DNA sequences against\n a large reference genome, such as the human genome.\n homepage: http://bio-bwa.sourceforge.net/\n documentation: http://www.htslib.org/doc/samtools.html\n arxiv: arXiv:1303.3997\n licence: [\"GPL-3.0-or-later\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing reference information.\n e.g. [ id:'test', single_end:false ]\n - fasta:\n type: file\n description: Input genome fasta file\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing reference information.\n e.g. [ id:'test', single_end:false ]\n - index:\n type: file\n description: BWA genome index files\n pattern: \"*.{amb,ann,bwt,pac,sa}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@maxulysse\"\n" }, { "path": "modules/nf-core/bwa/mem/main.nf", "content": "process BWA_MEM {\n tag \"$meta.id\"\n label 'process_high'\n\n conda \"bioconda::bwa=0.7.17 bioconda::samtools=1.16.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-fe8faa35dbf6dc65a0f7f5d4ea12e31a79f73e40:219b6c272b25e7e642ae3ff0bf0c5c81a5135ab4-0' :\n 'biocontainers/mulled-v2-fe8faa35dbf6dc65a0f7f5d4ea12e31a79f73e40:219b6c272b25e7e642ae3ff0bf0c5c81a5135ab4-0' }\"\n\n input:\n tuple val(meta), path(reads)\n tuple val(meta2), path(index)\n val sort_bam\n\n output:\n tuple val(meta), path(\"*.bam\"), emit: bam\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def args2 = task.ext.args2 ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def samtools_command = sort_bam ? 'sort' : 'view'\n \"\"\"\n INDEX=`find -L ./ -name \"*.amb\" | sed 's/\\\\.amb\\$//'`\n\n bwa mem \\\\\n $args \\\\\n -t $task.cpus \\\\\n \\$INDEX \\\\\n $reads \\\\\n | samtools $samtools_command $args2 --threads $task.cpus -o ${prefix}.bam -\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n bwa: \\$(echo \\$(bwa 2>&1) | sed 's/^.*Version: //; s/Contact:.*\\$//')\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/bwa/mem/meta.yml", "content": "name: bwa_mem\ndescription: Performs fastq alignment to a fasta reference using BWA\nkeywords:\n - mem\n - bwa\n - alignment\n - map\n - fastq\n - bam\n - sam\ntools:\n - bwa:\n description: |\n BWA is a software package for mapping DNA sequences against\n a large reference genome, such as the human genome.\n homepage: http://bio-bwa.sourceforge.net/\n documentation: http://www.htslib.org/doc/samtools.html\n arxiv: arXiv:1303.3997\n licence: [\"GPL-3.0-or-later\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - reads:\n type: file\n description: |\n List of input FastQ files of size 1 and 2 for single-end and paired-end data,\n respectively.\n - meta2:\n type: map\n description: |\n Groovy Map containing reference information.\n e.g. [ id:'test', single_end:false ]\n - index:\n type: file\n description: BWA genome index files\n pattern: \"Directory containing BWA index *.{amb,ann,bwt,pac,sa}\"\n - sort_bam:\n type: boolean\n description: use samtools sort (true) or samtools view (false)\n pattern: \"true or false\"\noutput:\n - bam:\n type: file\n description: Output BAM file containing read alignments\n pattern: \"*.{bam}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@jeremy1805\"\n" }, { "path": "modules/nf-core/chromap/chromap/main.nf", "content": "process CHROMAP_CHROMAP {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::chromap=0.2.4 bioconda::samtools=1.16.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/mulled-v2-1f09f39f20b1c4ee36581dc81cc323c70e661633:5b2e433ab8b3d1ef098fc944b567fd98caa23f56-0' :\n 'biocontainers/mulled-v2-1f09f39f20b1c4ee36581dc81cc323c70e661633:5b2e433ab8b3d1ef098fc944b567fd98caa23f56-0' }\"\n\n input:\n tuple val(meta), path(reads)\n tuple val(meta2), path(fasta)\n tuple val(meta3), path(index)\n path barcodes\n path whitelist\n path chr_order\n path pairs_chr_order\n\n output:\n tuple val(meta), path(\"*.bed.gz\") , optional:true, emit: bed\n tuple val(meta), path(\"*.bam\") , optional:true, emit: bam\n tuple val(meta), path(\"*.tagAlign.gz\"), optional:true, emit: tagAlign\n tuple val(meta), path(\"*.pairs.gz\") , optional:true, emit: pairs\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def args2 = task.ext.args2 ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def args_list = args.tokenize()\n\n def file_extension = args.contains(\"--SAM\") ? 'sam' : args.contains(\"--TagAlign\")? 'tagAlign' : args.contains(\"--pairs\")? 'pairs' : 'bed'\n if (barcodes) {\n args_list << \"-b ${barcodes.join(',')}\"\n if (whitelist) {\n args_list << \"--barcode-whitelist $whitelist\"\n }\n }\n if (chr_order) {\n args_list << \"--chr-order $chr_order\"\n }\n if (pairs_chr_order){\n args_list << \"--pairs-natural-chr-order $pairs_chr_order\"\n }\n def final_args = args_list.join(' ')\n def compression_cmds = \"gzip -n ${prefix}.${file_extension}\"\n if (args.contains(\"--SAM\")) {\n compression_cmds = \"\"\"\n samtools view $args2 -@ $task.cpus -bh \\\\\n -o ${prefix}.bam ${prefix}.${file_extension}\n rm ${prefix}.${file_extension}\n \"\"\"\n }\n if (meta.single_end) {\n \"\"\"\n chromap \\\\\n $final_args \\\\\n -t $task.cpus \\\\\n -x $index \\\\\n -r $fasta \\\\\n -1 ${reads.join(',')} \\\\\n -o ${prefix}.${file_extension}\n\n $compression_cmds\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n chromap: \\$(echo \\$(chromap --version 2>&1))\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n } else {\n \"\"\"\n chromap \\\\\n $final_args \\\\\n -t $task.cpus \\\\\n -x $index \\\\\n -r $fasta \\\\\n -1 ${reads[0]} \\\\\n -2 ${reads[1]} \\\\\n -o ${prefix}.${file_extension}\n\n $compression_cmds\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n chromap: \\$(echo \\$(chromap --version 2>&1))\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n }\n}\n" }, { "path": "modules/nf-core/chromap/chromap/meta.yml", "content": "name: chromap_chromap\ndescription: |\n Performs preprocessing and alignment of chromatin fastq files to\n fasta reference files using chromap.\nkeywords:\n - chromap\n - alignment\n - map\n - fastq\n - bam\n - sam\n - hi-c\n - atac-seq\n - chip-seq\n - trimming\n - duplicate removal\ntools:\n - chromap:\n description: Fast alignment and preprocessing of chromatin profiles\n homepage: https://github.com/haowenz/chromap\n documentation: https://github.com/haowenz/chromap\n tool_dev_url: https://github.com/haowenz/chromap\n\n licence: [\"GPL v3\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - reads:\n type: file\n description: |\n List of input FastQ files of size 1 and 2 for single-end and paired-end data,\n respectively.\n - meta2:\n type: map\n description: |\n Groovy Map containing information for the fasta\n e.g. [ id:'test' ]\n - fasta:\n type: file\n description: |\n The fasta reference file.\n - meta3:\n type: map\n description: |\n Groovy Map containing information for the index\n e.g. [ id:'test' ]\n - index:\n type: file\n description: |\n Chromap genome index files (*.index)\n - barcodes:\n type: file\n description: |\n Cell barcode files\n - whitelist:\n type: file\n description: |\n Cell barcode whitelist file\n - chr_order:\n type: file\n description: |\n Custom chromosome order\n - pairs_chr_order:\n type: file\n description: |\n Natural chromosome order for pairs flipping\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n - bed:\n type: file\n description: BED file\n pattern: \"*.bed.gz\"\n - bam:\n type: file\n description: BAM file\n pattern: \"*.bam\"\n - tagAlign:\n type: file\n description: tagAlign file\n pattern: \"*.tagAlign.gz\"\n - pairs:\n type: file\n description: pairs file\n pattern: \"*.pairs.gz\"\n\nauthors:\n - \"@mahesh-panchal\"\n - \"@joseespinosa\"\n" }, { "path": "modules/nf-core/chromap/index/main.nf", "content": "process CHROMAP_INDEX {\n tag \"$fasta\"\n label 'process_medium'\n\n conda \"bioconda::chromap=0.2.4\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/chromap:0.2.4--hd03093a_0' :\n 'biocontainers/chromap:0.2.4--hd03093a_0' }\"\n\n input:\n tuple val(meta), path(fasta)\n\n output:\n tuple val(meta), path (\"*.index\"), emit: index\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = fasta.baseName\n \"\"\"\n chromap \\\\\n -i \\\\\n $args \\\\\n -t $task.cpus \\\\\n -r $fasta \\\\\n -o ${prefix}.index\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n chromap: \\$(echo \\$(chromap --version 2>&1))\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/chromap/index/meta.yml", "content": "name: chromap_index\ndescription: Indexes a fasta reference genome ready for chromatin profiling.\nkeywords:\n - index\n - fasta\n - genome\n - reference\ntools:\n - chromap:\n description: Fast alignment and preprocessing of chromatin profiles\n homepage: https://github.com/haowenz/chromap\n documentation: https://github.com/haowenz/chromap\n tool_dev_url: https://github.com/haowenz/chromap\n\n licence: [\"GPL v3\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'test' ]\n - fasta:\n type: file\n description: Fasta reference file.\n\noutput:\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n - meta:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'test' ]\n - index:\n type: file\n description: Index file of the reference genome\n pattern: \"*.{index}\"\n\nauthors:\n - \"@mahesh-panchal\"\n - \"@joseespinosa\"\n" }, { "path": "modules/nf-core/custom/dumpsoftwareversions/main.nf", "content": "process CUSTOM_DUMPSOFTWAREVERSIONS {\n label 'process_single'\n\n // Requires `pyyaml` which does not have a dedicated container but is in the MultiQC container\n conda \"bioconda::multiqc=1.14\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/multiqc:1.14--pyhdfd78af_0' :\n 'biocontainers/multiqc:1.14--pyhdfd78af_0' }\"\n\n input:\n path versions\n\n output:\n path \"software_versions.yml\" , emit: yml\n path \"software_versions_mqc.yml\", emit: mqc_yml\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n template 'dumpsoftwareversions.py'\n}\n" }, { "path": "modules/nf-core/custom/dumpsoftwareversions/meta.yml", "content": "# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/modules/yaml-schema.json\nname: custom_dumpsoftwareversions\ndescription: Custom module used to dump software versions within the nf-core pipeline template\nkeywords:\n - custom\n - dump\n - version\ntools:\n - custom:\n description: Custom module used to dump software versions within the nf-core pipeline template\n homepage: https://github.com/nf-core/tools\n documentation: https://github.com/nf-core/tools\n licence: [\"MIT\"]\ninput:\n - versions:\n type: file\n description: YML file containing software versions\n pattern: \"*.yml\"\n\noutput:\n - yml:\n type: file\n description: Standard YML file containing software versions\n pattern: \"software_versions.yml\"\n - mqc_yml:\n type: file\n description: MultiQC custom content YML file containing software versions\n pattern: \"software_versions_mqc.yml\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@drpatelh\"\n - \"@grst\"\n" }, { "path": "modules/nf-core/custom/dumpsoftwareversions/templates/dumpsoftwareversions.py", "content": "#!/usr/bin/env python\n\n\n\"\"\"Provide functions to merge multiple versions.yml files.\"\"\"\n\n\nimport yaml\nimport platform\nfrom textwrap import dedent\n\n\ndef _make_versions_html(versions):\n \"\"\"Generate a tabular HTML output of all versions for MultiQC.\"\"\"\n html = [\n dedent(\n \"\"\"\\\\\n \n \n \n \n \n \n \n \n \n \"\"\"\n )\n ]\n for process, tmp_versions in sorted(versions.items()):\n html.append(\"\")\n for i, (tool, version) in enumerate(sorted(tmp_versions.items())):\n html.append(\n dedent(\n f\"\"\"\\\\\n \n \n \n \n \n \"\"\"\n )\n )\n html.append(\"\")\n html.append(\"
    Process Name Software Version
    {process if (i == 0) else ''}{tool}{version}
    \")\n return \"\\\\n\".join(html)\n\n\ndef main():\n \"\"\"Load all version files and generate merged output.\"\"\"\n versions_this_module = {}\n versions_this_module[\"${task.process}\"] = {\n \"python\": platform.python_version(),\n \"yaml\": yaml.__version__,\n }\n\n with open(\"$versions\") as f:\n versions_by_process = yaml.load(f, Loader=yaml.BaseLoader) | versions_this_module\n\n # aggregate versions by the module name (derived from fully-qualified process name)\n versions_by_module = {}\n for process, process_versions in versions_by_process.items():\n module = process.split(\":\")[-1]\n try:\n if versions_by_module[module] != process_versions:\n raise AssertionError(\n \"We assume that software versions are the same between all modules. \"\n \"If you see this error-message it means you discovered an edge-case \"\n \"and should open an issue in nf-core/tools. \"\n )\n except KeyError:\n versions_by_module[module] = process_versions\n\n versions_by_module[\"Workflow\"] = {\n \"Nextflow\": \"$workflow.nextflow.version\",\n \"$workflow.manifest.name\": \"$workflow.manifest.version\",\n }\n\n versions_mqc = {\n \"id\": \"software_versions\",\n \"section_name\": \"${workflow.manifest.name} Software Versions\",\n \"section_href\": \"https://github.com/${workflow.manifest.name}\",\n \"plot_type\": \"html\",\n \"description\": \"are collected at run time from the software output.\",\n \"data\": _make_versions_html(versions_by_module),\n }\n\n with open(\"software_versions.yml\", \"w\") as f:\n yaml.dump(versions_by_module, f, default_flow_style=False)\n with open(\"software_versions_mqc.yml\", \"w\") as f:\n yaml.dump(versions_mqc, f, default_flow_style=False)\n\n with open(\"versions.yml\", \"w\") as f:\n yaml.dump(versions_this_module, f, default_flow_style=False)\n\n\nif __name__ == \"__main__\":\n main()\n" }, { "path": "modules/nf-core/custom/getchromsizes/main.nf", "content": "process CUSTOM_GETCHROMSIZES {\n tag \"$fasta\"\n label 'process_single'\n\n conda \"bioconda::samtools=1.16.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/samtools:1.16.1--h6899075_1' :\n 'biocontainers/samtools:1.16.1--h6899075_1' }\"\n\n input:\n tuple val(meta), path(fasta)\n\n output:\n tuple val(meta), path (\"*.sizes\"), emit: sizes\n tuple val(meta), path (\"*.fai\") , emit: fai\n tuple val(meta), path (\"*.gzi\") , emit: gzi, optional: true\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n \"\"\"\n samtools faidx $fasta\n cut -f 1,2 ${fasta}.fai > ${fasta}.sizes\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n getchromsizes: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n\n stub:\n \"\"\"\n touch ${fasta}.fai\n touch ${fasta}.sizes\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n getchromsizes: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/custom/getchromsizes/meta.yml", "content": "name: custom_getchromsizes\ndescription: Generates a FASTA file of chromosome sizes and a fasta index file\nkeywords:\n - fasta\n - chromosome\n - indexing\ntools:\n - samtools:\n description: Tools for dealing with SAM, BAM and CRAM files\n homepage: http://www.htslib.org/\n documentation: http://www.htslib.org/doc/samtools.html\n tool_dev_url: https://github.com/samtools/samtools\n doi: 10.1093/bioinformatics/btp352\n licence: [\"MIT\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - fasta:\n type: file\n description: FASTA file\n pattern: \"*.{fa,fasta,fna,fas}\"\n\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - sizes:\n type: file\n description: File containing chromosome lengths\n pattern: \"*.{sizes}\"\n - fai:\n type: file\n description: FASTA index file\n pattern: \"*.{fai}\"\n - gzi:\n type: file\n description: Optional gzip index file for compressed inputs\n pattern: \"*.gzi\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@tamara-hodgetts\"\n - \"@chris-cheshire\"\n - \"@muffato\"\n" }, { "path": "modules/nf-core/deeptools/computematrix/main.nf", "content": "process DEEPTOOLS_COMPUTEMATRIX {\n tag \"$meta.id\"\n label 'process_high'\n\n conda \"bioconda::deeptools=3.5.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/deeptools:3.5.1--py_0' :\n 'biocontainers/deeptools:3.5.1--py_0' }\"\n\n input:\n tuple val(meta), path(bigwig)\n path bed\n\n output:\n tuple val(meta), path(\"*.mat.gz\") , emit: matrix\n tuple val(meta), path(\"*.mat.tab\"), emit: table\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n computeMatrix \\\\\n $args \\\\\n --regionsFileName $bed \\\\\n --scoreFileName $bigwig \\\\\n --outFileName ${prefix}.computeMatrix.mat.gz \\\\\n --outFileNameMatrix ${prefix}.computeMatrix.vals.mat.tab \\\\\n --numberOfProcessors $task.cpus\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n deeptools: \\$(computeMatrix --version | sed -e \"s/computeMatrix //g\")\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/deeptools/computematrix/meta.yml", "content": "name: deeptools_computematrix\ndescription: calculates scores per genome regions for other deeptools plotting utilities\nkeywords:\n - genome\n - regions\n - scores\n - matrix\ntools:\n - deeptools:\n description: A set of user-friendly tools for normalization and visualization of deep-sequencing data\n documentation: https://deeptools.readthedocs.io/en/develop/index.html\n tool_dev_url: https://github.com/deeptools/deepTools\n doi: \"10.1093/nar/gku365\"\n licence: [\"GPL v3\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test' ]\n - bigwig:\n type: file\n description: bigwig file containing genomic scores\n pattern: \"*.{bw,bigwig}\"\n - bed:\n type: file\n description: bed file containing genomic regions\n pattern: \"*.{bed}\"\n\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - matrix:\n type: file\n description: |\n gzipped matrix file needed by the plotHeatmap and plotProfile\n deeptools utilities\n pattern: \"*.{computeMatrix.mat.gz}\"\n - table:\n type: file\n description: |\n tabular file containing the scores of the generated matrix\n pattern: \"*.{computeMatrix.vals.mat.tab}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@jeremy1805\"\n - \"@emiller88\"\n - \"@drpatelh\"\n - \"@joseespinosa\"\n" }, { "path": "modules/nf-core/deeptools/plotfingerprint/main.nf", "content": "process DEEPTOOLS_PLOTFINGERPRINT {\n tag \"$meta.id\"\n label 'process_high'\n\n conda \"bioconda::deeptools=3.5.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/deeptools:3.5.1--py_0' :\n 'biocontainers/deeptools:3.5.1--py_0' }\"\n\n input:\n tuple val(meta), path(bams), path(bais)\n\n output:\n tuple val(meta), path(\"*.pdf\") , emit: pdf\n tuple val(meta), path(\"*.raw.txt\") , emit: matrix\n tuple val(meta), path(\"*.qcmetrics.txt\"), emit: metrics\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def extend = (meta.single_end && params.fragment_size > 0) ? \"--extendReads ${params.fragment_size}\" : ''\n \"\"\"\n plotFingerprint \\\\\n $args \\\\\n $extend \\\\\n --bamfiles ${bams.join(' ')} \\\\\n --plotFile ${prefix}.plotFingerprint.pdf \\\\\n --outRawCounts ${prefix}.plotFingerprint.raw.txt \\\\\n --outQualityMetrics ${prefix}.plotFingerprint.qcmetrics.txt \\\\\n --numberOfProcessors $task.cpus\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n deeptools: \\$(plotFingerprint --version | sed -e \"s/plotFingerprint //g\")\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/deeptools/plotfingerprint/meta.yml", "content": "name: deeptools_plotfingerprint\ndescription: plots cumulative reads coverages by BAM file\nkeywords:\n - plot\n - fingerprint\n - cumulative coverage\n - bam\ntools:\n - deeptools:\n description: A set of user-friendly tools for normalization and visualization of deep-sequencing data\n documentation: https://deeptools.readthedocs.io/en/develop/index.html\n tool_dev_url: https://github.com/deeptools/deepTools\n doi: \"10.1093/nar/gku365\"\n licence: [\"GPL v3\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test' ]\n - bam:\n type: file\n description: One or more BAM files\n pattern: \"*.{bam}\"\n - bais:\n type: file\n description: Corresponding BAM file indexes\n pattern: \"*.bam.bai\"\n\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - pdf:\n type: file\n description: |\n Output figure containing resulting plot\n pattern: \"*.{plotFingerprint.pdf}\"\n - matrix:\n type: file\n description: |\n Output file summarizing the read counts per bin\n pattern: \"*.{plotFingerprint.raw.txt}\"\n - metrics:\n type: file\n description: |\n file containing BAM file quality metrics\n pattern: \"*.{qcmetrics.txt}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@emiller88\"\n - \"@drpatelh\"\n - \"@joseespinosa\"\n" }, { "path": "modules/nf-core/deeptools/plotheatmap/main.nf", "content": "process DEEPTOOLS_PLOTHEATMAP {\n tag \"$meta.id\"\n label 'process_low'\n\n conda \"bioconda::deeptools=3.5.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/deeptools:3.5.1--py_0' :\n 'biocontainers/deeptools:3.5.1--py_0' }\"\n\n input:\n tuple val(meta), path(matrix)\n\n output:\n tuple val(meta), path(\"*.pdf\"), emit: pdf\n tuple val(meta), path(\"*.tab\"), emit: table\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n plotHeatmap \\\\\n $args \\\\\n --matrixFile $matrix \\\\\n --outFileName ${prefix}.plotHeatmap.pdf \\\\\n --outFileNameMatrix ${prefix}.plotHeatmap.mat.tab\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n deeptools: \\$(plotHeatmap --version | sed -e \"s/plotHeatmap //g\")\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/deeptools/plotheatmap/meta.yml", "content": "name: deeptools_plotheatmap\ndescription: plots values produced by deeptools_computematrix as a heatmap\nkeywords:\n - plot\n - heatmap\n - scores\n - matrix\ntools:\n - deeptools:\n description: A set of user-friendly tools for normalization and visualization of deep-sequencing data\n documentation: https://deeptools.readthedocs.io/en/develop/index.html\n tool_dev_url: https://github.com/deeptools/deepTools\n doi: \"10.1093/nar/gku365\"\n licence: [\"GPL v3\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test' ]\n - matrix:\n type: file\n description: |\n gzipped matrix file produced by deeptools_\n computematrix deeptools utility\n pattern: \"*.{mat.gz}\"\n\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - pdf:\n type: file\n description: |\n Output figure containing resulting plot\n pattern: \"*.{plotHeatmap.pdf}\"\n - matrix:\n type: file\n description: |\n File containing the matrix of values\n used to generate the heatmap\n pattern: \"*.{plotHeatmap.mat.tab}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@emiller88\"\n - \"@drpatelh\"\n - \"@joseespinosa\"\n" }, { "path": "modules/nf-core/deeptools/plotprofile/main.nf", "content": "process DEEPTOOLS_PLOTPROFILE {\n tag \"$meta.id\"\n label 'process_low'\n\n conda \"bioconda::deeptools=3.5.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/deeptools:3.5.1--py_0' :\n 'biocontainers/deeptools:3.5.1--py_0' }\"\n\n input:\n tuple val(meta), path(matrix)\n\n output:\n tuple val(meta), path(\"*.pdf\"), emit: pdf\n tuple val(meta), path(\"*.tab\"), emit: table\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n plotProfile \\\\\n $args \\\\\n --matrixFile $matrix \\\\\n --outFileName ${prefix}.plotProfile.pdf \\\\\n --outFileNameData ${prefix}.plotProfile.tab\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n deeptools: \\$(plotProfile --version | sed -e \"s/plotProfile //g\")\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/deeptools/plotprofile/meta.yml", "content": "name: deeptools_plotprofile\ndescription: plots values produced by deeptools_computematrix as a profile plot\nkeywords:\n - plot\n - profile\n - scores\n - matrix\ntools:\n - deeptools:\n description: A set of user-friendly tools for normalization and visualization of deep-sequencing data\n documentation: https://deeptools.readthedocs.io/en/develop/index.html\n tool_dev_url: https://github.com/deeptools/deepTools\n doi: \"10.1093/nar/gku365\"\n licence: [\"GPL v3\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test' ]\n - matrix:\n type: file\n description: |\n gzipped matrix file produced by deeptools_\n computematrix deeptools utility\n pattern: \"*.{mat.gz}\"\n\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - pdf:\n type: file\n description: |\n Output figure containing resulting plot\n pattern: \"*.{plotProfile.pdf}\"\n - matrix:\n type: file\n description: |\n File containing the matrix of values\n used to generate the profile\n pattern: \"*.{plotProfile.mat.tab}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@emiller88\"\n - \"@drpatelh\"\n - \"@joseespinosa\"\n" }, { "path": "modules/nf-core/fastqc/main.nf", "content": "process FASTQC {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::fastqc=0.11.9\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/fastqc:0.11.9--0' :\n 'biocontainers/fastqc:0.11.9--0' }\"\n\n input:\n tuple val(meta), path(reads)\n\n output:\n tuple val(meta), path(\"*.html\"), emit: html\n tuple val(meta), path(\"*.zip\") , emit: zip\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n // Make list of old name and new name pairs to use for renaming in the bash while loop\n def old_new_pairs = reads instanceof Path || reads.size() == 1 ? [[ reads, \"${prefix}.${reads.extension}\" ]] : reads.withIndex().collect { entry, index -> [ entry, \"${prefix}_${index + 1}.${entry.extension}\" ] }\n def rename_to = old_new_pairs*.join(' ').join(' ')\n def renamed_files = old_new_pairs.collect{ old_name, new_name -> new_name }.join(' ')\n \"\"\"\n printf \"%s %s\\\\n\" $rename_to | while read old_name new_name; do\n [ -f \"\\${new_name}\" ] || ln -s \\$old_name \\$new_name\n done\n\n fastqc \\\\\n $args \\\\\n --threads $task.cpus \\\\\n $renamed_files\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n fastqc: \\$( fastqc --version | sed -e \"s/FastQC v//g\" )\n END_VERSIONS\n \"\"\"\n\n stub:\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n touch ${prefix}.html\n touch ${prefix}.zip\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n fastqc: \\$( fastqc --version | sed -e \"s/FastQC v//g\" )\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/fastqc/meta.yml", "content": "name: fastqc\ndescription: Run FastQC on sequenced reads\nkeywords:\n - quality control\n - qc\n - adapters\n - fastq\ntools:\n - fastqc:\n description: |\n FastQC gives general quality metrics about your reads.\n It provides information about the quality score distribution\n across your reads, the per base sequence content (%A/C/G/T).\n You get information about adapter contamination and other\n overrepresented sequences.\n homepage: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/\n documentation: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/\n licence: [\"GPL-2.0-only\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - reads:\n type: file\n description: |\n List of input FastQ files of size 1 and 2 for single-end and paired-end data,\n respectively.\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - html:\n type: file\n description: FastQC report\n pattern: \"*_{fastqc.html}\"\n - zip:\n type: file\n description: FastQC report archive\n pattern: \"*_{fastqc.zip}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@grst\"\n - \"@ewels\"\n - \"@FelixKrueger\"\n" }, { "path": "modules/nf-core/gffread/main.nf", "content": "process GFFREAD {\n tag \"$gff\"\n label 'process_low'\n\n conda \"bioconda::gffread=0.12.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/gffread:0.12.1--h8b12597_0' :\n 'biocontainers/gffread:0.12.1--h8b12597_0' }\"\n\n input:\n path gff\n\n output:\n path \"*.gtf\" , emit: gtf\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${gff.baseName}\"\n \"\"\"\n gffread \\\\\n $gff \\\\\n $args \\\\\n -o ${prefix}.gtf\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n gffread: \\$(gffread --version 2>&1)\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/gffread/meta.yml", "content": "name: gffread\ndescription: Validate, filter, convert and perform various other operations on GFF files\nkeywords:\n - gff\n - conversion\n - validation\ntools:\n - gffread:\n description: GFF/GTF utility providing format conversions, region filtering, FASTA sequence extraction and more.\n homepage: http://ccb.jhu.edu/software/stringtie/gff.shtml#gffread\n documentation: http://ccb.jhu.edu/software/stringtie/gff.shtml#gffread\n tool_dev_url: https://github.com/gpertea/gffread\n doi: 10.12688/f1000research.23297.1\n licence: [\"MIT\"]\n\ninput:\n - gff:\n type: file\n description: A reference file in either the GFF3, GFF2 or GTF format.\n pattern: \"*.{gff, gtf}\"\n\noutput:\n - gtf:\n type: file\n description: GTF file resulting from the conversion of the GFF input file\n pattern: \"*.{gtf}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@emiller88\"\n" }, { "path": "modules/nf-core/gunzip/main.nf", "content": "process GUNZIP {\n tag \"$archive\"\n label 'process_single'\n\n conda \"conda-forge::sed=4.7\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/ubuntu:20.04' :\n 'nf-core/ubuntu:20.04' }\"\n\n input:\n tuple val(meta), path(archive)\n\n output:\n tuple val(meta), path(\"$gunzip\"), emit: gunzip\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n gunzip = archive.toString() - '.gz'\n \"\"\"\n # Not calling gunzip itself because it creates files\n # with the original group ownership rather than the\n # default one for that user / the work directory\n gzip \\\\\n -cd \\\\\n $args \\\\\n $archive \\\\\n > $gunzip\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n gunzip: \\$(echo \\$(gunzip --version 2>&1) | sed 's/^.*(gzip) //; s/ Copyright.*\\$//')\n END_VERSIONS\n \"\"\"\n\n stub:\n gunzip = archive.toString() - '.gz'\n \"\"\"\n touch $gunzip\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n gunzip: \\$(echo \\$(gunzip --version 2>&1) | sed 's/^.*(gzip) //; s/ Copyright.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/gunzip/meta.yml", "content": "name: gunzip\ndescription: Compresses and decompresses files.\nkeywords:\n - gunzip\n - compression\n - decompression\ntools:\n - gunzip:\n description: |\n gzip is a file format and a software application used for file compression and decompression.\n documentation: https://www.gnu.org/software/gzip/manual/gzip.html\n licence: [\"GPL-3.0-or-later\"]\ninput:\n - meta:\n type: map\n description: |\n Optional groovy Map containing meta information\n e.g. [ id:'test', single_end:false ]\n - archive:\n type: file\n description: File to be compressed/uncompressed\n pattern: \"*.*\"\noutput:\n - gunzip:\n type: file\n description: Compressed/uncompressed file\n pattern: \"*.*\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@joseespinosa\"\n - \"@drpatelh\"\n - \"@jfy133\"\n" }, { "path": "modules/nf-core/homer/annotatepeaks/main.nf", "content": "process HOMER_ANNOTATEPEAKS {\n tag \"$meta.id\"\n label 'process_medium'\n\n // WARN: Version information not provided by tool on CLI. Please update version string below when bumping container versions.\n conda \"bioconda::homer=4.11\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/homer:4.11--pl526hc9558a2_3' :\n 'biocontainers/homer:4.11--pl526hc9558a2_3' }\"\n\n input:\n tuple val(meta), path(peak)\n path fasta\n path gtf\n\n output:\n tuple val(meta), path(\"*annotatePeaks.txt\"), emit: txt\n tuple val(meta), path(\"*annStats.txt\"), emit: stats, optional: true\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def VERSION = '4.11' // WARN: Version information not provided by tool on CLI. Please update this string when bumping container versions.\n \"\"\"\n annotatePeaks.pl \\\\\n $peak \\\\\n $fasta \\\\\n $args \\\\\n -gtf $gtf \\\\\n -cpu $task.cpus \\\\\n > ${prefix}.annotatePeaks.txt\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n homer: $VERSION\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/homer/annotatepeaks/meta.yml", "content": "name: homer_annotatepeaks\ndescription: Annotate peaks with HOMER suite\nkeywords:\n - annotations\n - peaks\n - bed\ntools:\n - homer:\n description: |\n HOMER (Hypergeometric Optimization of Motif EnRichment) is a suite of tools for Motif Discovery and next-gen sequencing analysis.\n documentation: http://homer.ucsd.edu/homer/\n doi: 10.1016/j.molcel.2010.05.004.\n licence: [\"GPL-3.0-or-later\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - peaks:\n type: file\n description: The peak files in bed format\n pattern: \"*.bed\"\n - fasta:\n type: file\n description: Fasta file of reference genome\n pattern: \"*.fasta\"\n - gtf:\n type: file\n description: GTF file of reference genome\n pattern: \"*.gtf\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - annotated_peaks:\n type: file\n description: The annotated peaks\n pattern: \"*annotatePeaks.txt\"\n - annotation_stats:\n type: file\n description: the annStats file output from -annStats parameter\n pattern: \"*annStats.txt\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@kevinmenden\"\n" }, { "path": "modules/nf-core/khmer/uniquekmers/main.nf", "content": "process KHMER_UNIQUEKMERS {\n tag \"$fasta\"\n label 'process_low'\n\n conda \"bioconda::khmer=3.0.0a3\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/khmer:3.0.0a3--py37haa7609a_2' :\n 'biocontainers/khmer:3.0.0a3--py37haa7609a_2' }\"\n\n input:\n path fasta\n val kmer_size\n\n output:\n path \"report.txt\" , emit: report\n path \"kmers.txt\" , emit: kmers\n path \"versions.yml\", emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n \"\"\"\n unique-kmers.py \\\\\n -k $kmer_size \\\\\n -R report.txt \\\\\n $args \\\\\n $fasta\n\n grep ^number report.txt | sed 's/^.*:.[[:blank:]]//g' > kmers.txt\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n khmer: \\$( unique-kmers.py --version 2>&1 | grep ^khmer | sed 's/^khmer //;s/ .*\\$//' )\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/khmer/uniquekmers/meta.yml", "content": "name: \"khmer_uniquekmers\"\ndescription: In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more\nkeywords:\n - khmer\n - k-mer\n - effective genome size\n\ntools:\n - \"khmer\":\n description: khmer k-mer counting library\n homepage: https://github.com/dib-lab/khmer\n documentation: https://khmer.readthedocs.io/en/latest/\n tool_dev_url: https://github.com/dib-lab/khmer\n doi: \"10.12688/f1000research.6924.1\"\n licence: [\"BSD License\"]\n\ninput:\n - fasta:\n type: file\n description: fasta file\n pattern: \"*.{fa,fasta}\"\n - kmer_size:\n type: value\n description: k-mer size to use\n pattern: \"[0-9]+\"\n\noutput:\n - report:\n type: file\n description: Text file containing unique-kmers.py execution report\n pattern: \"report.txt\"\n - kmers:\n type: file\n description: Text file containing number of kmers\n pattern: \"kmers.txt\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@JoseEspinosa\"\n" }, { "path": "modules/nf-core/macs2/callpeak/main.nf", "content": "process MACS2_CALLPEAK {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::macs2=2.2.7.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/macs2:2.2.7.1--py38h4a8c8d9_3' :\n 'biocontainers/macs2:2.2.7.1--py38h4a8c8d9_3' }\"\n\n input:\n tuple val(meta), path(ipbam), path(controlbam)\n val macs2_gsize\n\n output:\n tuple val(meta), path(\"*.{narrowPeak,broadPeak}\"), emit: peak\n tuple val(meta), path(\"*.xls\") , emit: xls\n path \"versions.yml\" , emit: versions\n\n tuple val(meta), path(\"*.gappedPeak\"), optional:true, emit: gapped\n tuple val(meta), path(\"*.bed\") , optional:true, emit: bed\n tuple val(meta), path(\"*.bdg\") , optional:true, emit: bdg\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def args_list = args.tokenize()\n def format = meta.single_end ? 'BAM' : 'BAMPE'\n def control = controlbam ? \"--control $controlbam\" : ''\n if(args_list.contains('--format')){\n def id = args_list.findIndexOf{it=='--format'}\n format = args_list[id+1]\n args_list.remove(id+1)\n args_list.remove(id)\n }\n \"\"\"\n macs2 \\\\\n callpeak \\\\\n ${args_list.join(' ')} \\\\\n --gsize $macs2_gsize \\\\\n --format $format \\\\\n --name $prefix \\\\\n --treatment $ipbam \\\\\n $control\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n macs2: \\$(macs2 --version | sed -e \"s/macs2 //g\")\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/macs2/callpeak/meta.yml", "content": "name: macs2_callpeak\ndescription: Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments\nkeywords:\n - alignment\n - atac-seq\n - chip-seq\n - peak-calling\ntools:\n - macs2:\n description: Model Based Analysis for ChIP-Seq data\n\n documentation: https://docs.csc.fi/apps/macs2/\n tool_dev_url: https://github.com/macs3-project/MACS\n doi: \"10.1101/496521\"\n licence: [\"BSD\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - ipbam:\n type: file\n description: The ChIP-seq treatment file\n - controlbam:\n type: file\n description: The control file\n - macs2_gsize:\n type: string\n description: Effective genome size. It can be 1.0e+9 or 1000000000, or shortcuts:'hs' for human (2.7e9),\n 'mm' for mouse (1.87e9), 'ce' for C. elegans (9e7) and 'dm' for fruitfly (1.2e8)\n\noutput:\n - versions:\n type: file\n description: File containing software version\n pattern: \"versions.yml\"\n - peak:\n type: file\n description: BED file containing annotated peaks\n pattern: \"*.gappedPeak,*.narrowPeak}\"\n - xls:\n type: file\n description: xls file containing annotated peaks\n pattern: \"*.xls\"\n - gapped:\n type: file\n description: Optional BED file containing gapped peak\n pattern: \"*.gappedPeak\"\n - bed:\n type: file\n description: Optional BED file containing peak summits locations for every peak\n pattern: \"*.bed\"\n - bdg:\n type: file\n description: Optional bedGraph files for input and treatment input samples\n pattern: \"*.bdg\"\n\nauthors:\n - \"@ntoda03\"\n - \"@JoseEspinosa\"\n - \"@jianhong\"\n" }, { "path": "modules/nf-core/picard/collectmultiplemetrics/main.nf", "content": "process PICARD_COLLECTMULTIPLEMETRICS {\n tag \"$meta.id\"\n label 'process_single'\n\n conda \"bioconda::picard=3.0.0\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/picard:3.0.0--hdfd78af_1' :\n 'biocontainers/picard:3.0.0--hdfd78af_1' }\"\n\n input:\n tuple val(meta) , path(bam), path(bai)\n tuple val(meta2), path(fasta)\n tuple val(meta3), path(fai)\n\n output:\n tuple val(meta), path(\"*_metrics\"), emit: metrics\n tuple val(meta), path(\"*.pdf\") , emit: pdf\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def reference = fasta ? \"--REFERENCE_SEQUENCE ${fasta}\" : \"\"\n def avail_mem = 3072\n if (!task.memory) {\n log.info '[Picard CollectMultipleMetrics] Available memory not known - defaulting to 3GB. Specify process memory requirements to change this.'\n } else {\n avail_mem = (task.memory.mega*0.8).intValue()\n }\n \"\"\"\n picard \\\\\n -Xmx${avail_mem}M \\\\\n CollectMultipleMetrics \\\\\n $args \\\\\n --INPUT $bam \\\\\n --OUTPUT ${prefix}.CollectMultipleMetrics \\\\\n $reference\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n picard: \\$(picard CollectMultipleMetrics --version 2>&1 | grep -o 'Version.*' | cut -f2- -d:)\n END_VERSIONS\n \"\"\"\n\n stub:\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n touch ${prefix}.CollectMultipleMetrics.alignment_summary_metrics\n touch ${prefix}.CollectMultipleMetrics.insert_size_metrics\n touch ${prefix}.CollectMultipleMetrics.quality_distribution.pdf\n touch ${prefix}.CollectMultipleMetrics.base_distribution_by_cycle_metrics\n touch ${prefix}.CollectMultipleMetrics.quality_by_cycle_metrics\n touch ${prefix}.CollectMultipleMetrics.read_length_histogram.pdf\n touch ${prefix}.CollectMultipleMetrics.base_distribution_by_cycle.pdf\n touch ${prefix}.CollectMultipleMetrics.quality_by_cycle.pdf\n touch ${prefix}.CollectMultipleMetrics.insert_size_histogram.pdf\n touch ${prefix}.CollectMultipleMetrics.quality_distribution_metrics\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n picard: \\$(echo \\$(picard CollectMultipleMetrics --version 2>&1) | grep -o 'Version:.*' | cut -f2- -d:)\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/picard/collectmultiplemetrics/meta.yml", "content": "name: picard_collectmultiplemetrics\ndescription: Collect multiple metrics from a BAM file\nkeywords:\n - alignment\n - metrics\n - statistics\n - insert\n - quality\n - bam\ntools:\n - picard:\n description: |\n A set of command line tools (in Java) for manipulating high-throughput sequencing (HTS)\n data and formats such as SAM/BAM/CRAM and VCF.\n homepage: https://broadinstitute.github.io/picard/\n documentation: https://broadinstitute.github.io/picard/\n licence: [\"MIT\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: SAM/BAM/CRAM file\n pattern: \"*.{sam,bam,cram}\"\n - bai:\n type: file\n description: Optional SAM/BAM/CRAM file index\n pattern: \"*.{sai,bai,crai}\"\n - meta2:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'genome']\n - fasta:\n type: file\n description: Genome fasta file\n - meta3:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'genome']\n - fai:\n type: file\n description: Index of FASTA file. Only needed when fasta is supplied.\n pattern: \"*.fai\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - metrics:\n type: file\n description: Alignment metrics files generated by picard\n pattern: \"*_{metrics}\"\n - pdf:\n type: file\n description: PDF plots of metrics\n pattern: \"*.{pdf}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n" }, { "path": "modules/nf-core/picard/markduplicates/main.nf", "content": "process PICARD_MARKDUPLICATES {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::picard=3.0.0\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/picard:3.0.0--hdfd78af_1' :\n 'biocontainers/picard:3.0.0--hdfd78af_1' }\"\n\n input:\n tuple val(meta), path(bam)\n tuple val(meta2), path(fasta)\n tuple val(meta3), path(fai)\n\n output:\n tuple val(meta), path(\"*.bam\") , emit: bam\n tuple val(meta), path(\"*.bai\") , optional:true, emit: bai\n tuple val(meta), path(\"*.metrics.txt\"), emit: metrics\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def avail_mem = 3072\n if (!task.memory) {\n log.info '[Picard MarkDuplicates] Available memory not known - defaulting to 3GB. Specify process memory requirements to change this.'\n } else {\n avail_mem = (task.memory.mega*0.8).intValue()\n }\n \"\"\"\n picard \\\\\n -Xmx${avail_mem}M \\\\\n MarkDuplicates \\\\\n $args \\\\\n --INPUT $bam \\\\\n --OUTPUT ${prefix}.bam \\\\\n --REFERENCE_SEQUENCE $fasta \\\\\n --METRICS_FILE ${prefix}.MarkDuplicates.metrics.txt\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n picard: \\$(echo \\$(picard MarkDuplicates --version 2>&1) | grep -o 'Version:.*' | cut -f2- -d:)\n END_VERSIONS\n \"\"\"\n\n stub:\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n touch ${prefix}.bam\n touch ${prefix}.bam.bai\n touch ${prefix}.MarkDuplicates.metrics.txt\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n picard: \\$(echo \\$(picard MarkDuplicates --version 2>&1) | grep -o 'Version:.*' | cut -f2- -d:)\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/picard/markduplicates/meta.yml", "content": "name: picard_markduplicates\ndescription: Locate and tag duplicate reads in a BAM file\nkeywords:\n - markduplicates\n - pcr\n - duplicates\n - bam\n - sam\n - cram\ntools:\n - picard:\n description: |\n A set of command line tools (in Java) for manipulating high-throughput sequencing (HTS)\n data and formats such as SAM/BAM/CRAM and VCF.\n homepage: https://broadinstitute.github.io/picard/\n documentation: https://broadinstitute.github.io/picard/\n licence: [\"MIT\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM file\n pattern: \"*.{bam,cram,sam}\"\n - meta2:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'genome' ]\n - fasta:\n type: file\n description: Reference genome fasta file\n pattern: \"*.{fasta,fa}\"\n - meta3:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'genome' ]\n - fai:\n type: file\n description: Reference genome fasta index\n pattern: \"*.{fai}\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM file with duplicate reads marked/removed\n pattern: \"*.{bam}\"\n - bai:\n type: file\n description: An optional BAM index file. If desired, --CREATE_INDEX must be passed as a flag\n pattern: \"*.{bai}\"\n - metrics:\n type: file\n description: Duplicate metrics file generated by picard\n pattern: \"*.{metrics.txt}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@projectoriented\"\n - \"@ramprasadn\"\n" }, { "path": "modules/nf-core/picard/mergesamfiles/main.nf", "content": "process PICARD_MERGESAMFILES {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::picard=3.0.0\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/picard:3.0.0--hdfd78af_1' :\n 'biocontainers/picard:3.0.0--hdfd78af_1' }\"\n\n input:\n tuple val(meta), path(bams)\n\n output:\n tuple val(meta), path(\"*.bam\"), emit: bam\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def bam_files = bams.sort()\n def avail_mem = 3072\n if (!task.memory) {\n log.info '[Picard MergeSamFiles] Available memory not known - defaulting to 3GB. Specify process memory requirements to change this.'\n } else {\n avail_mem = (task.memory.mega*0.8).intValue()\n }\n if (bam_files.size() > 1) {\n \"\"\"\n picard \\\\\n -Xmx${avail_mem}M \\\\\n MergeSamFiles \\\\\n $args \\\\\n ${'--INPUT '+bam_files.join(' --INPUT ')} \\\\\n --OUTPUT ${prefix}.bam\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n picard: \\$( echo \\$(picard MergeSamFiles --version 2>&1) | grep -o 'Version:.*' | cut -f2- -d:)\n END_VERSIONS\n \"\"\"\n } else {\n \"\"\"\n ln -s ${bam_files[0]} ${prefix}.bam\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n picard: \\$( echo \\$(picard MergeSamFiles --version 2>&1) | grep -o 'Version:.*' | cut -f2- -d:)\n END_VERSIONS\n \"\"\"\n }\n}\n" }, { "path": "modules/nf-core/picard/mergesamfiles/meta.yml", "content": "name: picard_mergesamfiles\ndescription: Merges multiple BAM files into a single file\nkeywords:\n - merge\n - alignment\n - bam\n - sam\ntools:\n - picard:\n description: |\n A set of command line tools (in Java) for manipulating high-throughput sequencing (HTS)\n data and formats such as SAM/BAM/CRAM and VCF.\n homepage: https://broadinstitute.github.io/picard/\n documentation: https://broadinstitute.github.io/picard/\n licence: [\"MIT\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: List of BAM files\n pattern: \"*.{bam}\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: Merged BAM file\n pattern: \"*.{bam}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n" }, { "path": "modules/nf-core/preseq/lcextrap/main.nf", "content": "process PRESEQ_LCEXTRAP {\n tag \"$meta.id\"\n label 'process_single'\n label 'error_ignore'\n\n conda \"bioconda::preseq=3.1.2\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/preseq:3.1.2--h445547b_2':\n 'biocontainers/preseq:3.1.2--h445547b_2' }\"\n\n input:\n tuple val(meta), path(bam)\n\n output:\n tuple val(meta), path(\"*.lc_extrap.txt\"), emit: lc_extrap\n tuple val(meta), path(\"*.log\") , emit: log\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def paired_end = meta.single_end ? '' : '-pe'\n \"\"\"\n preseq \\\\\n lc_extrap \\\\\n $args \\\\\n $paired_end \\\\\n -output ${prefix}.lc_extrap.txt \\\\\n $bam\n cp .command.err ${prefix}.command.log\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n preseq: \\$(echo \\$(preseq 2>&1) | sed 's/^.*Version: //; s/Usage:.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/preseq/lcextrap/meta.yml", "content": "name: preseq_lcextrap\ndescription: Software for predicting library complexity and genome coverage in high-throughput sequencing\nkeywords:\n - preseq\n - library\n - complexity\ntools:\n - preseq:\n description: Software for predicting library complexity and genome coverage in high-throughput sequencing\n homepage: http://smithlabresearch.org/software/preseq/\n documentation: http://smithlabresearch.org/wp-content/uploads/manual.pdf\n tool_dev_url: https://github.com/smithlabcode/preseq\n\n licence: [\"GPL\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM/CRAM/SAM file\n pattern: \"*.{bam,cram,sam}\"\n\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n - lc_extrap:\n type: file\n description: File containing output of Preseq lcextrap\n pattern: \"*.{lc_extrap.txt}\"\n - log:\n type: file\n description: Log file containing stderr produced by Preseq\n pattern: \"*.{log}\"\n\nauthors:\n - \"@drpatelh\"\n - \"@Emiller88\"\n" }, { "path": "modules/nf-core/samtools/flagstat/main.nf", "content": "process SAMTOOLS_FLAGSTAT {\n tag \"$meta.id\"\n label 'process_single'\n\n conda \"bioconda::samtools=1.17\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/samtools:1.17--h00cdaf9_0' :\n 'biocontainers/samtools:1.17--h00cdaf9_0' }\"\n\n input:\n tuple val(meta), path(bam), path(bai)\n\n output:\n tuple val(meta), path(\"*.flagstat\"), emit: flagstat\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n samtools \\\\\n flagstat \\\\\n --threads ${task.cpus} \\\\\n $bam \\\\\n > ${prefix}.flagstat\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/samtools/flagstat/meta.yml", "content": "name: samtools_flagstat\ndescription: Counts the number of alignments in a BAM/CRAM/SAM file for each FLAG type\nkeywords:\n - stats\n - mapping\n - counts\n - bam\n - sam\n - cram\ntools:\n - samtools:\n description: |\n SAMtools is a set of utilities for interacting with and post-processing\n short DNA sequence read alignments in the SAM, BAM and CRAM formats, written by Heng Li.\n These files are generated as output by short read aligners like BWA.\n homepage: http://www.htslib.org/\n documentation: http://www.htslib.org/doc/samtools.html\n doi: 10.1093/bioinformatics/btp352\n licence: [\"MIT\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM/CRAM/SAM file\n pattern: \"*.{bam,cram,sam}\"\n - bai:\n type: file\n description: Index for BAM/CRAM/SAM file\n pattern: \"*.{bai,crai,sai}\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - flagstat:\n type: file\n description: File containing samtools flagstat output\n pattern: \"*.{flagstat}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n" }, { "path": "modules/nf-core/samtools/idxstats/main.nf", "content": "process SAMTOOLS_IDXSTATS {\n tag \"$meta.id\"\n label 'process_single'\n\n conda \"bioconda::samtools=1.17\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/samtools:1.17--h00cdaf9_0' :\n 'biocontainers/samtools:1.17--h00cdaf9_0' }\"\n\n input:\n tuple val(meta), path(bam), path(bai)\n\n output:\n tuple val(meta), path(\"*.idxstats\"), emit: idxstats\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n\n \"\"\"\n samtools \\\\\n idxstats \\\\\n --threads ${task.cpus-1} \\\\\n $bam \\\\\n > ${prefix}.idxstats\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/samtools/idxstats/meta.yml", "content": "name: samtools_idxstats\ndescription: Reports alignment summary statistics for a BAM/CRAM/SAM file\nkeywords:\n - stats\n - mapping\n - counts\n - chromosome\n - bam\n - sam\n - cram\ntools:\n - samtools:\n description: |\n SAMtools is a set of utilities for interacting with and post-processing\n short DNA sequence read alignments in the SAM, BAM and CRAM formats, written by Heng Li.\n These files are generated as output by short read aligners like BWA.\n homepage: http://www.htslib.org/\n documentation: http://www.htslib.org/doc/samtools.html\n doi: 10.1093/bioinformatics/btp352\n licence: [\"MIT\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM/CRAM/SAM file\n pattern: \"*.{bam,cram,sam}\"\n - bai:\n type: file\n description: Index for BAM/CRAM/SAM file\n pattern: \"*.{bai,crai,sai}\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - idxstats:\n type: file\n description: File containing samtools idxstats output\n pattern: \"*.{idxstats}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n" }, { "path": "modules/nf-core/samtools/index/main.nf", "content": "process SAMTOOLS_INDEX {\n tag \"$meta.id\"\n label 'process_low'\n\n conda \"bioconda::samtools=1.17\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/samtools:1.17--h00cdaf9_0' :\n 'biocontainers/samtools:1.17--h00cdaf9_0' }\"\n\n input:\n tuple val(meta), path(input)\n\n output:\n tuple val(meta), path(\"*.bai\") , optional:true, emit: bai\n tuple val(meta), path(\"*.csi\") , optional:true, emit: csi\n tuple val(meta), path(\"*.crai\"), optional:true, emit: crai\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n \"\"\"\n samtools \\\\\n index \\\\\n -@ ${task.cpus-1} \\\\\n $args \\\\\n $input\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n\n stub:\n \"\"\"\n touch ${input}.bai\n touch ${input}.crai\n touch ${input}.csi\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/samtools/index/meta.yml", "content": "name: samtools_index\ndescription: Index SAM/BAM/CRAM file\nkeywords:\n - index\n - bam\n - sam\n - cram\ntools:\n - samtools:\n description: |\n SAMtools is a set of utilities for interacting with and post-processing\n short DNA sequence read alignments in the SAM, BAM and CRAM formats, written by Heng Li.\n These files are generated as output by short read aligners like BWA.\n homepage: http://www.htslib.org/\n documentation: http://www.htslib.org/doc/samtools.html\n doi: 10.1093/bioinformatics/btp352\n licence: [\"MIT\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM/CRAM/SAM file\n pattern: \"*.{bam,cram,sam}\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bai:\n type: file\n description: BAM/CRAM/SAM index file\n pattern: \"*.{bai,crai,sai}\"\n - crai:\n type: file\n description: BAM/CRAM/SAM index file\n pattern: \"*.{bai,crai,sai}\"\n - csi:\n type: file\n description: CSI index file\n pattern: \"*.{csi}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@ewels\"\n - \"@maxulysse\"\n" }, { "path": "modules/nf-core/samtools/sort/main.nf", "content": "process SAMTOOLS_SORT {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::samtools=1.17\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/samtools:1.17--h00cdaf9_0' :\n 'biocontainers/samtools:1.17--h00cdaf9_0' }\"\n\n input:\n tuple val(meta), path(bam)\n\n output:\n tuple val(meta), path(\"*.bam\"), emit: bam\n tuple val(meta), path(\"*.csi\"), emit: csi, optional: true\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n if (\"$bam\" == \"${prefix}.bam\") error \"Input and output names are the same, use \\\"task.ext.prefix\\\" to disambiguate!\"\n \"\"\"\n samtools sort \\\\\n $args \\\\\n -@ $task.cpus \\\\\n -o ${prefix}.bam \\\\\n -T $prefix \\\\\n $bam\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n\n stub:\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n touch ${prefix}.bam\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/samtools/sort/meta.yml", "content": "name: samtools_sort\ndescription: Sort SAM/BAM/CRAM file\nkeywords:\n - sort\n - bam\n - sam\n - cram\ntools:\n - samtools:\n description: |\n SAMtools is a set of utilities for interacting with and post-processing\n short DNA sequence read alignments in the SAM, BAM and CRAM formats, written by Heng Li.\n These files are generated as output by short read aligners like BWA.\n homepage: http://www.htslib.org/\n documentation: http://www.htslib.org/doc/samtools.html\n doi: 10.1093/bioinformatics/btp352\n licence: [\"MIT\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM/CRAM/SAM file\n pattern: \"*.{bam,cram,sam}\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: Sorted BAM/CRAM/SAM file\n pattern: \"*.{bam,cram,sam}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n - csi:\n type: file\n description: BAM index file (optional)\n pattern: \"*.csi\"\nauthors:\n - \"@drpatelh\"\n - \"@ewels\"\n" }, { "path": "modules/nf-core/samtools/stats/main.nf", "content": "process SAMTOOLS_STATS {\n tag \"$meta.id\"\n label 'process_single'\n\n conda \"bioconda::samtools=1.17\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/samtools:1.17--h00cdaf9_0' :\n 'biocontainers/samtools:1.17--h00cdaf9_0' }\"\n\n input:\n tuple val(meta), path(input), path(input_index)\n tuple val(meta2), path(fasta)\n\n output:\n tuple val(meta), path(\"*.stats\"), emit: stats\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def reference = fasta ? \"--reference ${fasta}\" : \"\"\n \"\"\"\n samtools \\\\\n stats \\\\\n --threads ${task.cpus} \\\\\n ${reference} \\\\\n ${input} \\\\\n > ${prefix}.stats\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n\n stub:\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n \"\"\"\n touch ${prefix}.stats\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n samtools: \\$(echo \\$(samtools --version 2>&1) | sed 's/^.*samtools //; s/Using.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/samtools/stats/meta.yml", "content": "name: samtools_stats\ndescription: Produces comprehensive statistics from SAM/BAM/CRAM file\nkeywords:\n - statistics\n - counts\n - bam\n - sam\n - cram\ntools:\n - samtools:\n description: |\n SAMtools is a set of utilities for interacting with and post-processing\n short DNA sequence read alignments in the SAM, BAM and CRAM formats, written by Heng Li.\n These files are generated as output by short read aligners like BWA.\n homepage: http://www.htslib.org/\n documentation: http://www.htslib.org/doc/samtools.html\n doi: 10.1093/bioinformatics/btp352\n licence: [\"MIT\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - input:\n type: file\n description: BAM/CRAM file from alignment\n pattern: \"*.{bam,cram}\"\n - input_index:\n type: file\n description: BAI/CRAI file from alignment\n pattern: \"*.{bai,crai}\"\n - meta2:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'genome' ]\n - fasta:\n type: file\n description: Reference file the CRAM was created with (optional)\n pattern: \"*.{fasta,fa}\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - stats:\n type: file\n description: File containing samtools stats output\n pattern: \"*.{stats}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@FriederikeHanssen\"\n - \"@ramprasadn\"\n" }, { "path": "modules/nf-core/subread/featurecounts/main.nf", "content": "process SUBREAD_FEATURECOUNTS {\n tag \"$meta.id\"\n label 'process_medium'\n\n conda \"bioconda::subread=2.0.1\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/subread:2.0.1--hed695b0_0' :\n 'biocontainers/subread:2.0.1--hed695b0_0' }\"\n\n input:\n tuple val(meta), path(bams), path(annotation)\n\n output:\n tuple val(meta), path(\"*featureCounts.txt\") , emit: counts\n tuple val(meta), path(\"*featureCounts.txt.summary\"), emit: summary\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def paired_end = meta.single_end ? '' : '-p'\n\n def strandedness = 0\n if (meta.strandedness == 'forward') {\n strandedness = 1\n } else if (meta.strandedness == 'reverse') {\n strandedness = 2\n }\n \"\"\"\n featureCounts \\\\\n $args \\\\\n $paired_end \\\\\n -T $task.cpus \\\\\n -a $annotation \\\\\n -s $strandedness \\\\\n -o ${prefix}.featureCounts.txt \\\\\n ${bams.join(' ')}\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n subread: \\$( echo \\$(featureCounts -v 2>&1) | sed -e \"s/featureCounts v//g\")\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/subread/featurecounts/meta.yml", "content": "name: subread_featurecounts\ndescription: Count reads that map to genomic features\nkeywords:\n - counts\n - fasta\n - genome\n - reference\n\ntools:\n - featurecounts:\n description: featureCounts is a highly efficient general-purpose read summarization program that counts mapped reads for genomic features such as genes, exons, promoter, gene bodies, genomic bins and chromosomal locations. It can be used to count both RNA-seq and genomic DNA-seq reads.\n homepage: http://bioinf.wehi.edu.au/featureCounts/\n documentation: http://bioinf.wehi.edu.au/subread-package/SubreadUsersGuide.pdf\n doi: \"10.1093/bioinformatics/btt656\"\n licence: [\"GPL v3\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM/SAM file containing read alignments\n pattern: \"*.{bam}\"\n - annotation:\n type: file\n description: Genomic features annotation in GTF or SAF\n pattern: \"*.{gtf,saf}\"\n\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - counts:\n type: file\n description: Counts of reads mapping to features\n pattern: \"*featureCounts.txt\"\n - summary:\n type: file\n description: Summary log file\n pattern: \"*.featureCounts.txt.summary\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@ntoda03\"\n" }, { "path": "modules/nf-core/trimgalore/main.nf", "content": "process TRIMGALORE {\n tag \"$meta.id\"\n label 'process_high'\n\n conda \"bioconda::trim-galore=0.6.7\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/trim-galore:0.6.7--hdfd78af_0' :\n 'biocontainers/trim-galore:0.6.7--hdfd78af_0' }\"\n\n input:\n tuple val(meta), path(reads)\n\n output:\n tuple val(meta), path(\"*{3prime,5prime,trimmed,val}*.fq.gz\"), emit: reads\n tuple val(meta), path(\"*report.txt\") , emit: log , optional: true\n tuple val(meta), path(\"*unpaired*.fq.gz\") , emit: unpaired, optional: true\n tuple val(meta), path(\"*.html\") , emit: html , optional: true\n tuple val(meta), path(\"*.zip\") , emit: zip , optional: true\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n // Calculate number of --cores for TrimGalore based on value of task.cpus\n // See: https://github.com/FelixKrueger/TrimGalore/blob/master/Changelog.md#version-060-release-on-1-mar-2019\n // See: https://github.com/nf-core/atacseq/pull/65\n def cores = 1\n if (task.cpus) {\n cores = (task.cpus as int) - 4\n if (meta.single_end) cores = (task.cpus as int) - 3\n if (cores < 1) cores = 1\n if (cores > 8) cores = 8\n }\n\n // Added soft-links to original fastqs for consistent naming in MultiQC\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n if (meta.single_end) {\n def args_list = args.split(\"\\\\s(?=--)\").toList()\n args_list.removeAll { it.toLowerCase().contains('_r2 ') }\n \"\"\"\n [ ! -f ${prefix}.fastq.gz ] && ln -s $reads ${prefix}.fastq.gz\n trim_galore \\\\\n ${args_list.join(' ')} \\\\\n --cores $cores \\\\\n --gzip \\\\\n ${prefix}.fastq.gz\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n trimgalore: \\$(echo \\$(trim_galore --version 2>&1) | sed 's/^.*version //; s/Last.*\\$//')\n cutadapt: \\$(cutadapt --version)\n END_VERSIONS\n \"\"\"\n } else {\n \"\"\"\n [ ! -f ${prefix}_1.fastq.gz ] && ln -s ${reads[0]} ${prefix}_1.fastq.gz\n [ ! -f ${prefix}_2.fastq.gz ] && ln -s ${reads[1]} ${prefix}_2.fastq.gz\n trim_galore \\\\\n $args \\\\\n --cores $cores \\\\\n --paired \\\\\n --gzip \\\\\n ${prefix}_1.fastq.gz \\\\\n ${prefix}_2.fastq.gz\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n trimgalore: \\$(echo \\$(trim_galore --version 2>&1) | sed 's/^.*version //; s/Last.*\\$//')\n cutadapt: \\$(cutadapt --version)\n END_VERSIONS\n \"\"\"\n }\n}\n" }, { "path": "modules/nf-core/trimgalore/meta.yml", "content": "name: trimgalore\ndescription: Trim FastQ files using Trim Galore!\nkeywords:\n - trimming\n - adapters\n - sequencing adapters\n - fastq\ntools:\n - trimgalore:\n description: |\n A wrapper tool around Cutadapt and FastQC to consistently apply quality\n and adapter trimming to FastQ files, with some extra functionality for\n MspI-digested RRBS-type (Reduced Representation Bisufite-Seq) libraries.\n homepage: https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/\n documentation: https://github.com/FelixKrueger/TrimGalore/blob/master/Docs/Trim_Galore_User_Guide.md\n licence: [\"GPL-3.0-or-later\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - reads:\n type: file\n description: |\n List of input FastQ files of size 1 and 2 for single-end and paired-end data,\n respectively.\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - reads:\n type: file\n description: |\n List of input adapter trimmed FastQ files of size 1 and 2 for\n single-end and paired-end data, respectively.\n pattern: \"*{3prime,5prime,trimmed,val}*.fq.gz\"\n - unpaired:\n type: file\n description: |\n FastQ files containing unpaired reads from read 1 or read 2\n pattern: \"*unpaired*.fq.gz\"\n - html:\n type: file\n description: FastQC report (optional)\n pattern: \"*_{fastqc.html}\"\n - zip:\n type: file\n description: FastQC report archive (optional)\n pattern: \"*_{fastqc.zip}\"\n - log:\n type: file\n description: Trim Galore! trimming report\n pattern: \"*_{report.txt}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@ewels\"\n - \"@FelixKrueger\"\n" }, { "path": "modules/nf-core/ucsc/bedgraphtobigwig/main.nf", "content": "process UCSC_BEDGRAPHTOBIGWIG {\n tag \"$meta.id\"\n label 'process_single'\n\n // WARN: Version information not provided by tool on CLI. Please update version string below when bumping container versions.\n conda \"bioconda::ucsc-bedgraphtobigwig=445\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/ucsc-bedgraphtobigwig:445--h954228d_0' :\n 'biocontainers/ucsc-bedgraphtobigwig:445--h954228d_0' }\"\n\n input:\n tuple val(meta), path(bedgraph)\n path sizes\n\n output:\n tuple val(meta), path(\"*.bigWig\"), emit: bigwig\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def VERSION = '445' // WARN: Version information not provided by tool on CLI. Please update this string when bumping container versions.\n \"\"\"\n bedGraphToBigWig \\\\\n $bedgraph \\\\\n $sizes \\\\\n ${prefix}.bigWig\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n ucsc: $VERSION\n END_VERSIONS\n \"\"\"\n\n stub:\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n def VERSION = '445' // WARN: Version information not provided by tool on CLI. Please update this string when bumping container versions.\n \"\"\"\n touch ${prefix}.bigWig\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n ucsc: $VERSION\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/ucsc/bedgraphtobigwig/meta.yml", "content": "name: ucsc_bedgraphtobigwig\ndescription: Convert a bedGraph file to bigWig format.\nkeywords:\n - bedgraph\n - bigwig\n - ucsc\n - bedgraphtobigwig\n - converter\ntools:\n - ucsc:\n description: Convert a bedGraph file to bigWig format.\n homepage: http://hgdownload.cse.ucsc.edu/admin/exe/\n documentation: https://genome.ucsc.edu/goldenPath/help/bigWig.html\n licence: [\"varies; see http://genome.ucsc.edu/license\"]\n\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bedgraph:\n type: file\n description: bedGraph file\n pattern: \"*.{bedGraph}\"\n - sizes:\n type: file\n description: chromosome sizes file\n pattern: \"*.{sizes}\"\n\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n - bigwig:\n type: file\n description: bigWig file\n pattern: \"*.{bigWig}\"\n\nauthors:\n - \"@drpatelh\"\n" }, { "path": "modules/nf-core/umitools/extract/main.nf", "content": "process UMITOOLS_EXTRACT {\n tag \"$meta.id\"\n label \"process_single\"\n label \"process_long\"\n\n conda \"bioconda::umi_tools=1.1.4\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/umi_tools:1.1.4--py38hbff2b2d_1' :\n 'biocontainers/umi_tools:1.1.4--py38hbff2b2d_1' }\"\n\n input:\n tuple val(meta), path(reads)\n\n output:\n tuple val(meta), path(\"*.fastq.gz\"), emit: reads\n tuple val(meta), path(\"*.log\") , emit: log\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def prefix = task.ext.prefix ?: \"${meta.id}\"\n if (meta.single_end) {\n \"\"\"\n umi_tools \\\\\n extract \\\\\n -I $reads \\\\\n -S ${prefix}.umi_extract.fastq.gz \\\\\n $args \\\\\n > ${prefix}.umi_extract.log\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n umitools: \\$(umi_tools --version 2>&1 | sed 's/^.*UMI-tools version://; s/ *\\$//')\n END_VERSIONS\n \"\"\"\n } else {\n \"\"\"\n umi_tools \\\\\n extract \\\\\n -I ${reads[0]} \\\\\n --read2-in=${reads[1]} \\\\\n -S ${prefix}.umi_extract_1.fastq.gz \\\\\n --read2-out=${prefix}.umi_extract_2.fastq.gz \\\\\n $args \\\\\n > ${prefix}.umi_extract.log\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n umitools: \\$(umi_tools --version 2>&1 | sed 's/^.*UMI-tools version://; s/ *\\$//')\n END_VERSIONS\n \"\"\"\n }\n}\n" }, { "path": "modules/nf-core/umitools/extract/meta.yml", "content": "name: umitools_extract\ndescription: Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place\nkeywords:\n - umitools\n - extract\ntools:\n - umi_tools:\n description: >\n UMI-tools contains tools for dealing with Unique Molecular Identifiers (UMIs)/Random Molecular Tags (RMTs)\n and single cell RNA-Seq cell barcodes\n documentation: https://umi-tools.readthedocs.io/en/latest/\n license: [\"MIT\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - reads:\n type: list\n description: |\n List of input FASTQ files whose UMIs will be extracted.\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - reads:\n type: file\n description: >\n Extracted FASTQ files. |\n For single-end reads, pattern is \\${prefix}.umi_extract.fastq.gz. |\n For paired-end reads, pattern is \\${prefix}.umi_extract_{1,2}.fastq.gz.\n pattern: \"*.{fastq.gz}\"\n - log:\n type: file\n description: Logfile for umi_tools\n pattern: \"*.{log}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n\nauthors:\n - \"@drpatelh\"\n - \"@grst\"\n" }, { "path": "modules/nf-core/untar/main.nf", "content": "process UNTAR {\n tag \"$archive\"\n label 'process_single'\n\n conda \"conda-forge::sed=4.7 bioconda::grep=3.4 conda-forge::tar=1.34\"\n container \"${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?\n 'https://depot.galaxyproject.org/singularity/ubuntu:20.04' :\n 'nf-core/ubuntu:20.04' }\"\n\n input:\n tuple val(meta), path(archive)\n\n output:\n tuple val(meta), path(\"$prefix\"), emit: untar\n path \"versions.yml\" , emit: versions\n\n when:\n task.ext.when == null || task.ext.when\n\n script:\n def args = task.ext.args ?: ''\n def args2 = task.ext.args2 ?: ''\n prefix = task.ext.prefix ?: ( meta.id ? \"${meta.id}\" : archive.baseName.toString().replaceFirst(/\\.tar$/, \"\"))\n\n \"\"\"\n mkdir $prefix\n\n ## Ensures --strip-components only applied when top level of tar contents is a directory\n ## If just files or multiple directories, place all in prefix\n if [[ \\$(tar -taf ${archive} | grep -o -P \"^.*?\\\\/\" | uniq | wc -l) -eq 1 ]]; then\n tar \\\\\n -C $prefix --strip-components 1 \\\\\n -xavf \\\\\n $args \\\\\n $archive \\\\\n $args2\n else\n tar \\\\\n -C $prefix \\\\\n -xavf \\\\\n $args \\\\\n $archive \\\\\n $args2\n fi\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n untar: \\$(echo \\$(tar --version 2>&1) | sed 's/^.*(GNU tar) //; s/ Copyright.*\\$//')\n END_VERSIONS\n \"\"\"\n\n stub:\n prefix = task.ext.prefix ?: ( meta.id ? \"${meta.id}\" : archive.toString().replaceFirst(/\\.[^\\.]+(.gz)?$/, \"\"))\n \"\"\"\n mkdir $prefix\n touch ${prefix}/file.txt\n\n cat <<-END_VERSIONS > versions.yml\n \"${task.process}\":\n untar: \\$(echo \\$(tar --version 2>&1) | sed 's/^.*(GNU tar) //; s/ Copyright.*\\$//')\n END_VERSIONS\n \"\"\"\n}\n" }, { "path": "modules/nf-core/untar/meta.yml", "content": "name: untar\ndescription: Extract files.\nkeywords:\n - untar\n - uncompress\n - extract\ntools:\n - untar:\n description: |\n Extract tar.gz files.\n documentation: https://www.gnu.org/software/tar/manual/\n licence: [\"GPL-3.0-or-later\"]\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - archive:\n type: file\n description: File to be untar\n pattern: \"*.{tar}.{gz}\"\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - untar:\n type: directory\n description: Directory containing contents of archive\n pattern: \"*/\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@joseespinosa\"\n - \"@drpatelh\"\n - \"@matthdsm\"\n - \"@jfy133\"\n" }, { "path": "modules.json", "content": "{\n \"name\": \"nf-core/atacseq\",\n \"homePage\": \"https://github.com/nf-core/atacseq\",\n \"repos\": {\n \"https://github.com/nf-core/modules.git\": {\n \"modules\": {\n \"nf-core\": {\n \"ataqv/ataqv\": {\n \"branch\": \"master\",\n \"git_sha\": \"11c7e5b3073845889060c793786bf3177275d62e\",\n \"installed_by\": [\"modules\"]\n },\n \"ataqv/mkarv\": {\n \"branch\": \"master\",\n \"git_sha\": \"11c7e5b3073845889060c793786bf3177275d62e\",\n \"installed_by\": [\"modules\"]\n },\n \"bowtie2/align\": {\n \"branch\": \"master\",\n \"git_sha\": \"fe54581f8bed20e4c4a51c616c93fd3379d89820\",\n \"installed_by\": [\"fastq_align_bowtie2\"]\n },\n \"bowtie2/build\": {\n \"branch\": \"master\",\n \"git_sha\": \"6a24fbe314bb2e6fe6306c29a63076ea87e8eb3c\",\n \"installed_by\": [\"modules\"]\n },\n \"bwa/index\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"bwa/mem\": {\n \"branch\": \"master\",\n \"git_sha\": \"603ecbd9f45300c9788f197d2a15a005685b4220\",\n \"installed_by\": [\"fastq_align_bwa\"]\n },\n \"chromap/chromap\": {\n \"branch\": \"master\",\n \"git_sha\": \"603ecbd9f45300c9788f197d2a15a005685b4220\",\n \"installed_by\": [\"fastq_align_chromap\"]\n },\n \"chromap/index\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"custom/dumpsoftwareversions\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"custom/getchromsizes\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"deeptools/computematrix\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"deeptools/plotfingerprint\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"deeptools/plotheatmap\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"deeptools/plotprofile\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"fastqc\": {\n \"branch\": \"master\",\n \"git_sha\": \"bd8092b67b5103bdd52e300f75889442275c3117\",\n \"installed_by\": [\"fastq_fastqc_umitools_trimgalore\"]\n },\n \"gffread\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"gunzip\": {\n \"branch\": \"master\",\n \"git_sha\": \"e06548bfa36ee31869b81041879dd6b3a83b1d57\",\n \"installed_by\": [\"modules\"]\n },\n \"homer/annotatepeaks\": {\n \"branch\": \"master\",\n \"git_sha\": \"ffc27c68870f5f67e541bb67d94e03c597f75257\",\n \"installed_by\": [\"modules\"]\n },\n \"khmer/uniquekmers\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"macs2/callpeak\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"picard/collectmultiplemetrics\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"picard/markduplicates\": {\n \"branch\": \"master\",\n \"git_sha\": \"735e1e04e7e01751d2d6e97055bbdb6f70683cc1\",\n \"installed_by\": [\"bam_markduplicates_picard\"]\n },\n \"picard/mergesamfiles\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"preseq/lcextrap\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"samtools/flagstat\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"bam_stats_samtools\"]\n },\n \"samtools/idxstats\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"bam_stats_samtools\"]\n },\n \"samtools/index\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"bam_markduplicates_picard\", \"bam_sort_stats_samtools\"]\n },\n \"samtools/sort\": {\n \"branch\": \"master\",\n \"git_sha\": \"a0f7be95788366c1923171e358da7d049eb440f9\",\n \"installed_by\": [\"bam_sort_stats_samtools\"]\n },\n \"samtools/stats\": {\n \"branch\": \"master\",\n \"git_sha\": \"735e1e04e7e01751d2d6e97055bbdb6f70683cc1\",\n \"installed_by\": [\"bam_stats_samtools\"]\n },\n \"subread/featurecounts\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"modules\"]\n },\n \"trimgalore\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"fastq_fastqc_umitools_trimgalore\"]\n },\n \"ucsc/bedgraphtobigwig\": {\n \"branch\": \"master\",\n \"git_sha\": \"66290981ab6038ea86177ade40b9449bc790b0ce\",\n \"installed_by\": [\"modules\"]\n },\n \"umitools/extract\": {\n \"branch\": \"master\",\n \"git_sha\": \"911696ea0b62df80e900ef244d7867d177971f73\",\n \"installed_by\": [\"fastq_fastqc_umitools_trimgalore\"]\n },\n \"untar\": {\n \"branch\": \"master\",\n \"git_sha\": \"5c460c5a4736974abde2843294f35307ee2b0e5e\",\n \"installed_by\": [\"modules\"]\n }\n }\n },\n \"subworkflows\": {\n \"nf-core\": {\n \"bam_markduplicates_picard\": {\n \"branch\": \"master\",\n \"git_sha\": \"a9784afdd5dcda23b84e64db75dc591065d64653\",\n \"installed_by\": [\"subworkflows\"]\n },\n \"bam_sort_stats_samtools\": {\n \"branch\": \"master\",\n \"git_sha\": \"735e1e04e7e01751d2d6e97055bbdb6f70683cc1\",\n \"installed_by\": [\"fastq_align_bowtie2\", \"fastq_align_bwa\", \"fastq_align_chromap\"]\n },\n \"bam_stats_samtools\": {\n \"branch\": \"master\",\n \"git_sha\": \"735e1e04e7e01751d2d6e97055bbdb6f70683cc1\",\n \"installed_by\": [\"bam_markduplicates_picard\", \"bam_sort_stats_samtools\"]\n },\n \"fastq_align_bowtie2\": {\n \"branch\": \"master\",\n \"git_sha\": \"fe54581f8bed20e4c4a51c616c93fd3379d89820\",\n \"installed_by\": [\"subworkflows\"]\n },\n \"fastq_align_bwa\": {\n \"branch\": \"master\",\n \"git_sha\": \"a9784afdd5dcda23b84e64db75dc591065d64653\",\n \"installed_by\": [\"subworkflows\"]\n },\n \"fastq_align_chromap\": {\n \"branch\": \"master\",\n \"git_sha\": \"735e1e04e7e01751d2d6e97055bbdb6f70683cc1\",\n \"installed_by\": [\"subworkflows\"]\n },\n \"fastq_fastqc_umitools_trimgalore\": {\n \"branch\": \"master\",\n \"git_sha\": \"a9784afdd5dcda23b84e64db75dc591065d64653\",\n \"installed_by\": [\"subworkflows\"]\n }\n }\n }\n }\n }\n}\n" }, { "path": "nextflow.config", "content": "/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n nf-core/atacseq Nextflow config file\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Default config options for all compute environments\n----------------------------------------------------------------------------------------\n*/\n\n// Global default params, used in configs\nparams {\n // Input options\n input = null\n seq_center = null\n fragment_size = 200\n fingerprint_bins = 500000\n read_length = null\n with_control = false\n\n\n // References\n genome = null\n igenomes_base = 's3://ngi-igenomes/igenomes'\n igenomes_ignore = false\n save_reference = false\n ataqv_mito_reference = null\n\n // Options: Trimming\n clip_r1 = null\n clip_r2 = null\n three_prime_clip_r1 = null\n three_prime_clip_r2 = null\n trim_nextseq = null\n skip_trimming = false\n save_trimmed = false\n min_trimmed_reads = 10000\n\n // Options: Alignment\n aligner = 'bwa'\n bwa_min_score = null\n keep_mito = false\n keep_dups = false\n keep_multi_map = false\n skip_merge_replicates = false\n save_align_intermeds = false\n save_unaligned = false\n\n // Options: Peaks\n narrow_peak = false\n broad_cutoff = 0.1\n macs_fdr = null\n macs_pvalue = null\n min_reps_consensus = 1\n save_macs_pileup = false\n skip_peak_qc = false\n skip_peak_annotation = false\n skip_consensus_peaks = false\n\n // Options: DESeq2 QC\n deseq2_vst = true\n skip_deseq2_qc = false\n\n // Options: QC\n skip_qc = false\n skip_fastqc = false\n skip_picard_metrics = false\n skip_preseq = true\n skip_plot_profile = false\n skip_plot_fingerprint = false\n skip_ataqv = false\n skip_igv = false\n skip_multiqc = false\n\n // Options: Config\n bamtools_filter_pe_config = \"$projectDir/assets/bamtools_filter_pe.json\"\n bamtools_filter_se_config = \"$projectDir/assets/bamtools_filter_se.json\"\n\n // MultiQC options\n multiqc_config = null\n multiqc_title = null\n multiqc_logo = null\n max_multiqc_email_size = '25.MB'\n multiqc_methods_description = null\n\n // Boilerplate options\n outdir = null\n publish_dir_mode = 'copy'\n email = null\n email_on_fail = null\n plaintext_email = false\n monochrome_logs = false\n hook_url = null\n help = false\n version = false\n\n // Config options\n config_profile_name = null\n config_profile_description = null\n custom_config_version = 'master'\n custom_config_base = \"https://raw.githubusercontent.com/nf-core/configs/${params.custom_config_version}\"\n config_profile_contact = null\n config_profile_url = null\n\n // Max resource options\n // Defaults only, expecting to be overwritten\n max_memory = '128.GB'\n max_cpus = 16\n max_time = '240.h'\n\n // Schema validation default options\n validationFailUnrecognisedParams = false\n validationLenientMode = false\n validationSchemaIgnoreParams = 'genomes'\n validationShowHiddenParams = false\n validate_params = true\n\n}\n\n// Load base.config by default for all pipelines\nincludeConfig 'conf/base.config'\n\n// Load nf-core custom profiles from different Institutions\ntry {\n includeConfig \"${params.custom_config_base}/nfcore_custom.config\"\n} catch (Exception e) {\n System.err.println(\"WARNING: Could not load nf-core/config profiles: ${params.custom_config_base}/nfcore_custom.config\")\n}\n\n// Load nf-core/atacseq custom profiles from different institutions.\n// Warning: Uncomment only if a pipeline-specific instititutional config already exists on nf-core/configs!\n// try {\n// includeConfig \"${params.custom_config_base}/pipeline/atacseq.config\"\n// } catch (Exception e) {\n// System.err.println(\"WARNING: Could not load nf-core/config/atacseq profiles: ${params.custom_config_base}/pipeline/atacseq.config\")\n// }\n\nprofiles {\n debug {\n dumpHashes = true\n process.beforeScript = 'echo $HOSTNAME'\n cleanup = false\n }\n conda {\n conda.enabled = true\n docker.enabled = false\n singularity.enabled = false\n podman.enabled = false\n shifter.enabled = false\n charliecloud.enabled = false\n apptainer.enabled = false\n }\n mamba {\n conda.enabled = true\n conda.useMamba = true\n docker.enabled = false\n singularity.enabled = false\n podman.enabled = false\n shifter.enabled = false\n charliecloud.enabled = false\n apptainer.enabled = false\n }\n docker {\n docker.enabled = true\n docker.userEmulation = true\n conda.enabled = false\n singularity.enabled = false\n podman.enabled = false\n shifter.enabled = false\n charliecloud.enabled = false\n apptainer.enabled = false\n }\n arm {\n docker.runOptions = '-u $(id -u):$(id -g) --platform=linux/amd64'\n }\n singularity {\n singularity.enabled = true\n singularity.autoMounts = true\n conda.enabled = false\n docker.enabled = false\n podman.enabled = false\n shifter.enabled = false\n charliecloud.enabled = false\n apptainer.enabled = false\n }\n podman {\n podman.enabled = true\n conda.enabled = false\n docker.enabled = false\n singularity.enabled = false\n shifter.enabled = false\n charliecloud.enabled = false\n apptainer.enabled = false\n }\n shifter {\n shifter.enabled = true\n conda.enabled = false\n docker.enabled = false\n singularity.enabled = false\n podman.enabled = false\n charliecloud.enabled = false\n apptainer.enabled = false\n }\n charliecloud {\n charliecloud.enabled = true\n conda.enabled = false\n docker.enabled = false\n singularity.enabled = false\n podman.enabled = false\n shifter.enabled = false\n apptainer.enabled = false\n }\n apptainer {\n apptainer.enabled = true\n conda.enabled = false\n docker.enabled = false\n singularity.enabled = false\n podman.enabled = false\n shifter.enabled = false\n charliecloud.enabled = false\n }\n gitpod {\n executor.name = 'local'\n executor.cpus = 16\n executor.memory = 60.GB\n }\n test { includeConfig 'conf/test.config' }\n test_controls { includeConfig 'conf/test_controls.config' }\n test_full { includeConfig 'conf/test_full.config' }\n}\n\n// Set default registry for Apptainer, Docker, Podman and Singularity independent of -profile\n// Will not be used unless Apptainer / Docker / Podman / Singularity are enabled\n// Set to your registry if you have a mirror of containers\napptainer.registry = 'quay.io'\ndocker.registry = 'quay.io'\npodman.registry = 'quay.io'\nsingularity.registry = 'quay.io'\n\n// Nextflow plugins\nplugins {\n id 'nf-validation' // Validation of pipeline parameters and creation of an input channel from a sample sheet\n}\n\n// Load igenomes.config if required\nif (!params.igenomes_ignore) {\n includeConfig 'conf/igenomes.config'\n} else {\n params.genomes = [:]\n}\n\n// Export these variables to prevent local Python/R libraries from conflicting with those in the container\n// The JULIA depot path has been adjusted to a fixed path `/usr/local/share/julia` that needs to be used for packages in the container.\n// See https://apeltzer.github.io/post/03-julia-lang-nextflow/ for details on that. Once we have a common agreement on where to keep Julia packages, this is adjustable.\n\nenv {\n PYTHONNOUSERSITE = 1\n R_PROFILE_USER = \"/.Rprofile\"\n R_ENVIRON_USER = \"/.Renviron\"\n JULIA_DEPOT_PATH = \"/usr/local/share/julia\"\n}\n\n// Capture exit codes from upstream processes when piping\nprocess.shell = ['/bin/bash', '-euo', 'pipefail']\n\ndef trace_timestamp = new java.util.Date().format( 'yyyy-MM-dd_HH-mm-ss')\ntimeline {\n enabled = true\n file = \"${params.outdir}/pipeline_info/execution_timeline_${trace_timestamp}.html\"\n}\nreport {\n enabled = true\n file = \"${params.outdir}/pipeline_info/execution_report_${trace_timestamp}.html\"\n}\ntrace {\n enabled = true\n file = \"${params.outdir}/pipeline_info/execution_trace_${trace_timestamp}.txt\"\n}\ndag {\n enabled = true\n file = \"${params.outdir}/pipeline_info/pipeline_dag_${trace_timestamp}.html\"\n}\n\nmanifest {\n name = 'nf-core/atacseq'\n author = \"\"\"Patel H, Langer B, Espinosa-Carrasco J, Syme R\"\"\"\n homePage = 'https://github.com/nf-core/atacseq'\n description = \"\"\"ATACSeq peak-calling and differential analysis pipeline.\"\"\"\n mainScript = 'main.nf'\n nextflowVersion = '!>=23.04.0'\n version = '2.1.2'\n doi = 'https://doi.org/10.5281/zenodo.2634132'\n}\n\n// Load modules.config for DSL2 module specific options\nincludeConfig 'conf/modules.config'\n\n// Function to ensure that resource requirements don't go beyond\n// a maximum limit\ndef check_max(obj, type) {\n if (type == 'memory') {\n try {\n if (obj.compareTo(params.max_memory as nextflow.util.MemoryUnit) == 1)\n return params.max_memory as nextflow.util.MemoryUnit\n else\n return obj\n } catch (all) {\n println \" ### ERROR ### Max memory '${params.max_memory}' is not valid! Using default value: $obj\"\n return obj\n }\n } else if (type == 'time') {\n try {\n if (obj.compareTo(params.max_time as nextflow.util.Duration) == 1)\n return params.max_time as nextflow.util.Duration\n else\n return obj\n } catch (all) {\n println \" ### ERROR ### Max time '${params.max_time}' is not valid! Using default value: $obj\"\n return obj\n }\n } else if (type == 'cpus') {\n try {\n return Math.min( obj, params.max_cpus as int )\n } catch (all) {\n println \" ### ERROR ### Max cpus '${params.max_cpus}' is not valid! Using default value: $obj\"\n return obj\n }\n }\n}\n" }, { "path": "nextflow_schema.json", "content": "{\n \"$schema\": \"http://json-schema.org/draft-07/schema\",\n \"$id\": \"https://raw.githubusercontent.com/nf-core/atacseq/master/nextflow_schema.json\",\n \"title\": \"nf-core/atacseq pipeline parameters\",\n \"description\": \"ATACSeq peak-calling and differential analysis pipeline.\",\n \"type\": \"object\",\n \"definitions\": {\n \"input_output_options\": {\n \"title\": \"Input/output options\",\n \"type\": \"object\",\n \"fa_icon\": \"fas fa-terminal\",\n \"description\": \"Define where the pipeline should find input data and save output data.\",\n \"required\": [\"input\", \"outdir\"],\n \"properties\": {\n \"input\": {\n \"type\": \"string\",\n \"format\": \"file-path\",\n \"exists\": true,\n \"mimetype\": \"text/csv\",\n \"pattern\": \"^\\\\S+\\\\.csv$\",\n \"description\": \"Path to comma-separated file containing information about the samples in the experiment.\",\n \"help_text\": \"You will need to create a samplesheet with information about the samples in your experiment before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 5 columns, and a header row. See [usage docs](https://nf-co.re/atacseq/docs/usage#introduction).\",\n \"fa_icon\": \"fas fa-file-csv\"\n },\n \"fragment_size\": {\n \"type\": \"integer\",\n \"description\": \"Estimated fragment size used to extend single-end reads.\",\n \"fa_icon\": \"fas fa-chart-area\",\n \"default\": 200\n },\n \"seq_center\": {\n \"type\": \"string\",\n \"description\": \"Sequencing center information to be added to read group of BAM files.\",\n \"fa_icon\": \"fas fa-synagogue\"\n },\n \"read_length\": {\n \"type\": \"integer\",\n \"description\": \"Read length used to calculate or retrieve pre-computed MACS2 genome size for peak calling if `--macs_gsize` isn't provided.\",\n \"fa_icon\": \"fas fa-chart-area\",\n \"help_text\": \"Read length together with the genome fasta are used to calculate MACS2 genome size using the `khmer` program as explained [here](https://deeptools.readthedocs.io/en/develop/content/feature/effectiveGenomeSize.html#effective-genome-size). For all the genomes present in the `igenomes.config` the genome size has been already precomputed and the read length is then used to retrieve the corresponding value\",\n \"enum\": [50, 75, 100, 150, 200]\n },\n \"with_control\": {\n \"type\": \"boolean\",\n \"description\": \"Use controls.\",\n \"help_text\": \"Use this to indicate that your samplesheet lists controls.\",\n \"fa_icon\": \"fas fa-check-square\"\n },\n \"outdir\": {\n \"type\": \"string\",\n \"format\": \"directory-path\",\n \"description\": \"The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.\",\n \"fa_icon\": \"fas fa-folder-open\"\n },\n \"email\": {\n \"type\": \"string\",\n \"description\": \"Email address for completion summary.\",\n \"fa_icon\": \"fas fa-envelope\",\n \"help_text\": \"Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits. If set in your user config file (`~/.nextflow/config`) then you don't need to specify this on the command line for every run.\",\n \"pattern\": \"^([a-zA-Z0-9_\\\\-\\\\.]+)@([a-zA-Z0-9_\\\\-\\\\.]+)\\\\.([a-zA-Z]{2,5})$\"\n },\n \"multiqc_title\": {\n \"type\": \"string\",\n \"description\": \"MultiQC report title. Printed as page header, used for filename if not otherwise specified.\",\n \"fa_icon\": \"fas fa-file-signature\"\n }\n }\n },\n \"reference_genome_options\": {\n \"title\": \"Reference genome options\",\n \"type\": \"object\",\n \"fa_icon\": \"fas fa-dna\",\n \"description\": \"Reference genome related files and options required for the workflow.\",\n \"properties\": {\n \"genome\": {\n \"type\": \"string\",\n \"description\": \"Name of iGenomes reference.\",\n \"fa_icon\": \"fas fa-book\",\n \"help_text\": \"If using a reference genome configured in the pipeline using iGenomes, use this parameter to give the ID for the reference. This is then used to build the full paths for all required reference genome files e.g. `--genome GRCh38`. \\n\\nSee the [nf-core website docs](https://nf-co.re/usage/reference_genomes) for more details.\"\n },\n \"fasta\": {\n \"type\": \"string\",\n \"format\": \"file-path\",\n \"exists\": true,\n \"mimetype\": \"text/plain\",\n \"pattern\": \"^\\\\S+\\\\.fn?a(sta)?(\\\\.gz)?$\",\n \"description\": \"Path to FASTA genome file.\",\n \"help_text\": \"This parameter is *mandatory* if `--genome` is not specified. If you don't have the appropriate alignment index available this will be generated for you automatically. Combine with `--save_reference` to save alignment index for future runs.\",\n \"fa_icon\": \"far fa-file-code\"\n },\n \"gtf\": {\n \"type\": \"string\",\n \"format\": \"file-path\",\n \"exists\": true,\n \"mimetype\": \"text/plain\",\n \"pattern\": \"^\\\\S+\\\\.gtf(\\\\.gz)?$\",\n \"description\": \"Path to GTF annotation file.\",\n \"fa_icon\": \"fas fa-code-branch\",\n \"help_text\": \"This parameter is *mandatory* if `--genome` is not specified.\"\n },\n \"gff\": {\n \"type\": \"string\",\n \"format\": \"file-path\",\n \"exists\": true,\n \"mimetype\": \"text/plain\",\n \"pattern\": \"^\\\\S+\\\\.gff(\\\\.gz)?$\",\n \"fa_icon\": \"fas fa-code-branch\",\n \"description\": \"Path to GFF3 annotation file.\",\n \"help_text\": \"This parameter must be specified if `--genome` or `--gtf` are not specified.\"\n },\n \"bwa_index\": {\n \"type\": \"string\",\n \"format\": \"path\",\n \"exists\": true,\n \"description\": \"Path to directory or tar.gz archive for pre-built BWA index.\",\n \"fa_icon\": \"fas fa-bezier-curve\"\n },\n \"bowtie2_index\": {\n \"type\": \"string\",\n \"format\": \"path\",\n \"exists\": true,\n \"fa_icon\": \"fas fa-bezier-curve\",\n \"description\": \"Path to directory or tar.gz archive for pre-built Bowtie2 index.\"\n },\n \"chromap_index\": {\n \"type\": \"string\",\n \"format\": \"path\",\n \"exists\": true,\n \"fa_icon\": \"fas fa-bezier-curve\",\n \"description\": \"Path to directory or tar.gz archive for pre-built Chromap index.\"\n },\n \"star_index\": {\n \"type\": \"string\",\n \"format\": \"path\",\n \"exists\": true,\n \"fa_icon\": \"fas fa-bezier-curve\",\n \"description\": \"Path to directory or tar.gz archive for pre-built STAR index.\"\n },\n \"gene_bed\": {\n \"type\": \"string\",\n \"format\": \"file-path\",\n \"exists\": true,\n \"mimetype\": \"text/plain\",\n \"pattern\": \"^\\\\S+\\\\.bed(\\\\.gz)?$\",\n \"fa_icon\": \"fas fa-procedures\",\n \"description\": \"Path to BED file containing gene intervals. This will be created from the GTF file if not specified.\"\n },\n \"tss_bed\": {\n \"type\": \"string\",\n \"format\": \"file-path\",\n \"exists\": true,\n \"mimetype\": \"text/plain\",\n \"pattern\": \"^\\\\S+\\\\.bed(\\\\.gz)?$\",\n \"fa_icon\": \"fas fa-procedures\",\n \"description\": \"Path to BED file containing transcription start sites. This will be created from the gene BED file if not specified.\"\n },\n \"macs_gsize\": {\n \"type\": \"number\",\n \"description\": \"Effective genome size parameter required by MACS2.\",\n \"help_text\": \"[Effective genome size](https://github.com/taoliu/MACS#-g--gsize) parameter required by MACS2. If using an iGenomes reference these have been provided when `--genome` is set as *GRCh37*, *GRCh38*, *GRCm38*, *WBcel235*, *BDGP6*, *R64-1-1*, *EF2*, *hg38*, *hg19* and *mm10*. For other genomes, if this parameter is not specified then the MACS2 peak-calling and differential analysis will be skipped.\",\n \"fa_icon\": \"fas fa-arrows-alt-h\"\n },\n \"blacklist\": {\n \"type\": \"string\",\n \"format\": \"path\",\n \"exists\": true,\n \"description\": \"Path to blacklist regions in BED format, used for filtering alignments.\",\n \"help_text\": \"If provided, alignments that overlap with the regions in this file will be filtered out (see [ENCODE blacklists](https://sites.google.com/site/anshulkundaje/projects/blacklists)). The file should be in BED format. Blacklisted regions for *GRCh37*, *GRCh38*, *GRCm38*, *hg19*, *hg38*, *mm10* are bundled with the pipeline in the [`blacklists`](../assets/blacklists/) directory, and as such will be automatically used if any of those genomes are specified with the `--genome` parameter.\",\n \"fa_icon\": \"fas fa-book-dead\"\n },\n \"mito_name\": {\n \"type\": \"string\",\n \"description\": \"Name of Mitochondrial chomosome in reference assembly e.g. chrM.\",\n \"help_text\": \"Reads aligning to this contig are filtered out if a valid identifier is provided otherwise this step is skipped. Where possible these have been provided in the [`igenomes.config`](../conf/igenomes.config).\",\n \"fa_icon\": \"fas fa-signature\"\n },\n \"save_reference\": {\n \"type\": \"boolean\",\n \"description\": \"If generated by the pipeline save the aligner index (e.g. BWA) in the results directory.\",\n \"help_text\": \"If the index generated by the aligner is generated by the pipeline use this parameter to save it to your results folder. These can then be used for future pipeline runs, reducing processing times.\",\n \"fa_icon\": \"fas fa-save\"\n },\n \"igenomes_base\": {\n \"type\": \"string\",\n \"format\": \"directory-path\",\n \"description\": \"Directory / URL base for iGenomes references.\",\n \"default\": \"s3://ngi-igenomes/igenomes\",\n \"fa_icon\": \"fas fa-cloud-download-alt\",\n \"hidden\": true\n },\n \"igenomes_ignore\": {\n \"type\": \"boolean\",\n \"description\": \"Do not load the iGenomes reference config.\",\n \"fa_icon\": \"fas fa-ban\",\n \"hidden\": true,\n \"help_text\": \"Do not load `igenomes.config` when running the pipeline. You may choose this option if you observe clashes between custom parameters and those supplied in `igenomes.config`.\"\n },\n \"keep_mito\": {\n \"type\": \"boolean\",\n \"description\": \"Reads mapping to mitochondrial contig are not filtered from alignments.\",\n \"fa_icon\": \"fas fa-cart-arrow-down\",\n \"default\": false\n },\n \"ataqv_mito_reference\": {\n \"type\": \"string\",\n \"description\": \"Sets the value of the ataqv --mitochondrial-reference-name argument\",\n \"help_text\": \"By default takes the value of the mito_name parameter, if set. However, some plants and algae have chloroplast genomes in addition to a mitochondrial genome and thus mito_name can have values as multiple names that are separated by a | symbol that will break ataqv, in these cases this parameter can be used to overwrite these values.\",\n \"fa_icon\": \"fas fa-signature\"\n }\n }\n },\n \"adapter_trimming_options\": {\n \"title\": \"Adapter trimming options\",\n \"type\": \"object\",\n \"fa_icon\": \"fas fa-cut\",\n \"description\": \"Options to adjust adapter trimming criteria.\",\n \"properties\": {\n \"clip_r1\": {\n \"type\": \"integer\",\n \"description\": \"Instructs Trim Galore to remove bp from the 5' end of read 1 (or single-end reads).\",\n \"fa_icon\": \"fas fa-cut\"\n },\n \"clip_r2\": {\n \"type\": \"integer\",\n \"description\": \"Instructs Trim Galore to remove bp from the 5' end of read 2 (paired-end reads only).\",\n \"fa_icon\": \"fas fa-cut\"\n },\n \"three_prime_clip_r1\": {\n \"type\": \"integer\",\n \"description\": \"Instructs Trim Galore to remove bp from the 3' end of read 1 AFTER adapter/quality trimming has been performed.\",\n \"fa_icon\": \"fas fa-cut\"\n },\n \"three_prime_clip_r2\": {\n \"type\": \"integer\",\n \"description\": \"Instructs Trim Galore to remove bp from the 3' end of read 2 AFTER adapter/quality trimming has been performed.\",\n \"fa_icon\": \"fas fa-cut\"\n },\n \"trim_nextseq\": {\n \"type\": \"integer\",\n \"description\": \"Instructs Trim Galore to apply the --nextseq=X option, to trim based on quality after removing poly-G tails.\",\n \"help_text\": \"This enables the option Cutadapt `--nextseq-trim=3'CUTOFF` option via Trim Galore, which will set a quality cutoff (that is normally given with -q instead), but qualities of G bases are ignored. This trimming is in common for the NextSeq- and NovaSeq-platforms, where basecalls without any signal are called as high-quality G bases.\",\n \"fa_icon\": \"fas fa-cut\"\n },\n \"min_trimmed_reads\": {\n \"type\": \"integer\",\n \"default\": 10000,\n \"fa_icon\": \"fas fa-hand-paper\",\n \"description\": \"Minimum number of trimmed reads below which samples are removed from further processing. Some downstream steps in the pipeline will fail if this threshold is too low.\"\n },\n \"skip_trimming\": {\n \"type\": \"boolean\",\n \"description\": \"Skip the adapter trimming step.\",\n \"help_text\": \"Use this if your input FastQ files have already been trimmed outside of the workflow or if you're very confident that there is no adapter contamination in your data.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n },\n \"save_trimmed\": {\n \"type\": \"boolean\",\n \"description\": \"Save the trimmed FastQ files in the results directory.\",\n \"help_text\": \"By default, trimmed FastQ files will not be saved to the results directory. Specify this flag (or set to true in your config file) to copy these files to the results directory when complete.\",\n \"fa_icon\": \"fas fa-save\"\n }\n }\n },\n \"alignment_options\": {\n \"title\": \"Alignment options\",\n \"type\": \"object\",\n \"fa_icon\": \"fas fa-map-signs\",\n \"description\": \"Options to adjust parameters and filtering criteria for read alignments.\",\n \"properties\": {\n \"aligner\": {\n \"type\": \"string\",\n \"default\": \"bwa\",\n \"description\": \"Specifies the alignment algorithm to use - available options are 'bwa', 'bowtie2', 'chromap' and 'star'.\",\n \"fa_icon\": \"fas fa-map-signs\",\n \"enum\": [\"bwa\", \"bowtie2\", \"chromap\", \"star\"]\n },\n \"keep_dups\": {\n \"type\": \"boolean\",\n \"description\": \"Duplicate reads are not filtered from alignments.\",\n \"fa_icon\": \"fas fa-cart-arrow-down\"\n },\n \"keep_multi_map\": {\n \"type\": \"boolean\",\n \"description\": \"Reads mapping to multiple locations are not filtered from alignments.\",\n \"fa_icon\": \"fas fa-cart-arrow-down\"\n },\n \"bwa_min_score\": {\n \"type\": \"integer\",\n \"description\": \"Don\\u2019t output BWA MEM alignments with score lower than this parameter.\",\n \"fa_icon\": \"fas fa-hand-paper\"\n },\n \"skip_merge_replicates\": {\n \"type\": \"boolean\",\n \"default\": false,\n \"description\": \"Do not perform alignment merging and downstream analysis by merging replicates i.e. only do this by merging resequenced libraries.\",\n \"help_text\": \"An additional series of steps are performed by the pipeline for merging the replicates from the same experimental group. This is primarily to increase the sequencing depth in order to perform downstream analyses such as footprinting. Specifying this parameter means that these steps will not be performed.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n },\n \"save_align_intermeds\": {\n \"type\": \"boolean\",\n \"description\": \"Save the intermediate BAM files from the alignment step.\",\n \"help_text\": \"By default, intermediate BAM files will not be saved. The final BAM files created after the appropriate filtering step are always saved to limit storage usage. Set this parameter to also save other intermediate BAM files.\",\n \"fa_icon\": \"fas fa-save\"\n },\n \"save_unaligned\": {\n \"type\": \"boolean\",\n \"fa_icon\": \"fas fa-save\",\n \"description\": \"Where possible, save unaligned reads from either STAR, HISAT2 or Salmon to the results directory.\",\n \"help_text\": \"This may either be in the form of FastQ or BAM files depending on the options available for that particular tool.\"\n },\n \"bamtools_filter_pe_config\": {\n \"type\": \"string\",\n \"format\": \"path\",\n \"exists\": true,\n \"default\": \"$projectDir/assets/bamtools_filter_pe.json\",\n \"hidden\": true,\n \"description\": \"BAMTools JSON file with custom filters for paired-end data.\",\n \"fa_icon\": \"fas fa-cog\"\n },\n \"bamtools_filter_se_config\": {\n \"type\": \"string\",\n \"format\": \"path\",\n \"exists\": true,\n \"default\": \"$projectDir/assets/bamtools_filter_se.json\",\n \"hidden\": true,\n \"description\": \"BAMTools JSON file with custom filters for single-end data.\",\n \"fa_icon\": \"fas fa-cog\"\n }\n }\n },\n \"peak_calling_options\": {\n \"title\": \"Peak calling options\",\n \"type\": \"object\",\n \"fa_icon\": \"fas fa-chart-area\",\n \"description\": \"Options to adjust peak calling criteria.\",\n \"properties\": {\n \"narrow_peak\": {\n \"type\": \"boolean\",\n \"description\": \"Run MACS2 in narrowPeak mode.\",\n \"help_text\": \"MACS2 is run by default with the [`--broad`](https://github.com/taoliu/MACS#--broad) flag. Specify this flag to call peaks in narrowPeak mode.\",\n \"fa_icon\": \"fas fa-arrows-alt-h\"\n },\n \"broad_cutoff\": {\n \"type\": \"number\",\n \"default\": 0.1,\n \"description\": \"Specifies broad cutoff value for MACS2. Only used when --narrow_peak isnt specified.\",\n \"fa_icon\": \"fas fa-hand-scissors\"\n },\n \"macs_fdr\": {\n \"type\": \"number\",\n \"description\": \"Minimum FDR (q-value) cutoff for peak detection, --macs_fdr and --macs_pvalue are mutually exclusive.\",\n \"fa_icon\": \"fas fa-sort-amount-down\"\n },\n \"macs_pvalue\": {\n \"type\": \"number\",\n \"description\": \"p-value cutoff for peak detection, --macs_fdr and --macs_pvalue are mutually exclusive. If --macs_pvalue cutoff is set, q-value will not be calculated and reported as -1 in the final .xls file.\",\n \"fa_icon\": \"fas fa-sort-amount-down\"\n },\n \"min_reps_consensus\": {\n \"type\": \"integer\",\n \"default\": 1,\n \"description\": \"Number of biological replicates required from a given condition for a peak to contribute to a consensus peak.\",\n \"help_text\": \"If you are confident you have good reproducibility amongst your replicates then you can increase the value of this parameter to create a 'reproducible' set of consensus peaks. For example, a value of 2 will mean peaks that have been called in at least 2 replicates will contribute to the consensus set of peaks, and as such peaks that are unique to a given replicate will be discarded.\",\n \"fa_icon\": \"fas fa-sort-numeric-down\"\n },\n \"save_macs_pileup\": {\n \"type\": \"boolean\",\n \"description\": \"Instruct MACS2 to create bedGraph files normalised to signal per million reads.\",\n \"fa_icon\": \"fas fa-save\"\n },\n \"skip_peak_qc\": {\n \"type\": \"boolean\",\n \"fa_icon\": \"fas fa-fast-forward\",\n \"description\": \"Skip MACS2 peak QC plot generation.\"\n },\n \"skip_peak_annotation\": {\n \"type\": \"boolean\",\n \"fa_icon\": \"fas fa-fast-forward\",\n \"description\": \"Skip annotation of MACS2 and consensus peaks with HOMER.\"\n },\n \"skip_consensus_peaks\": {\n \"type\": \"boolean\",\n \"description\": \"Skip consensus peak generation, annotation and counting.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n }\n }\n },\n \"deseq_qc_options\": {\n \"title\": \"Differential analysis options\",\n \"type\": \"object\",\n \"fa_icon\": \"fas fa-not-equal\",\n \"description\": \"Options to adjust differential analysis criteria.\",\n \"properties\": {\n \"deseq2_vst\": {\n \"type\": \"boolean\",\n \"description\": \"Use vst transformation instead of rlog with DESeq2.\",\n \"help_text\": \"See [DESeq2 docs](http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#data-transformations-and-visualization).\",\n \"fa_icon\": \"fas fa-dolly\",\n \"default\": true\n },\n \"skip_deseq2_qc\": {\n \"type\": \"boolean\",\n \"fa_icon\": \"fas fa-fast-forward\",\n \"description\": \"Skip DESeq2 PCA and heatmap plotting.\"\n }\n }\n },\n \"process_skipping_options\": {\n \"title\": \"Process skipping options\",\n \"type\": \"object\",\n \"fa_icon\": \"fas fa-fast-forward\",\n \"description\": \"Options to skip various steps within the workflow.\",\n \"properties\": {\n \"skip_fastqc\": {\n \"type\": \"boolean\",\n \"description\": \"Skip FastQC.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n },\n \"skip_picard_metrics\": {\n \"type\": \"boolean\",\n \"description\": \"Skip Picard CollectMultipleMetrics.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n },\n \"skip_preseq\": {\n \"type\": \"boolean\",\n \"description\": \"Skip Preseq.\",\n \"fa_icon\": \"fas fa-fast-forward\",\n \"default\": true\n },\n \"skip_plot_profile\": {\n \"type\": \"boolean\",\n \"description\": \"Skip deepTools plotProfile.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n },\n \"skip_plot_fingerprint\": {\n \"type\": \"boolean\",\n \"description\": \"Skip deepTools plotFingerprint.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n },\n \"skip_igv\": {\n \"type\": \"boolean\",\n \"description\": \"Skip IGV.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n },\n \"skip_multiqc\": {\n \"type\": \"boolean\",\n \"description\": \"Skip MultiQC.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n },\n \"skip_qc\": {\n \"type\": \"boolean\",\n \"fa_icon\": \"fas fa-fast-forward\",\n \"description\": \"Skip all QC steps except for MultiQC.\"\n },\n \"skip_ataqv\": {\n \"type\": \"boolean\",\n \"default\": false,\n \"description\": \"Skip Ataqv.\",\n \"fa_icon\": \"fas fa-fast-forward\"\n }\n }\n },\n \"institutional_config_options\": {\n \"title\": \"Institutional config options\",\n \"type\": \"object\",\n \"fa_icon\": \"fas fa-university\",\n \"description\": \"Parameters used to describe centralised config profiles. These should not be edited.\",\n \"help_text\": \"The centralised nf-core configuration profiles use a handful of pipeline parameters to describe themselves. This information is then printed to the Nextflow log when you run a pipeline. You should not need to change these values when you run a pipeline.\",\n \"properties\": {\n \"custom_config_version\": {\n \"type\": \"string\",\n \"description\": \"Git commit id for Institutional configs.\",\n \"default\": \"master\",\n \"hidden\": true,\n \"fa_icon\": \"fas fa-users-cog\"\n },\n \"custom_config_base\": {\n \"type\": \"string\",\n \"description\": \"Base directory for Institutional configs.\",\n \"default\": \"https://raw.githubusercontent.com/nf-core/configs/master\",\n \"hidden\": true,\n \"help_text\": \"If you're running offline, Nextflow will not be able to fetch the institutional config files from the internet. If you don't need them, then this is not a problem. If you do need them, you should download the files from the repo and tell Nextflow where to find them with this parameter.\",\n \"fa_icon\": \"fas fa-users-cog\"\n },\n \"config_profile_name\": {\n \"type\": \"string\",\n \"description\": \"Institutional config name.\",\n \"hidden\": true,\n \"fa_icon\": \"fas fa-users-cog\"\n },\n \"config_profile_description\": {\n \"type\": \"string\",\n \"description\": \"Institutional config description.\",\n \"hidden\": true,\n \"fa_icon\": \"fas fa-users-cog\"\n },\n \"config_profile_contact\": {\n \"type\": \"string\",\n \"description\": \"Institutional config contact information.\",\n \"hidden\": true,\n \"fa_icon\": \"fas fa-users-cog\"\n },\n \"config_profile_url\": {\n \"type\": \"string\",\n \"description\": \"Institutional config URL link.\",\n \"hidden\": true,\n \"fa_icon\": \"fas fa-users-cog\"\n }\n }\n },\n \"max_job_request_options\": {\n \"title\": \"Max job request options\",\n \"type\": \"object\",\n \"fa_icon\": \"fab fa-acquisitions-incorporated\",\n \"description\": \"Set the top limit for requested resources for any single job.\",\n \"help_text\": \"If you are running on a smaller system, a pipeline step requesting more resources than are available may cause the Nextflow to stop the run with an error. These options allow you to cap the maximum resources requested by any single job so that the pipeline will run on your system.\\n\\nNote that you can not _increase_ the resources requested by any job using these options. For that you will need your own configuration file. See [the nf-core website](https://nf-co.re/usage/configuration) for details.\",\n \"properties\": {\n \"max_cpus\": {\n \"type\": \"integer\",\n \"description\": \"Maximum number of CPUs that can be requested for any single job.\",\n \"default\": 16,\n \"fa_icon\": \"fas fa-microchip\",\n \"hidden\": true,\n \"help_text\": \"Use to set an upper-limit for the CPU requirement for each process. Should be an integer e.g. `--max_cpus 1`\"\n },\n \"max_memory\": {\n \"type\": \"string\",\n \"description\": \"Maximum amount of memory that can be requested for any single job.\",\n \"default\": \"128.GB\",\n \"fa_icon\": \"fas fa-memory\",\n \"pattern\": \"^\\\\d+(\\\\.\\\\d+)?\\\\.?\\\\s*(K|M|G|T)?B$\",\n \"hidden\": true,\n \"help_text\": \"Use to set an upper-limit for the memory requirement for each process. Should be a string in the format integer-unit e.g. `--max_memory '8.GB'`\"\n },\n \"max_time\": {\n \"type\": \"string\",\n \"description\": \"Maximum amount of time that can be requested for any single job.\",\n \"default\": \"240.h\",\n \"fa_icon\": \"far fa-clock\",\n \"pattern\": \"^(\\\\d+\\\\.?\\\\s*(s|m|h|d|day)\\\\s*)+$\",\n \"hidden\": true,\n \"help_text\": \"Use to set an upper-limit for the time requirement for each process. Should be a string in the format integer-unit e.g. `--max_time '2.h'`\"\n }\n }\n },\n \"generic_options\": {\n \"title\": \"Generic options\",\n \"type\": \"object\",\n \"fa_icon\": \"fas fa-file-import\",\n \"description\": \"Less common options for the pipeline, typically set in a config file.\",\n \"help_text\": \"These options are common to all nf-core pipelines and allow you to customise some of the core preferences for how the pipeline runs.\\n\\nTypically these options would be set in a Nextflow config file loaded for all pipeline runs, such as `~/.nextflow/config`.\",\n \"properties\": {\n \"help\": {\n \"type\": \"boolean\",\n \"description\": \"Display help text.\",\n \"fa_icon\": \"fas fa-question-circle\",\n \"hidden\": true\n },\n \"version\": {\n \"type\": \"boolean\",\n \"description\": \"Display version and exit.\",\n \"fa_icon\": \"fas fa-question-circle\",\n \"hidden\": true\n },\n \"publish_dir_mode\": {\n \"type\": \"string\",\n \"default\": \"copy\",\n \"description\": \"Method used to save pipeline results to output directory.\",\n \"help_text\": \"The Nextflow `publishDir` option specifies which intermediate files should be saved to the output directory. This option tells the pipeline what method should be used to move these files. See [Nextflow docs](https://www.nextflow.io/docs/latest/process.html#publishdir) for details.\",\n \"fa_icon\": \"fas fa-copy\",\n \"enum\": [\"symlink\", \"rellink\", \"link\", \"copy\", \"copyNoFollow\", \"move\"],\n \"hidden\": true\n },\n \"fingerprint_bins\": {\n \"type\": \"integer\",\n \"default\": 500000,\n \"description\": \"Number of genomic bins to use when calculating deepTools fingerprint plot.\",\n \"fa_icon\": \"fas fa-dumpster\",\n \"hidden\": true\n },\n \"email_on_fail\": {\n \"type\": \"string\",\n \"description\": \"Email address for completion summary, only when pipeline fails.\",\n \"fa_icon\": \"fas fa-exclamation-triangle\",\n \"pattern\": \"^([a-zA-Z0-9_\\\\-\\\\.]+)@([a-zA-Z0-9_\\\\-\\\\.]+)\\\\.([a-zA-Z]{2,5})$\",\n \"help_text\": \"An email address to send a summary email to when the pipeline is completed - ONLY sent if the pipeline does not exit successfully.\",\n \"hidden\": true\n },\n \"plaintext_email\": {\n \"type\": \"boolean\",\n \"description\": \"Send plain-text email instead of HTML.\",\n \"fa_icon\": \"fas fa-remove-format\",\n \"hidden\": true\n },\n \"max_multiqc_email_size\": {\n \"type\": \"string\",\n \"description\": \"File size limit when attaching MultiQC reports to summary emails.\",\n \"pattern\": \"^\\\\d+(\\\\.\\\\d+)?\\\\.?\\\\s*(K|M|G|T)?B$\",\n \"default\": \"25.MB\",\n \"fa_icon\": \"fas fa-file-upload\",\n \"hidden\": true\n },\n \"monochrome_logs\": {\n \"type\": \"boolean\",\n \"description\": \"Do not use coloured log outputs.\",\n \"fa_icon\": \"fas fa-palette\",\n \"hidden\": true\n },\n \"hook_url\": {\n \"type\": \"string\",\n \"description\": \"Incoming hook URL for messaging service\",\n \"fa_icon\": \"fas fa-people-group\",\n \"help_text\": \"Incoming hook URL for messaging service. Currently, MS Teams and Slack are supported.\",\n \"hidden\": true\n },\n \"multiqc_config\": {\n \"type\": \"string\",\n \"format\": \"file-path\",\n \"exists\": true,\n \"mimetype\": \"text/plain\",\n \"description\": \"Custom config file to supply to MultiQC.\",\n \"fa_icon\": \"fas fa-cog\",\n \"hidden\": true\n },\n \"multiqc_logo\": {\n \"type\": \"string\",\n \"format\": \"file-path\",\n \"exists\": true,\n \"mimetype\": \"text/plain\",\n \"description\": \"Custom logo file to supply to MultiQC. File name must also be set in the MultiQC config file\",\n \"fa_icon\": \"fas fa-image\",\n \"hidden\": true\n },\n \"multiqc_methods_description\": {\n \"type\": \"string\",\n \"format\": \"file-path\",\n \"exists\": true,\n \"mimetype\": \"text/plain\",\n \"description\": \"Custom MultiQC yaml file containing HTML including a methods description.\",\n \"fa_icon\": \"fas fa-cog\"\n },\n \"validate_params\": {\n \"type\": \"boolean\",\n \"description\": \"Boolean whether to validate parameters against the schema at runtime\",\n \"default\": true,\n \"fa_icon\": \"fas fa-check-square\",\n \"hidden\": true\n },\n \"validationShowHiddenParams\": {\n \"type\": \"boolean\",\n \"fa_icon\": \"far fa-eye-slash\",\n \"description\": \"Show all params when using `--help`\",\n \"default\": false,\n \"hidden\": true,\n \"help_text\": \"By default, parameters set as _hidden_ in the schema are not shown on the command line when a user runs with `--help`. Specifying this option will tell the pipeline to show all parameters.\"\n },\n \"validationFailUnrecognisedParams\": {\n \"type\": \"boolean\",\n \"fa_icon\": \"far fa-check-circle\",\n \"description\": \"Validation of parameters fails when an unrecognised parameter is found.\",\n \"hidden\": true,\n \"help_text\": \"By default, when an unrecognised parameter is found, it returns a warinig.\"\n },\n \"validationLenientMode\": {\n \"type\": \"boolean\",\n \"fa_icon\": \"far fa-check-circle\",\n \"description\": \"Validation of parameters in lenient more.\",\n \"default\": false,\n \"hidden\": true,\n \"help_text\": \"Allows string values that are parseable as numbers or booleans. For further information see [JSONSchema docs](https://github.com/everit-org/json-schema#lenient-mode).\"\n }\n }\n }\n },\n \"allOf\": [\n {\n \"$ref\": \"#/definitions/input_output_options\"\n },\n {\n \"$ref\": \"#/definitions/reference_genome_options\"\n },\n {\n \"$ref\": \"#/definitions/adapter_trimming_options\"\n },\n {\n \"$ref\": \"#/definitions/alignment_options\"\n },\n {\n \"$ref\": \"#/definitions/peak_calling_options\"\n },\n {\n \"$ref\": \"#/definitions/deseq_qc_options\"\n },\n {\n \"$ref\": \"#/definitions/process_skipping_options\"\n },\n {\n \"$ref\": \"#/definitions/institutional_config_options\"\n },\n {\n \"$ref\": \"#/definitions/max_job_request_options\"\n },\n {\n \"$ref\": \"#/definitions/generic_options\"\n }\n ]\n}\n" }, { "path": "pyproject.toml", "content": "# Config file for Python. Mostly used to configure linting of bin/check_samplesheet.py with Black.\n# Should be kept the same as nf-core/tools to avoid fighting with template synchronisation.\n[tool.black]\nline-length = 120\ntarget_version = [\"py37\", \"py38\", \"py39\", \"py310\"]\n\n[tool.isort]\nprofile = \"black\"\nknown_first_party = [\"nf_core\"]\nmulti_line_output = 3\n" }, { "path": "subworkflows/local/align_star.nf", "content": "/*\n * Map reads, sort, index BAM file and run samtools stats, flagstat and idxstats\n */\n\ninclude { STAR_ALIGN } from '../../modules/local/star_align'\ninclude { BAM_SORT_STATS_SAMTOOLS } from '../nf-core/bam_sort_stats_samtools/main'\n\nworkflow ALIGN_STAR {\n take:\n ch_reads // channel: [ val(meta), [ reads ] ]\n ch_index // channel: /path/to/star/index/\n ch_fasta // channel: /path/to/fasta\n seq_center // string: sequencing center\n\n main:\n\n ch_versions = Channel.empty()\n\n //\n // Map reads with STAR\n //\n STAR_ALIGN ( ch_reads, ch_index, seq_center )\n ch_versions = ch_versions.mix(STAR_ALIGN.out.versions.first())\n\n //\n // Sort, index BAM file and run samtools stats, flagstat and idxstats\n //\n BAM_SORT_STATS_SAMTOOLS ( STAR_ALIGN.out.bam, ch_fasta )\n ch_versions = ch_versions.mix(BAM_SORT_STATS_SAMTOOLS.out.versions)\n\n emit:\n orig_bam = STAR_ALIGN.out.bam // channel: [ val(meta), bam ]\n log_final = STAR_ALIGN.out.log_final // channel: [ val(meta), log_final ]\n log_out = STAR_ALIGN.out.log_out // channel: [ val(meta), log_out ]\n log_progress = STAR_ALIGN.out.log_progress // channel: [ val(meta), log_progress ]\n bam_sorted = STAR_ALIGN.out.bam_sorted // channel: [ val(meta), bam_sorted ]\n bam_transcript = STAR_ALIGN.out.bam_transcript // channel: [ val(meta), bam_transcript ]\n fastq = STAR_ALIGN.out.fastq // channel: [ val(meta), fastq ]\n tab = STAR_ALIGN.out.tab // channel: [ val(meta), tab ]\n\n bam = BAM_SORT_STATS_SAMTOOLS.out.bam // channel: [ val(meta), [ bam ] ]\n bai = BAM_SORT_STATS_SAMTOOLS.out.bai // channel: [ val(meta), [ bai ] ]\n stats = BAM_SORT_STATS_SAMTOOLS.out.stats // channel: [ val(meta), [ stats ] ]\n flagstat = BAM_SORT_STATS_SAMTOOLS.out.flagstat // channel: [ val(meta), [ flagstat ] ]\n idxstats = BAM_SORT_STATS_SAMTOOLS.out.idxstats // channel: [ val(meta), [ idxstats ] ]\n\n versions = ch_versions // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/local/bam_bedgraph_bigwig_bedtools_ucsc.nf", "content": "\n//\n// Convert BAM to normalised bigWig via bedGraph using BEDTools and UCSC\n//\n\ninclude { BEDTOOLS_GENOMECOV } from '../../modules/local/bedtools_genomecov'\ninclude { UCSC_BEDGRAPHTOBIGWIG } from '../../modules/nf-core/ucsc/bedgraphtobigwig/main'\n\nworkflow BAM_BEDGRAPH_BIGWIG_BEDTOOLS_UCSC {\n take:\n ch_bam_flagstat // channel: [ val(meta), [bam], [flagstat] ]\n ch_chrom_sizes // channel: [ bed ]\n \n main:\n\n ch_versions = Channel.empty()\n\n //\n // Create bedGraph coverage track\n //\n BEDTOOLS_GENOMECOV (\n ch_bam_flagstat\n )\n ch_versions = ch_versions.mix(BEDTOOLS_GENOMECOV.out.versions.first())\n\n //\n // Create bigWig coverage tracks\n //\n UCSC_BEDGRAPHTOBIGWIG (\n BEDTOOLS_GENOMECOV.out.bedgraph,\n ch_chrom_sizes\n )\n ch_versions = ch_versions.mix(UCSC_BEDGRAPHTOBIGWIG.out.versions.first())\n\n emit:\n bedgraph = BEDTOOLS_GENOMECOV.out.bedgraph // channel: [ val(meta), [ bedgraph ] ]\n scale_factor = BEDTOOLS_GENOMECOV.out.scale_factor // channel: [ val(meta), [ txt ] ]\n\n bigwig = UCSC_BEDGRAPHTOBIGWIG.out.bigwig // channel: [ val(meta), [ bigwig ] ]\n\n versions = ch_versions // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/local/bam_filter_bamtools.nf", "content": "include { SAMTOOLS_SORT } from '../../modules/nf-core/samtools/sort/main'\ninclude { SAMTOOLS_INDEX } from '../../modules/nf-core/samtools/index/main'\ninclude { BAM_SORT_STATS_SAMTOOLS } from '../nf-core/bam_sort_stats_samtools/main'\ninclude { BAM_STATS_SAMTOOLS } from '../nf-core/bam_stats_samtools/main'\n\ninclude { BAMTOOLS_FILTER } from '../../modules/local/bamtools_filter'\ninclude { BAM_REMOVE_ORPHANS } from '../../modules/local/bam_remove_orphans'\n\nworkflow BAM_FILTER_BAMTOOLS {\n take:\n ch_bam_bai // channel: [ val(meta), [ bam ], [bai] ]\n ch_bed // channel: [ bed ]\n ch_fasta // channel: [ fasta ]\n ch_bamtools_filter_se_config // channel: [ config_file ]\n ch_bamtools_filter_pe_config // channel: [ config_file ]\n\n main:\n\n ch_versions = Channel.empty()\n\n //\n // Filter BAM file with BAMTools\n //\n BAMTOOLS_FILTER (\n ch_bam_bai,\n ch_bed,\n ch_bamtools_filter_se_config,\n ch_bamtools_filter_pe_config\n )\n ch_versions = ch_versions.mix(BAMTOOLS_FILTER.out.versions.first())\n\n BAMTOOLS_FILTER\n .out\n .bam\n .branch { \n meta, bam ->\n single_end: meta.single_end\n return [ meta, bam ]\n paired_end: !meta.single_end\n return [ meta, bam ]\n }\n .set { ch_bam }\n\n //\n // Index SE BAM file\n //\n SAMTOOLS_INDEX {\n ch_bam.single_end\n }\n ch_versions = ch_versions.mix(SAMTOOLS_INDEX.out.versions.first())\n\n //\n // Run samtools stats, flagstat and idxstats on SE BAM\n //\n BAM_STATS_SAMTOOLS (\n ch_bam.single_end.join(SAMTOOLS_INDEX.out.bai),\n ch_fasta\n )\n ch_versions = ch_versions.mix(BAM_STATS_SAMTOOLS.out.versions.first())\n\n //\n // Name sort PE BAM before filtering with pysam\n //\n SAMTOOLS_SORT (\n ch_bam.paired_end\n )\n ch_versions = ch_versions.mix(SAMTOOLS_SORT.out.versions.first())\n\n //\n // Remove orphan reads from PE BAM file\n //\n BAM_REMOVE_ORPHANS (\n SAMTOOLS_SORT.out.bam\n )\n ch_versions = ch_versions.mix(BAM_REMOVE_ORPHANS.out.versions.first())\n\n //\n // Sort, index PE BAM file and run samtools stats, flagstat and idxstats\n //\n BAM_SORT_STATS_SAMTOOLS (\n BAM_REMOVE_ORPHANS.out.bam,\n ch_fasta\n )\n ch_versions = ch_versions.mix(BAM_SORT_STATS_SAMTOOLS.out.versions.first())\n\n emit:\n name_bam = SAMTOOLS_SORT.out.bam // channel: [ val(meta), [ bam ] ]\n bam = BAM_SORT_STATS_SAMTOOLS.out.bam.mix(ch_bam.single_end) // channel: [ val(meta), [ bam ] ]\n bai = BAM_SORT_STATS_SAMTOOLS.out.bai.mix(SAMTOOLS_INDEX.out.bai) // channel: [ val(meta), [ bai ] ]\n stats = BAM_SORT_STATS_SAMTOOLS.out.stats.mix(BAM_STATS_SAMTOOLS.out.stats) // channel: [ val(meta), [ stats ] ]\n flagstat = BAM_SORT_STATS_SAMTOOLS.out.flagstat.mix(BAM_STATS_SAMTOOLS.out.flagstat) // channel: [ val(meta), [ flagstat ] ]\n idxstats = BAM_SORT_STATS_SAMTOOLS.out.idxstats.mix(BAM_STATS_SAMTOOLS.out.idxstats) // channel: [ val(meta), [ idxstats ] ]\n versions = ch_versions // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/local/bam_peaks_call_qc_annotate_macs2_homer.nf", "content": "//\n// Call peaks with MACS2, annotate with HOMER and perform downstream QC\n//\n\ninclude { MACS2_CALLPEAK } from '../../modules/nf-core/macs2/callpeak/main'\ninclude { HOMER_ANNOTATEPEAKS } from '../../modules/nf-core/homer/annotatepeaks/main'\n\ninclude { FRIP_SCORE } from '../../modules/local/frip_score'\ninclude { MULTIQC_CUSTOM_PEAKS } from '../../modules/local/multiqc_custom_peaks'\ninclude { PLOT_MACS2_QC } from '../../modules/local/plot_macs2_qc'\ninclude { PLOT_HOMER_ANNOTATEPEAKS } from '../../modules/local/plot_homer_annotatepeaks'\n\nworkflow BAM_PEAKS_CALL_QC_ANNOTATE_MACS2_HOMER {\n take:\n ch_bam // channel: [ val(meta), [ ip_bam ], [ control_bam ] ]\n ch_fasta // channel: [ fasta ]\n ch_gtf // channel: [ gtf ]\n macs_gsize // integer: value for --macs_gsize parameter\n annotate_peaks_suffix // string: suffix for input HOMER annotate peaks files to be trimmed off\n ch_peak_count_header_multiqc // channel: [ header_file ]\n ch_frip_score_multiqc // channel: [ header_file ]\n ch_peak_annotation_header_multiqc // channel: [ header_file ]\n is_narrow_peak // boolean: true/false\n skip_peak_annotation // boolean: true/false\n skip_peak_qc // boolean: true/false\n \n main:\n\n ch_versions = Channel.empty()\n\n //\n // Call peaks with MACS2\n //\n MACS2_CALLPEAK (\n ch_bam,\n macs_gsize\n )\n ch_versions = ch_versions.mix(MACS2_CALLPEAK.out.versions.first())\n\n //\n // Filter out samples with 0 MACS2 peaks called\n //\n MACS2_CALLPEAK\n .out\n .peak\n .filter { \n meta, peaks ->\n peaks.size() > 0\n }\n .set { ch_macs2_peaks }\n\n // Create channels: [ meta, ip_bam, peaks ]\n ch_bam\n .join(ch_macs2_peaks, by: [0])\n .map {\n meta, ip_bam, control_bam, peaks ->\n [ meta, ip_bam, peaks ]\n }\n .set { ch_bam_peaks }\n\n //\n // Calculate FRiP score\n //\n FRIP_SCORE (\n ch_bam_peaks\n )\n ch_versions = ch_versions.mix(FRIP_SCORE.out.versions.first())\n\n // Create channels: [ meta, peaks, frip ]\n ch_bam_peaks\n .join(FRIP_SCORE.out.txt, by: [0])\n .map {\n meta, ip_bam, peaks, frip ->\n [ meta, peaks, frip ]\n }\n .set { ch_bam_peak_frip }\n\n //\n // FRiP score custom content for MultiQC\n //\n MULTIQC_CUSTOM_PEAKS (\n ch_bam_peak_frip,\n ch_peak_count_header_multiqc,\n ch_frip_score_multiqc\n )\n ch_versions = ch_versions.mix(MULTIQC_CUSTOM_PEAKS.out.versions.first())\n\n ch_homer_annotatepeaks = Channel.empty()\n ch_plot_macs2_qc_txt = Channel.empty()\n ch_plot_macs2_qc_pdf = Channel.empty()\n ch_plot_homer_annotatepeaks_txt = Channel.empty()\n ch_plot_homer_annotatepeaks_pdf = Channel.empty()\n ch_plot_homer_annotatepeaks_tsv = Channel.empty()\n if (!skip_peak_annotation) {\n //\n // Annotate peaks with HOMER\n //\n HOMER_ANNOTATEPEAKS (\n ch_macs2_peaks,\n ch_fasta,\n ch_gtf\n )\n ch_homer_annotatepeaks = HOMER_ANNOTATEPEAKS.out.txt\n ch_versions = ch_versions.mix(HOMER_ANNOTATEPEAKS.out.versions.first())\n \n if (!skip_peak_qc) {\n //\n // MACS2 QC plots with R\n //\n PLOT_MACS2_QC (\n ch_macs2_peaks.collect{it[1]},\n is_narrow_peak\n )\n ch_plot_macs2_qc_txt = PLOT_MACS2_QC.out.txt\n ch_plot_macs2_qc_pdf = PLOT_MACS2_QC.out.pdf\n ch_versions = ch_versions.mix(PLOT_MACS2_QC.out.versions)\n\n //\n // Peak annotation QC plots with R\n //\n PLOT_HOMER_ANNOTATEPEAKS (\n HOMER_ANNOTATEPEAKS.out.txt.collect{it[1]},\n ch_peak_annotation_header_multiqc,\n annotate_peaks_suffix\n )\n ch_plot_homer_annotatepeaks_txt = PLOT_HOMER_ANNOTATEPEAKS.out.txt\n ch_plot_homer_annotatepeaks_pdf = PLOT_HOMER_ANNOTATEPEAKS.out.pdf\n ch_plot_homer_annotatepeaks_tsv = PLOT_HOMER_ANNOTATEPEAKS.out.tsv\n ch_versions = ch_versions.mix(PLOT_HOMER_ANNOTATEPEAKS.out.versions)\n }\n }\n\n emit:\n peaks = ch_macs2_peaks // channel: [ val(meta), [ peaks ] ]\n xls = MACS2_CALLPEAK.out.xls // channel: [ val(meta), [ xls ] ]\n gapped_peaks = MACS2_CALLPEAK.out.gapped // channel: [ val(meta), [ gapped_peak ] ]\n bed = MACS2_CALLPEAK.out.bed // channel: [ val(meta), [ bed ] ]\n bedgraph = MACS2_CALLPEAK.out.bdg // channel: [ val(meta), [ bedgraph ] ]\n\n frip_txt = FRIP_SCORE.out.txt // channel: [ val(meta), [ txt ] ]\n \n frip_multiqc = MULTIQC_CUSTOM_PEAKS.out.frip // channel: [ val(meta), [ frip ] ]\n peak_count_multiqc = MULTIQC_CUSTOM_PEAKS.out.count // channel: [ val(meta), [ counts ] ]\n\n homer_annotatepeaks = ch_homer_annotatepeaks // channel: [ val(meta), [ txt ] ]\n\n plot_macs2_qc_txt = ch_plot_macs2_qc_txt // channel: [ txt ]\n plot_macs2_qc_pdf = ch_plot_macs2_qc_pdf // channel: [ pdf ]\n\n plot_homer_annotatepeaks_txt = ch_plot_homer_annotatepeaks_txt // channel: [ txt ]\n plot_homer_annotatepeaks_pdf = ch_plot_homer_annotatepeaks_pdf // channel: [ pdf ]\n plot_homer_annotatepeaks_tsv = ch_plot_homer_annotatepeaks_tsv // channel: [ tsv ]\n\n versions = ch_versions // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/local/bed_consensus_quantify_qc_bedtools_featurecounts_deseq2.nf", "content": "//\n// Call consensus peaks with BEDTools and custom scripts, annotate with HOMER, quantify with featureCounts and QC with DESeq2\n//\n\ninclude { HOMER_ANNOTATEPEAKS } from '../../modules/nf-core/homer/annotatepeaks/main'\ninclude { SUBREAD_FEATURECOUNTS } from '../../modules/nf-core/subread/featurecounts/main'\n\ninclude { MACS2_CONSENSUS } from '../../modules/local/macs2_consensus'\ninclude { DESEQ2_QC } from '../../modules/local/deseq2_qc'\n\nworkflow BED_CONSENSUS_QUANTIFY_QC_BEDTOOLS_FEATURECOUNTS_DESEQ2 {\n take:\n ch_peaks // channel: [ val(meta), [ peaks ] ]\n ch_bams // channel: [ val(meta), [ bams ] ]\n ch_fasta // channel: [ fasta ]\n ch_gtf // channel: [ gtf ]\n ch_deseq2_pca_header_multiqc // channel: [ header_file ]\n ch_deseq2_clustering_header_multiqc // channel: [ header_file ]\n is_narrow_peak // boolean: true/false\n skip_peak_annotation // boolean: true/false\n skip_deseq2_qc // boolean: true/false\n \n main:\n\n ch_versions = Channel.empty()\n\n // Create channels: [ meta , [ peaks ] ]\n // where meta = [ id : consensus_peaks ]\n ch_peaks\n .collect { it[1] }\n .filter { it.size() > 1 }\n .map { \n peaks ->\n [ [ id: 'consensus_peaks' ], peaks ]\n }\n .set { ch_consensus_peaks }\n\n //\n // Generate consensus peaks across samples\n //\n MACS2_CONSENSUS (\n ch_consensus_peaks,\n is_narrow_peak\n )\n ch_versions = ch_versions.mix(MACS2_CONSENSUS.out.versions)\n\n //\n // Annotate consensus peaks\n //\n ch_homer_annotatepeaks = Channel.empty()\n if (!skip_peak_annotation) {\n HOMER_ANNOTATEPEAKS (\n MACS2_CONSENSUS.out.bed,\n ch_fasta,\n ch_gtf\n )\n ch_homer_annotatepeaks = HOMER_ANNOTATEPEAKS.out.txt\n ch_versions = ch_versions.mix(HOMER_ANNOTATEPEAKS.out.versions)\n }\n\n // Create channels: [ meta, [ bams ], saf ]\n ch_bams\n .join(ch_peaks)\n .collect { it[1] }\n .filter { it.size() > 1 }\n .map { [ it ] }\n .concat(MACS2_CONSENSUS.out.saf)\n .collect()\n .filter { it.size() == 3 }\n .map {\n bam, meta, saf -> \n [ meta, bam , saf ]\n }\n .set { ch_bam_saf }\n\n //\n // Quantify peaks across samples with featureCounts\n //\n SUBREAD_FEATURECOUNTS (\n ch_bam_saf\n )\n ch_versions = ch_versions.mix(SUBREAD_FEATURECOUNTS.out.versions)\n\n //\n // Generate QC plots with DESeq2\n //\n ch_deseq2_qc_pdf = Channel.empty()\n ch_deseq2_qc_rdata = Channel.empty()\n ch_deseq2_qc_rds = Channel.empty()\n ch_deseq2_qc_pca_txt = Channel.empty()\n ch_deseq2_qc_pca_multiqc = Channel.empty()\n ch_deseq2_qc_dists_txt = Channel.empty()\n ch_deseq2_qc_dists_multiqc = Channel.empty()\n ch_deseq2_qc_log = Channel.empty()\n ch_deseq2_qc_size_factors = Channel.empty()\n if (!skip_deseq2_qc) {\n DESEQ2_QC (\n SUBREAD_FEATURECOUNTS.out.counts,\n ch_deseq2_pca_header_multiqc,\n ch_deseq2_clustering_header_multiqc\n )\n ch_deseq2_qc_pdf = DESEQ2_QC.out.pdf\n ch_deseq2_qc_rdata = DESEQ2_QC.out.rdata\n ch_deseq2_qc_rds = DESEQ2_QC.out.rds\n ch_deseq2_qc_pca_txt = DESEQ2_QC.out.pca_txt\n ch_deseq2_qc_pca_multiqc = DESEQ2_QC.out.pca_multiqc\n ch_deseq2_qc_dists_txt = DESEQ2_QC.out.dists_txt\n ch_deseq2_qc_dists_multiqc = DESEQ2_QC.out.dists_multiqc\n ch_deseq2_qc_log = DESEQ2_QC.out.log\n ch_deseq2_qc_size_factors = DESEQ2_QC.out.size_factors\n ch_versions = ch_versions.mix(DESEQ2_QC.out.versions)\n }\n\n emit:\n consensus_bed = MACS2_CONSENSUS.out.bed // channel: [ bed ]\n consensus_saf = MACS2_CONSENSUS.out.saf // channel: [ saf ]\n consensus_pdf = MACS2_CONSENSUS.out.pdf // channel: [ pdf ]\n consensus_boolean_txt = MACS2_CONSENSUS.out.boolean_txt // channel: [ txt ]\n consensus_intersect_txt = MACS2_CONSENSUS.out.intersect_txt // channel: [ txt ]\n\n homer_annotatepeaks = ch_homer_annotatepeaks // channel: [ txt ]\n\n featurecounts_txt = SUBREAD_FEATURECOUNTS.out.counts // channel: [ txt ]\n featurecounts_summary = SUBREAD_FEATURECOUNTS.out.summary // channel: [ txt ]\n\n deseq2_qc_pdf = ch_deseq2_qc_pdf // channel: [ pdf ]\n deseq2_qc_rdata = ch_deseq2_qc_rdata // channel: [ rdata ]\n deseq2_qc_rds = ch_deseq2_qc_rds // channel: [ rds ]\n deseq2_qc_pca_txt = ch_deseq2_qc_pca_txt // channel: [ txt ]\n deseq2_qc_pca_multiqc = ch_deseq2_qc_pca_multiqc // channel: [ txt ]\n deseq2_qc_dists_txt = ch_deseq2_qc_dists_txt // channel: [ txt ]\n deseq2_qc_dists_multiqc = ch_deseq2_qc_dists_multiqc // channel: [ txt ]\n deseq2_qc_log = ch_deseq2_qc_log // channel: [ txt ]\n deseq2_qc_size_factors = ch_deseq2_qc_size_factors // channel: [ txt ]\n\n versions = ch_versions // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/local/bigwig_plot_deeptools.nf", "content": "\n//\n// Create coverage matrices, plot coverage profiles and heatmap with deepTools\n//\n\ninclude { DEEPTOOLS_PLOTPROFILE } from '../../modules/nf-core/deeptools/plotprofile/main'\ninclude { DEEPTOOLS_PLOTHEATMAP } from '../../modules/nf-core/deeptools/plotheatmap/main'\ninclude { DEEPTOOLS_COMPUTEMATRIX as DEEPTOOLS_COMPUTEMATRIX_SCALE_REGIONS } from '../../modules/nf-core/deeptools/computematrix/main'\ninclude { DEEPTOOLS_COMPUTEMATRIX as DEEPTOOLS_COMPUTEMATRIX_REFERENCE_POINT } from '../../modules/nf-core/deeptools/computematrix/main'\n\nworkflow BIGWIG_PLOT_DEEPTOOLS {\n take:\n ch_bigwig // channel: [ val(meta), bigwig ]\n ch_gene_bed // channel: [ bed ]\n ch_tss_bed // channel: [ bed ]\n \n main:\n\n ch_versions = Channel.empty()\n\n //\n // deepTools matrix generation for plotting over full transcript length\n //\n DEEPTOOLS_COMPUTEMATRIX_SCALE_REGIONS (\n ch_bigwig,\n ch_gene_bed\n )\n ch_versions = ch_versions.mix(DEEPTOOLS_COMPUTEMATRIX_SCALE_REGIONS.out.versions.first())\n\n //\n // deepTools matrix generation for plotting at TSS point\n //\n DEEPTOOLS_COMPUTEMATRIX_REFERENCE_POINT (\n ch_bigwig,\n ch_tss_bed\n )\n ch_versions = ch_versions.mix(DEEPTOOLS_COMPUTEMATRIX_REFERENCE_POINT.out.versions.first())\n\n //\n // deepTools profile plots\n //\n DEEPTOOLS_PLOTPROFILE (\n DEEPTOOLS_COMPUTEMATRIX_SCALE_REGIONS.out.matrix\n )\n ch_versions = ch_versions.mix(DEEPTOOLS_PLOTPROFILE.out.versions.first())\n\n //\n // deepTools heatmaps\n //\n DEEPTOOLS_PLOTHEATMAP (\n DEEPTOOLS_COMPUTEMATRIX_REFERENCE_POINT.out.matrix\n )\n ch_versions = ch_versions.mix(DEEPTOOLS_PLOTHEATMAP.out.versions.first())\n\n emit:\n scale_regions_matrix = DEEPTOOLS_COMPUTEMATRIX_SCALE_REGIONS.out.matrix // channel: [ val(meta), [ matrix ] ]\n scale_regions_table = DEEPTOOLS_COMPUTEMATRIX_SCALE_REGIONS.out.table // channel: [ val(meta), [ table ] ]\n\n reference_point_matrix = DEEPTOOLS_COMPUTEMATRIX_REFERENCE_POINT.out.matrix // channel: [ val(meta), [ matrix ] ]\n reference_point_table = DEEPTOOLS_COMPUTEMATRIX_REFERENCE_POINT.out.table // channel: [ val(meta), [ table ] ]\n\n plotprofile_pdf = DEEPTOOLS_PLOTPROFILE.out.pdf // channel: [ val(meta), [ pdf ] ]\n plotprofile_table = DEEPTOOLS_PLOTPROFILE.out.table // channel: [ val(meta), [ table ] ]\n\n plotheatmap_pdf = DEEPTOOLS_PLOTHEATMAP.out.pdf // channel: [ val(meta), [ pdf ] ]\n plotheatmap_table = DEEPTOOLS_PLOTHEATMAP.out.table // channel: [ val(meta), [ table ] ]\n\n versions = ch_versions // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/local/input_check.nf", "content": "//\n// Check input samplesheet and get read channels\n//\n\ninclude { SAMPLESHEET_CHECK } from '../../modules/local/samplesheet_check'\n\nworkflow INPUT_CHECK {\n take:\n samplesheet // file: /path/to/samplesheet.csv\n seq_center // string: sequencing center for read group\n with_control // boolean: samplesheet contains controls\n\n\n main:\n SAMPLESHEET_CHECK ( samplesheet )\n .csv\n .splitCsv ( header:true, sep:',' )\n .map { create_fastq_channel(it, seq_center) }\n .set { reads }\n\n emit:\n reads // channel: [ val(meta), [ reads ] ]\n versions = SAMPLESHEET_CHECK.out.versions // channel: [ versions.yml ]\n}\n\n// Function to get list of [ meta, [ fastq_1, fastq_2 ] ]\ndef create_fastq_channel(LinkedHashMap row, String seq_center) {\n def meta = [:]\n meta.id = row.sample\n meta.single_end = row.single_end.toBoolean()\n meta.control = row.control\n\n def read_group = \"\\'@RG\\\\tID:${meta.id}\\\\tSM:${meta.id - ~/_T\\d+$/}\\\\tPL:ILLUMINA\\\\tLB:${meta.id}\\\\tPU:1\\'\"\n if (seq_center) {\n read_group = \"\\'@RG\\\\tID:${meta.id}\\\\tSM:${meta.id - ~/_T\\d+$/}\\\\tPL:ILLUMINA\\\\tLB:${meta.id}\\\\tPU:1\\\\tCN:${seq_center}\\'\"\n }\n meta.read_group = read_group\n\n // add path(s) of the fastq file(s) to the meta map\n def fastq_meta = []\n if (!file(row.fastq_1).exists()) {\n exit 1, \"ERROR: Please check input samplesheet -> Read 1 FastQ file does not exist!\\n${row.fastq_1}\"\n }\n if (meta.single_end) {\n fastq_meta = [ meta, [ file(row.fastq_1) ] ]\n } else {\n if (!file(row.fastq_2).exists()) {\n exit 1, \"ERROR: Please check input samplesheet -> Read 2 FastQ file does not exist!\\n${row.fastq_2}\"\n }\n fastq_meta = [ meta, [ file(row.fastq_1), file(row.fastq_2) ] ]\n }\n return fastq_meta\n}\n" }, { "path": "subworkflows/local/prepare_genome.nf", "content": "//\n// Uncompress and prepare reference genome files\n//\n\ninclude {\n GUNZIP as GUNZIP_FASTA\n GUNZIP as GUNZIP_GTF\n GUNZIP as GUNZIP_GFF\n GUNZIP as GUNZIP_GENE_BED\n GUNZIP as GUNZIP_TSS_BED\n GUNZIP as GUNZIP_BLACKLIST } from '../../modules/nf-core/gunzip/main'\n\ninclude {\n UNTAR as UNTAR_BWA_INDEX\n UNTAR as UNTAR_BOWTIE2_INDEX\n UNTAR as UNTAR_CHROMAP_INDEX\n UNTAR as UNTAR_STAR_INDEX } from '../../modules/nf-core/untar/main'\n\ninclude { GFFREAD } from '../../modules/nf-core/gffread/main'\ninclude { CUSTOM_GETCHROMSIZES } from '../../modules/nf-core/custom/getchromsizes/main'\ninclude { BWA_INDEX } from '../../modules/nf-core/bwa/index/main'\ninclude { BOWTIE2_BUILD } from '../../modules/nf-core/bowtie2/build/main'\ninclude { CHROMAP_INDEX } from '../../modules/nf-core/chromap/index/main'\ninclude { KHMER_UNIQUEKMERS } from '../../modules/nf-core/khmer/uniquekmers/main'\n\ninclude { STAR_GENOMEGENERATE } from '../../modules/local/star_genomegenerate'\ninclude { GTF2BED } from '../../modules/local/gtf2bed'\ninclude { GENOME_BLACKLIST_REGIONS } from '../../modules/local/genome_blacklist_regions'\ninclude { GET_AUTOSOMES } from '../../modules/local/get_autosomes'\ninclude { TSS_EXTRACT } from '../../modules/local/tss_extract'\n\nworkflow PREPARE_GENOME {\n take:\n prepare_tool_index // string : tool to prepare index for\n\n main:\n ch_versions = Channel.empty()\n\n //\n // Uncompress genome fasta file if required\n //\n ch_fasta = Channel.empty()\n if (params.fasta.endsWith('.gz')) {\n ch_fasta = GUNZIP_FASTA ( [ [:], params.fasta ] ).gunzip.map{ it[1] }\n ch_versions = ch_versions.mix(GUNZIP_FASTA.out.versions)\n } else {\n ch_fasta = Channel.value(file(params.fasta))\n }\n\n //\n // Uncompress GTF annotation file or create from GFF3 if required\n //\n if (params.gtf) {\n if (params.gtf.endsWith('.gz')) {\n ch_gtf = GUNZIP_GTF ( [ [:], params.gtf ] ).gunzip.map{ it[1] }\n ch_versions = ch_versions.mix(GUNZIP_GTF.out.versions)\n } else {\n ch_gtf = Channel.value(file(params.gtf))\n }\n } else if (params.gff) {\n if (params.gff.endsWith('.gz')) {\n ch_gff = GUNZIP_GFF ( [ [:], params.gff ] ).gunzip.map{ it[1] }\n ch_versions = ch_versions.mix(GUNZIP_GFF.out.versions)\n } else {\n ch_gff = Channel.value(file(params.gff))\n }\n ch_gtf = GFFREAD ( ch_gff ).gtf\n ch_versions = ch_versions.mix(GFFREAD.out.versions)\n }\n\n //\n // Uncompress blacklist file if required\n //\n ch_blacklist = Channel.empty()\n if (params.blacklist) {\n if (params.blacklist.endsWith('.gz')) {\n ch_blacklist = GUNZIP_BLACKLIST ( [ [:], params.blacklist ] ).gunzip.map{ it[1] }\n ch_versions = ch_versions.mix(GUNZIP_BLACKLIST.out.versions)\n } else {\n ch_blacklist = Channel.value(file(params.blacklist))\n }\n }\n\n //\n // Uncompress gene BED annotation file or create from GTF if required\n //\n\n // If --gtf is supplied along with --genome\n // Make gene bed from supplied --gtf instead of using iGenomes one automatically\n def make_bed = false\n if (!params.gene_bed) {\n make_bed = true\n } else if (params.genome && params.gtf) {\n if (params.genomes[ params.genome ].gtf != params.gtf) {\n make_bed = true\n }\n }\n\n if (make_bed) {\n ch_gene_bed = GTF2BED ( ch_gtf ).bed\n ch_versions = ch_versions.mix(GTF2BED.out.versions)\n } else {\n if (params.gene_bed.endsWith('.gz')) {\n ch_gene_bed = GUNZIP_GENE_BED ( [ [:], params.gene_bed ] ).gunzip.map{ it[1] }\n ch_versions = ch_versions.mix(GUNZIP_GENE_BED.out.versions)\n } else {\n ch_gene_bed = Channel.value(file(params.gene_bed))\n }\n }\n\n if (!params.tss_bed) {\n ch_tss_bed = TSS_EXTRACT ( ch_gene_bed ).tss\n ch_versions = ch_versions.mix(TSS_EXTRACT.out.versions)\n } else {\n if (params.tss_bed.endsWith('.gz')) {\n ch_tss_bed = GUNZIP_TSS_BED ( [ [:], params.tss_bed ] ).gunzip.map{ it[1] }\n ch_versions = ch_versions.mix(GUNZIP_TSS_BED.out.versions)\n } else {\n ch_tss_bed = Channel.value(file(params.tss_bed))\n }\n }\n\n //\n // Create chromosome sizes file\n //\n CUSTOM_GETCHROMSIZES ( ch_fasta.map { [ [:], it ] } )\n ch_chrom_sizes = CUSTOM_GETCHROMSIZES.out.sizes.map { it[1] }\n ch_fai = CUSTOM_GETCHROMSIZES.out.fai.map{ it[1] }\n ch_versions = ch_versions.mix(CUSTOM_GETCHROMSIZES.out.versions)\n\n //\n // Create autosomal chromosome list for ataqv\n //\n ch_genome_autosomes = Channel.empty()\n GET_AUTOSOMES (\n ch_fai\n )\n ch_genome_autosomes = GET_AUTOSOMES.out.txt\n ch_versions = ch_versions.mix(GET_AUTOSOMES.out.versions)\n\n\n //\n // Prepare genome intervals for filtering by removing regions in blacklist file\n //\n ch_genome_filtered_bed = Channel.empty()\n GENOME_BLACKLIST_REGIONS (\n ch_chrom_sizes,\n ch_blacklist.ifEmpty([]),\n params.mito_name ?: '',\n params.keep_mito\n )\n ch_genome_filtered_bed = GENOME_BLACKLIST_REGIONS.out.bed\n ch_versions = ch_versions.mix(GENOME_BLACKLIST_REGIONS.out.versions)\n\n //\n // Uncompress BWA index or generate from scratch if required\n //\n ch_bwa_index = Channel.empty()\n if (prepare_tool_index == 'bwa') {\n if (params.bwa_index) {\n if (params.bwa_index.endsWith('.tar.gz')) {\n ch_bwa_index = UNTAR_BWA_INDEX ( [ [:], params.bwa_index ] ).untar\n ch_versions = ch_versions.mix(UNTAR_BWA_INDEX.out.versions)\n } else {\n ch_bwa_index = [ [:], file(params.bwa_index) ]\n }\n } else {\n ch_bwa_index = BWA_INDEX ( ch_fasta.map { [ [:], it ] } ).index\n ch_versions = ch_versions.mix(BWA_INDEX.out.versions)\n }\n }\n\n //\n // Uncompress Bowtie2 index or generate from scratch if required\n //\n ch_bowtie2_index = Channel.empty()\n if (prepare_tool_index == 'bowtie2') {\n if (params.bowtie2_index) {\n if (params.bowtie2_index.endsWith('.tar.gz')) {\n ch_bowtie2_index = UNTAR_BOWTIE2_INDEX ( [ [:], params.bowtie2_index ] ).untar\n ch_versions = ch_versions.mix(UNTAR_BOWTIE2_INDEX.out.versions)\n } else {\n ch_bowtie2_index = [ [:], file(params.bowtie2_index) ]\n }\n } else {\n ch_bowtie2_index = BOWTIE2_BUILD ( ch_fasta.map { [ [:], it ] } ).index\n ch_versions = ch_versions.mix(BOWTIE2_BUILD.out.versions)\n }\n }\n\n //\n // Uncompress CHROMAP index or generate from scratch if required\n //\n ch_chromap_index = Channel.empty()\n if (prepare_tool_index == 'chromap') {\n if (params.chromap_index) {\n if (params.chromap_index.endsWith('.tar.gz')) {\n ch_chromap_index = UNTAR_CHROMAP_INDEX ( [ [:], params.chromap_index ] ).untar\n ch_versions = ch_versions.mix(UNTAR.out.versions)\n } else {\n ch_chromap_index = [ [:], file(params.chromap_index) ]\n }\n } else {\n ch_chromap_index = CHROMAP_INDEX ( ch_fasta.map { [ [:], it ] } ).index\n ch_versions = ch_versions.mix(CHROMAP_INDEX.out.versions)\n }\n }\n\n //\n // Uncompress STAR index or generate from scratch if required\n //\n ch_star_index = Channel.empty()\n if (prepare_tool_index == 'star') {\n if (params.star_index) {\n if (params.star_index.endsWith('.tar.gz')) {\n ch_star_index = UNTAR_STAR_INDEX ( [ [:], params.star_index ] ).untar.map{ it[1] }\n ch_versions = ch_versions.mix(UNTAR_STAR_INDEX.out.versions)\n } else {\n ch_star_index = Channel.value(file(params.star_index))\n }\n } else {\n ch_star_index = STAR_GENOMEGENERATE ( ch_fasta, ch_gtf ).index\n ch_versions = ch_versions.mix(STAR_GENOMEGENERATE.out.versions)\n }\n }\n\n //\n // Estimate MACS2 genome size\n //\n ch_macs_gsize = params.macs_gsize\n if (!params.macs_gsize) {\n KHMER_UNIQUEKMERS (\n ch_fasta,\n params.read_length\n )\n ch_macs_gsize = KHMER_UNIQUEKMERS.out.kmers.map { it.text.trim() }\n ch_versions = ch_versions.mix(KHMER_UNIQUEKMERS.out.versions)\n }\n\n emit:\n fasta = ch_fasta // path: genome.fasta\n fai = ch_fai // path: genome.fai\n gtf = ch_gtf // path: genome.gtf\n gene_bed = ch_gene_bed // path: gene.bed\n tss_bed = ch_tss_bed // path: tss.bed\n chrom_sizes = ch_chrom_sizes // path: genome.sizes\n filtered_bed = ch_genome_filtered_bed // path: *.include_regions.bed\n bwa_index = ch_bwa_index // path: bwa/index/\n bowtie2_index = ch_bowtie2_index // path: bowtie2/index/\n chromap_index = ch_chromap_index // path: genome.index\n star_index = ch_star_index // path: star/index/\n autosomes = ch_genome_autosomes // path: *.autosomes.txt\n macs_gsize = ch_macs_gsize // integer: MACS2 genome size\n\n versions = ch_versions.ifEmpty(null) // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/nf-core/bam_markduplicates_picard/main.nf", "content": "//\n// Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats\n//\n\ninclude { PICARD_MARKDUPLICATES } from '../../../modules/nf-core/picard/markduplicates/main'\ninclude { SAMTOOLS_INDEX } from '../../../modules/nf-core/samtools/index/main'\ninclude { BAM_STATS_SAMTOOLS } from '../bam_stats_samtools/main'\n\nworkflow BAM_MARKDUPLICATES_PICARD {\n\n take:\n ch_bam // channel: [ val(meta), path(bam) ]\n ch_fasta // channel: [ path(fasta) ]\n ch_fai // channel: [ path(fai) ]\n\n main:\n\n ch_versions = Channel.empty()\n\n PICARD_MARKDUPLICATES ( ch_bam, ch_fasta, ch_fai )\n ch_versions = ch_versions.mix(PICARD_MARKDUPLICATES.out.versions.first())\n\n SAMTOOLS_INDEX ( PICARD_MARKDUPLICATES.out.bam )\n ch_versions = ch_versions.mix(SAMTOOLS_INDEX.out.versions.first())\n\n ch_bam_bai = PICARD_MARKDUPLICATES.out.bam\n .join(SAMTOOLS_INDEX.out.bai, by: [0], remainder: true)\n .join(SAMTOOLS_INDEX.out.csi, by: [0], remainder: true)\n .map {\n meta, bam, bai, csi ->\n if (bai) {\n [ meta, bam, bai ]\n } else {\n [ meta, bam, csi ]\n }\n }\n\n BAM_STATS_SAMTOOLS ( ch_bam_bai, ch_fasta )\n ch_versions = ch_versions.mix(BAM_STATS_SAMTOOLS.out.versions)\n\n emit:\n bam = PICARD_MARKDUPLICATES.out.bam // channel: [ val(meta), path(bam) ]\n metrics = PICARD_MARKDUPLICATES.out.metrics // channel: [ val(meta), path(bam) ]\n bai = SAMTOOLS_INDEX.out.bai // channel: [ val(meta), path(bai) ]\n csi = SAMTOOLS_INDEX.out.csi // channel: [ val(meta), path(csi) ]\n\n stats = BAM_STATS_SAMTOOLS.out.stats // channel: [ val(meta), path(stats) ]\n flagstat = BAM_STATS_SAMTOOLS.out.flagstat // channel: [ val(meta), path(flagstat) ]\n idxstats = BAM_STATS_SAMTOOLS.out.idxstats // channel: [ val(meta), path(idxstats) ]\n\n versions = ch_versions // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/nf-core/bam_markduplicates_picard/meta.yml", "content": "# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/subworkflows/yaml-schema.json\nname: \"bam_markduplicates_picard\"\ndescription: Picard MarkDuplicates, index BAM file and run samtools stats, flagstat and idxstats\nkeywords:\n - markduplicates\n - bam\n - sam\n - cram\n\nmodules:\n - picard/markduplicates\n - samtools/index\n - samtools/stats\n - samtools/idxstats\n - samtools/flagstat\n\ninput:\n - ch_bam:\n description: |\n BAM/CRAM/SAM file\n Structure: [ val(meta), path(bam) ]\n - ch_fasta:\n description: |\n Reference genome fasta file\n Structure: [ path(fasta) ]\n - ch_fasta:\n description: |\n Index of the reference genome fasta file\n Structure: [ path(fai) ]\noutput:\n - bam:\n description: |\n processed BAM/CRAM/SAM file\n Structure: [ val(meta), path(bam) ]\n - bai:\n description: |\n BAM/CRAM/SAM samtools index\n Structure: [ val(meta), path(bai) ]\n - csi:\n description: |\n CSI samtools index\n Structure: [ val(meta), path(csi) ]\n - stats:\n description: |\n File containing samtools stats output\n Structure: [ val(meta), path(stats) ]\n - flagstat:\n description: |\n File containing samtools flagstat output\n Structure: [ val(meta), path(flagstat) ]\n - idxstats:\n description: |\n File containing samtools idxstats output\n Structure: [ val(meta), path(idxstats) ]\n - versions:\n description: |\n Files containing software versions\n Structure: [ path(versions.yml) ]\nauthors:\n - \"@dmarron\"\n - \"@drpatelh\"\n" }, { "path": "subworkflows/nf-core/bam_sort_stats_samtools/main.nf", "content": "//\n// Sort, index BAM file and run samtools stats, flagstat and idxstats\n//\n\ninclude { SAMTOOLS_SORT } from '../../../modules/nf-core/samtools/sort/main'\ninclude { SAMTOOLS_INDEX } from '../../../modules/nf-core/samtools/index/main'\ninclude { BAM_STATS_SAMTOOLS } from '../bam_stats_samtools/main'\n\nworkflow BAM_SORT_STATS_SAMTOOLS {\n take:\n ch_bam // channel: [ val(meta), [ bam ] ]\n ch_fasta // channel: [ val(meta), path(fasta) ]\n\n main:\n\n ch_versions = Channel.empty()\n\n SAMTOOLS_SORT ( ch_bam )\n ch_versions = ch_versions.mix(SAMTOOLS_SORT.out.versions.first())\n\n SAMTOOLS_INDEX ( SAMTOOLS_SORT.out.bam )\n ch_versions = ch_versions.mix(SAMTOOLS_INDEX.out.versions.first())\n\n SAMTOOLS_SORT.out.bam\n .join(SAMTOOLS_INDEX.out.bai, by: [0], remainder: true)\n .join(SAMTOOLS_INDEX.out.csi, by: [0], remainder: true)\n .map {\n meta, bam, bai, csi ->\n if (bai) {\n [ meta, bam, bai ]\n } else {\n [ meta, bam, csi ]\n }\n }\n .set { ch_bam_bai }\n\n BAM_STATS_SAMTOOLS ( ch_bam_bai, ch_fasta )\n ch_versions = ch_versions.mix(BAM_STATS_SAMTOOLS.out.versions)\n\n emit:\n bam = SAMTOOLS_SORT.out.bam // channel: [ val(meta), [ bam ] ]\n bai = SAMTOOLS_INDEX.out.bai // channel: [ val(meta), [ bai ] ]\n csi = SAMTOOLS_INDEX.out.csi // channel: [ val(meta), [ csi ] ]\n\n stats = BAM_STATS_SAMTOOLS.out.stats // channel: [ val(meta), [ stats ] ]\n flagstat = BAM_STATS_SAMTOOLS.out.flagstat // channel: [ val(meta), [ flagstat ] ]\n idxstats = BAM_STATS_SAMTOOLS.out.idxstats // channel: [ val(meta), [ idxstats ] ]\n\n versions = ch_versions // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/nf-core/bam_sort_stats_samtools/meta.yml", "content": "# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/subworkflows/yaml-schema.json\nname: bam_sort_stats_samtools\ndescription: Sort SAM/BAM/CRAM file\nkeywords:\n - sort\n - bam\n - sam\n - cram\nmodules:\n - samtools/sort\n - samtools/index\n - samtools/stats\n - samtools/idxstats\n - samtools/flagstat\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: BAM/CRAM/SAM file\n pattern: \"*.{bam,cram,sam}\"\n - fasta:\n type: file\n description: Reference genome fasta file\n pattern: \"*.{fasta,fa}\"\n# TODO Update when we decide on a standard for subworkflow docs\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - bam:\n type: file\n description: Sorted BAM/CRAM/SAM file\n pattern: \"*.{bam,cram,sam}\"\n - bai:\n type: file\n description: BAM/CRAM/SAM index file\n pattern: \"*.{bai,crai,sai}\"\n - crai:\n type: file\n description: BAM/CRAM/SAM index file\n pattern: \"*.{bai,crai,sai}\"\n - stats:\n type: file\n description: File containing samtools stats output\n pattern: \"*.{stats}\"\n - flagstat:\n type: file\n description: File containing samtools flagstat output\n pattern: \"*.{flagstat}\"\n - idxstats:\n type: file\n description: File containing samtools idxstats output\n pattern: \"*.{idxstats}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@ewels\"\n" }, { "path": "subworkflows/nf-core/bam_stats_samtools/main.nf", "content": "//\n// Run SAMtools stats, flagstat and idxstats\n//\n\ninclude { SAMTOOLS_STATS } from '../../../modules/nf-core/samtools/stats/main'\ninclude { SAMTOOLS_IDXSTATS } from '../../../modules/nf-core/samtools/idxstats/main'\ninclude { SAMTOOLS_FLAGSTAT } from '../../../modules/nf-core/samtools/flagstat/main'\n\nworkflow BAM_STATS_SAMTOOLS {\n take:\n ch_bam_bai // channel: [ val(meta), path(bam), path(bai) ]\n ch_fasta // channel: [ val(meta), path(fasta) ]\n\n main:\n ch_versions = Channel.empty()\n\n SAMTOOLS_STATS ( ch_bam_bai, ch_fasta )\n ch_versions = ch_versions.mix(SAMTOOLS_STATS.out.versions)\n\n SAMTOOLS_FLAGSTAT ( ch_bam_bai )\n ch_versions = ch_versions.mix(SAMTOOLS_FLAGSTAT.out.versions)\n\n SAMTOOLS_IDXSTATS ( ch_bam_bai )\n ch_versions = ch_versions.mix(SAMTOOLS_IDXSTATS.out.versions)\n\n emit:\n stats = SAMTOOLS_STATS.out.stats // channel: [ val(meta), path(stats) ]\n flagstat = SAMTOOLS_FLAGSTAT.out.flagstat // channel: [ val(meta), path(flagstat) ]\n idxstats = SAMTOOLS_IDXSTATS.out.idxstats // channel: [ val(meta), path(idxstats) ]\n\n versions = ch_versions // channel: [ path(versions.yml) ]\n}\n" }, { "path": "subworkflows/nf-core/bam_stats_samtools/meta.yml", "content": "# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/subworkflows/yaml-schema.json\nname: bam_stats_samtools\ndescription: Produces comprehensive statistics from SAM/BAM/CRAM file\nkeywords:\n - statistics\n - counts\n - bam\n - sam\n - cram\nmodules:\n - samtools/stats\n - samtools/idxstats\n - samtools/flagstat\ninput:\n - ch_bam_bai:\n description: |\n The input channel containing the BAM/CRAM and it's index\n Structure: [ val(meta), path(bam), path(bai) ]\n - ch_fasta:\n description: |\n Reference genome fasta file\n Structure: [ path(fasta) ]\noutput:\n - stats:\n description: |\n File containing samtools stats output\n Structure: [ val(meta), path(stats) ]\n - flagstat:\n description: |\n File containing samtools flagstat output\n Structure: [ val(meta), path(flagstat) ]\n - idxstats:\n description: |\n File containing samtools idxstats output\n Structure: [ val(meta), path(idxstats)]\n - versions:\n description: |\n Files containing software versions\n Structure: [ path(versions.yml) ]\nauthors:\n - \"@drpatelh\"\n" }, { "path": "subworkflows/nf-core/fastq_align_bowtie2/main.nf", "content": "//\n// Alignment with Bowtie2\n//\n\ninclude { BOWTIE2_ALIGN } from '../../../modules/nf-core/bowtie2/align/main'\ninclude { BAM_SORT_STATS_SAMTOOLS } from '../bam_sort_stats_samtools/main'\n\nworkflow FASTQ_ALIGN_BOWTIE2 {\n take:\n ch_reads // channel: [ val(meta), [ reads ] ]\n ch_index // channel: /path/to/bowtie2/index/\n save_unaligned // val\n sort_bam // val\n ch_fasta // channel: /path/to/reference.fasta\n\n main:\n\n ch_versions = Channel.empty()\n\n //\n // Map reads with Bowtie2\n //\n BOWTIE2_ALIGN ( ch_reads, ch_index, save_unaligned, sort_bam )\n ch_versions = ch_versions.mix(BOWTIE2_ALIGN.out.versions)\n\n //\n // Sort, index BAM file and run samtools stats, flagstat and idxstats\n //\n BAM_SORT_STATS_SAMTOOLS ( BOWTIE2_ALIGN.out.aligned, ch_fasta )\n ch_versions = ch_versions.mix(BAM_SORT_STATS_SAMTOOLS.out.versions)\n\n emit:\n bam_orig = BOWTIE2_ALIGN.out.aligned // channel: [ val(meta), aligned ]\n log_out = BOWTIE2_ALIGN.out.log // channel: [ val(meta), log ]\n fastq = BOWTIE2_ALIGN.out.fastq // channel: [ val(meta), fastq ]\n\n bam = BAM_SORT_STATS_SAMTOOLS.out.bam // channel: [ val(meta), [ bam ] ]\n bai = BAM_SORT_STATS_SAMTOOLS.out.bai // channel: [ val(meta), [ bai ] ]\n csi = BAM_SORT_STATS_SAMTOOLS.out.csi // channel: [ val(meta), [ csi ] ]\n stats = BAM_SORT_STATS_SAMTOOLS.out.stats // channel: [ val(meta), [ stats ] ]\n flagstat = BAM_SORT_STATS_SAMTOOLS.out.flagstat // channel: [ val(meta), [ flagstat ] ]\n idxstats = BAM_SORT_STATS_SAMTOOLS.out.idxstats // channel: [ val(meta), [ idxstats ] ]\n\n versions = ch_versions // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/nf-core/fastq_align_bowtie2/meta.yml", "content": "# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/subworkflows/yaml-schema.json\nname: fastq_align_bowtie2\ndescription: Align reads to a reference genome using bowtie2 then sort with samtools\nkeywords:\n - align\n - fasta\n - genome\n - reference\nmodules:\n - bowtie2/align\n - samtools/sort\n - samtools/index\n - samtools/stats\n - samtools/idxstats\n - samtools/flagstat\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - ch_reads:\n type: file\n description: |\n List of input FastQ files of size 1 and 2 for single-end and paired-end data,\n respectively.\n - ch_index:\n type: file\n description: Bowtie2 genome index files\n pattern: \"*.ebwt\"\n - save_unaligned:\n type: boolean\n description: |\n Save reads that do not map to the reference (true) or discard them (false)\n (default: false)\n - sort_bam:\n type: boolean\n description: |\n Save reads that do not map to the reference (true) or discard them (false)\n default: false\n - ch_fasta:\n type: file\n description: Reference fasta file\n pattern: \"*.{fasta,fa}\"\n# TODO Update when we decide on a standard for subworkflow docs\noutput:\n - bam:\n type: file\n description: Output BAM file containing read alignments\n pattern: \"*.{bam}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\n - fastq:\n type: file\n description: Unaligned FastQ files\n pattern: \"*.fastq.gz\"\n - log:\n type: file\n description: Alignment log\n pattern: \"*.log\"\n# TODO Add samtools outputs\nauthors:\n - \"@drpatelh\"\n" }, { "path": "subworkflows/nf-core/fastq_align_bwa/main.nf", "content": "//\n// Alignment with BWA\n//\n\ninclude { BWA_MEM } from '../../../modules/nf-core/bwa/mem/main'\ninclude { BAM_SORT_STATS_SAMTOOLS } from '../bam_sort_stats_samtools/main'\n\nworkflow FASTQ_ALIGN_BWA {\n take:\n ch_reads // channel (mandatory): [ val(meta), [ path(reads) ] ]\n ch_index // channel (mandatory): [ val(meta2), path(index) ]\n val_sort_bam // boolean (mandatory): true or false\n ch_fasta // channel (optional) : [ path(fasta) ]\n\n main:\n ch_versions = Channel.empty()\n\n //\n // Map reads with BWA\n //\n\n BWA_MEM ( ch_reads, ch_index, val_sort_bam )\n ch_versions = ch_versions.mix(BWA_MEM.out.versions.first())\n\n //\n // Sort, index BAM file and run samtools stats, flagstat and idxstats\n //\n\n BAM_SORT_STATS_SAMTOOLS ( BWA_MEM.out.bam, ch_fasta )\n ch_versions = ch_versions.mix(BAM_SORT_STATS_SAMTOOLS.out.versions)\n\n emit:\n bam_orig = BWA_MEM.out.bam // channel: [ val(meta), path(bam) ]\n\n bam = BAM_SORT_STATS_SAMTOOLS.out.bam // channel: [ val(meta), path(bam) ]\n bai = BAM_SORT_STATS_SAMTOOLS.out.bai // channel: [ val(meta), path(bai) ]\n csi = BAM_SORT_STATS_SAMTOOLS.out.csi // channel: [ val(meta), path(csi) ]\n stats = BAM_SORT_STATS_SAMTOOLS.out.stats // channel: [ val(meta), path(stats) ]\n flagstat = BAM_SORT_STATS_SAMTOOLS.out.flagstat // channel: [ val(meta), path(flagstat) ]\n idxstats = BAM_SORT_STATS_SAMTOOLS.out.idxstats // channel: [ val(meta), path(idxstats) ]\n\n versions = ch_versions // channel: [ path(versions.yml) ]\n}\n" }, { "path": "subworkflows/nf-core/fastq_align_bwa/meta.yml", "content": "# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/subworkflows/yaml-schema.json\nname: fastq_align_bwa\ndescription: Align reads to a reference genome using bwa then sort with samtools\nkeywords:\n - align\n - fasta\n - genome\n - reference\nmodules:\n - bwa/align\n - samtools/sort\n - samtools/index\n - samtools/stats\n - samtools/idxstats\n - samtools/flagstat\ninput:\n - ch_reads:\n description: |\n List of input FastQ files of size 1 and 2 for single-end and paired-end data,\n respectively.\n Structure: [ val(meta), [ path(reads) ] ]\n - ch_index:\n description: |\n BWA genome index files\n Structure: [ val(meta2), path(index) ]\n - val_sort_bam:\n type: boolean\n description: If true bwa modules sort resulting bam files\n pattern: \"true|false\"\n - ch_fasta:\n type: file\n description: |\n Optional reference fasta file. This only needs to be given if val_sort_bam = true\n Structure: [ path(fasta) ]\n\noutput:\n - bam_orig:\n description: |\n BAM file produced by bwa\n Structure: [ val(meta), path(bam) ]\n - bam:\n description: |\n BAM file ordered by samtools\n Structure: [ val(meta), path(bam) ]\n - bai:\n description: |\n BAI index of the ordered BAM file\n Structure: [ val(meta), path(bai) ]\n - csi:\n description: |\n CSI index of the ordered BAM file\n Structure: [ val(meta), path(csi) ]\n - stats:\n description: |\n File containing samtools stats output\n Structure: [ val(meta), path(stats) ]\n - flagstat:\n description: |\n File containing samtools flagstat output\n Structure: [ val(meta), path(flagstat) ]\n - idxstats:\n description: |\n File containing samtools idxstats output\n Structure: [ val(meta), path(idxstats) ]\n - versions:\n description: |\n Files containing software versions\n Structure: [ path(versions.yml) ]\nauthors:\n - \"@JoseEspinosa\"\n" }, { "path": "subworkflows/nf-core/fastq_align_chromap/main.nf", "content": "/*\n * Map reads, sort, index BAM file and run samtools stats, flagstat and idxstats\n */\n\ninclude { CHROMAP_CHROMAP } from '../../../modules/nf-core/chromap/chromap/main'\ninclude { BAM_SORT_STATS_SAMTOOLS } from '../bam_sort_stats_samtools/main'\n\nworkflow FASTQ_ALIGN_CHROMAP {\n take:\n ch_reads // channel (mandatory): [ val(meta), [ reads ] ]\n ch_index // channel (mandatory): [ val(meta2, [ index ] ]\n ch_fasta // channel (mandatory): [ val(meta2, [ fasta ] ]\n ch_barcodes // channel (optional): [ barcodes ]\n ch_whitelist // channel (optional): [ whitelist ]\n ch_chr_order // channel (optional): [ chr_order ]\n ch_pairs_chr_order // channel (optional): [ pairs_chr_order ]\n\n main:\n ch_versions = Channel.empty()\n\n //\n // Map reads with CHROMAP\n //\n CHROMAP_CHROMAP(ch_reads, ch_fasta, ch_index, ch_barcodes, ch_whitelist, ch_chr_order, ch_pairs_chr_order)\n ch_versions = ch_versions.mix(CHROMAP_CHROMAP.out.versions)\n\n //\n // Sort, index BAM file and run samtools stats, flagstat and idxstats\n //\n BAM_SORT_STATS_SAMTOOLS(CHROMAP_CHROMAP.out.bam, ch_fasta)\n ch_versions = ch_versions.mix(BAM_SORT_STATS_SAMTOOLS.out.versions)\n\n emit:\n bam = BAM_SORT_STATS_SAMTOOLS.out.bam // channel: [ val(meta), [ bam ] ]\n bai = BAM_SORT_STATS_SAMTOOLS.out.bai // channel: [ val(meta), [ bai ] ]\n stats = BAM_SORT_STATS_SAMTOOLS.out.stats // channel: [ val(meta), [ stats ] ]\n flagstat = BAM_SORT_STATS_SAMTOOLS.out.flagstat // channel: [ val(meta), [ flagstat ] ]\n idxstats = BAM_SORT_STATS_SAMTOOLS.out.idxstats // channel: [ val(meta), [ idxstats ] ]\n\n versions = ch_versions // path: versions.yml\n}\n" }, { "path": "subworkflows/nf-core/fastq_align_chromap/meta.yml", "content": "# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/subworkflows/yaml-schema.json\nname: \"fastq_align_chromap\"\ndescription: Align high throughput chromatin profiles using Chromap then sort with samtools\nkeywords:\n - align\n - fasta\n - genome\n - reference\n - chromatin profiles\n - chip-seq\n - atac-seq\n - hic\nmodules:\n - chromap/chromap\n - samtools/sort\n - samtools/index\n - samtools/stats\n - samtools/idxstats\n - samtools/flagstat\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test', single_end:false ]\n - ch_reads:\n type: file\n description: |\n Structure: [val(meta), path(reads)]\n List of input FastQ files of size 1 and 2 for single-end and paired-end data,\n respectively.\n - meta2:\n type: map\n description: |\n Groovy Map containing reference information\n e.g. [ id:'test' ]\n - ch_index:\n type: file\n description: |\n Structure: [val(meta2), path(index)]\n Chromap genome index files\n pattern: \"*.index\"\n - ch_fasta:\n type: file\n description: |\n Structure: [val(meta2), path(fasta)]\n Reference fasta file\n pattern: \"*.{fasta,fa}\"\n - ch_barcodes:\n type: file\n description: |\n Structure: [path(barcodes)]\n Cell barcode files\n - ch_whitelist:\n type: file\n description: |\n Structure: [path(whitelist)]\n Cell barcode whitelist file\n - ch_chr_order:\n type: file\n description: |\n Structure: [path(chr_order)]\n Custom chromosome order\n - ch_pairs_chr_order:\n type: file\n description: |\n Structure: [path(pairs_chr_order)]\n Natural chromosome order for pairs flipping\noutput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test' ]\n - bam:\n type: file\n description: BAM file\n pattern: \"*.bam\"\n - bai:\n type: file\n description: BAM index (currently only for snapaligner)\n pattern: \"*.bai\"\n - stats:\n type: file\n description: File containing samtools stats output\n pattern: \"*.{stats}\"\n - flagstat:\n type: file\n description: File containing samtools flagstat output\n pattern: \"*.{flagstat}\"\n - idxstats:\n type: file\n description: File containing samtools idxstats output\n pattern: \"*.{idxstats}\"\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@JoseEspinosa\"\n" }, { "path": "subworkflows/nf-core/fastq_fastqc_umitools_trimgalore/main.nf", "content": "//\n// Read QC, UMI extraction and trimming\n//\n\ninclude { FASTQC } from '../../../modules/nf-core/fastqc/main'\ninclude { UMITOOLS_EXTRACT } from '../../../modules/nf-core/umitools/extract/main'\ninclude { TRIMGALORE } from '../../../modules/nf-core/trimgalore/main'\n\n//\n// Function that parses TrimGalore log output file to get total number of reads after trimming\n//\ndef getTrimGaloreReadsAfterFiltering(log_file) {\n def total_reads = 0\n def filtered_reads = 0\n log_file.eachLine { line ->\n def total_reads_matcher = line =~ /([\\d\\.]+)\\ssequences processed in total/\n def filtered_reads_matcher = line =~ /shorter than the length cutoff[^:]+:\\s([\\d\\.]+)/\n if (total_reads_matcher) total_reads = total_reads_matcher[0][1].toFloat()\n if (filtered_reads_matcher) filtered_reads = filtered_reads_matcher[0][1].toFloat()\n }\n return total_reads - filtered_reads\n}\n\nworkflow FASTQ_FASTQC_UMITOOLS_TRIMGALORE {\n take:\n reads // channel: [ val(meta), [ reads ] ]\n skip_fastqc // boolean: true/false\n with_umi // boolean: true/false\n skip_umi_extract // boolean: true/false\n skip_trimming // boolean: true/false\n umi_discard_read // integer: 0, 1 or 2\n min_trimmed_reads // integer: > 0\n\n main:\n ch_versions = Channel.empty()\n fastqc_html = Channel.empty()\n fastqc_zip = Channel.empty()\n if (!skip_fastqc) {\n FASTQC (reads)\n fastqc_html = FASTQC.out.html\n fastqc_zip = FASTQC.out.zip\n ch_versions = ch_versions.mix(FASTQC.out.versions.first())\n }\n\n umi_reads = reads\n umi_log = Channel.empty()\n if (with_umi && !skip_umi_extract) {\n UMITOOLS_EXTRACT (reads)\n umi_reads = UMITOOLS_EXTRACT.out.reads\n umi_log = UMITOOLS_EXTRACT.out.log\n ch_versions = ch_versions.mix(UMITOOLS_EXTRACT.out.versions.first())\n\n // Discard R1 / R2 if required\n if (umi_discard_read in [1,2]) {\n UMITOOLS_EXTRACT\n .out\n .reads\n .map {\n meta, reads ->\n meta.single_end ? [ meta, reads ] : [ meta + ['single_end': true], reads[umi_discard_read % 2] ]\n }\n .set { umi_reads }\n }\n }\n\n trim_reads = umi_reads\n trim_unpaired = Channel.empty()\n trim_html = Channel.empty()\n trim_zip = Channel.empty()\n trim_log = Channel.empty()\n trim_read_count = Channel.empty()\n if (!skip_trimming) {\n TRIMGALORE (umi_reads)\n trim_unpaired = TRIMGALORE.out.unpaired\n trim_html = TRIMGALORE.out.html\n trim_zip = TRIMGALORE.out.zip\n trim_log = TRIMGALORE.out.log\n ch_versions = ch_versions.mix(TRIMGALORE.out.versions.first())\n\n //\n // Filter FastQ files based on minimum trimmed read count after adapter trimming\n //\n TRIMGALORE\n .out\n .reads\n .join(trim_log, remainder: true)\n .map {\n meta, reads, trim_log ->\n if (trim_log) {\n num_reads = getTrimGaloreReadsAfterFiltering(meta.single_end ? trim_log : trim_log[-1])\n [ meta, reads, num_reads ]\n } else {\n [ meta, reads, min_trimmed_reads.toFloat() + 1 ]\n }\n }\n .set { ch_num_trimmed_reads }\n\n ch_num_trimmed_reads\n .filter { meta, reads, num_reads -> num_reads >= min_trimmed_reads.toFloat() }\n .map { meta, reads, num_reads -> [ meta, reads ] }\n .set { trim_reads }\n\n ch_num_trimmed_reads\n .map { meta, reads, num_reads -> [ meta, num_reads ] }\n .set { trim_read_count }\n }\n\n emit:\n reads = trim_reads // channel: [ val(meta), [ reads ] ]\n\n fastqc_html // channel: [ val(meta), [ html ] ]\n fastqc_zip // channel: [ val(meta), [ zip ] ]\n\n umi_log // channel: [ val(meta), [ log ] ]\n\n trim_unpaired // channel: [ val(meta), [ reads ] ]\n trim_html // channel: [ val(meta), [ html ] ]\n trim_zip // channel: [ val(meta), [ zip ] ]\n trim_log // channel: [ val(meta), [ txt ] ]\n trim_read_count // channel: [ val(meta), val(count) ]\n\n versions = ch_versions.ifEmpty(null) // channel: [ versions.yml ]\n}\n" }, { "path": "subworkflows/nf-core/fastq_fastqc_umitools_trimgalore/meta.yml", "content": "# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/subworkflows/yaml-schema.json\nname: \"fastq_fastqc_umitools_trimgalore\"\ndescription: Read QC, UMI extraction and trimming\nkeywords:\n - fastq\n - fastqc\n - qc\n - UMI\n - trimming\n - trimgalore\nmodules:\n - fastqc\n - umitools/extract\n - trimgalore\ninput:\n - meta:\n type: map\n description: |\n Groovy Map containing sample information\n e.g. [ id:'test' ]\n - reads:\n type: file\n description: |\n List of input FastQ files of size 1 and 2 for single-end and paired-end data,\n respectively.\n - skip_fastqc:\n type: boolean\n description: |\n Skip fastqc process\n - with_umi:\n type: boolean\n description: |\n With or without umi detection\n - skip_umi_extract:\n type: boolean\n description: |\n With or without umi extrection\n - skip_trimming:\n type: boolean\n description: |\n Allows to skip trimgalore execution\n - umi_discard_read:\n type: integer\n description: |\n Discard R1 / R2 if required\n - min_trimmed_reads:\n type: integer\n description: |\n Inputs with fewer than this reads will be filtered out of the \"reads\" output channel\n\noutput:\n - reads:\n type: file\n description: >\n Extracted FASTQ files. |\n For single-end reads, pattern is \\${prefix}.umi_extract.fastq.gz. |\n For paired-end reads, pattern is \\${prefix}.umi_extract_{1,2}.fastq.gz.\n pattern: \"*.{fastq.gz}\"\n - fastqc_html:\n type: file\n description: FastQC report\n pattern: \"*_{fastqc.html}\"\n - fastqc_zip:\n type: file\n description: FastQC report archive\n pattern: \"*_{fastqc.zip}\"\n - log:\n type: file\n description: Logfile for umi_tools\n pattern: \"*.{log}\"\n - trim_unpaired:\n type: file\n description: |\n FastQ files containing unpaired reads from read 1 or read 2\n pattern: \"*unpaired*.fq.gz\"\n - trim_html:\n type: file\n description: FastQC report (optional)\n pattern: \"*_{fastqc.html}\"\n - trim_zip:\n type: file\n description: FastQC report archive (optional)\n pattern: \"*_{fastqc.zip}\"\n - trim_log:\n type: file\n description: Trim Galore! trimming report\n pattern: \"*_{report.txt}\"\n - trim_read_count:\n type: integer\n description: Number of reads remaining after trimming for all input samples\n - versions:\n type: file\n description: File containing software versions\n pattern: \"versions.yml\"\nauthors:\n - \"@drpatelh\"\n - \"@KamilMaliszArdigen\"\n" }, { "path": "tower.yml", "content": "reports:\n multiqc_report.html:\n display: \"MultiQC HTML report\"\n samplesheet.csv:\n display: \"Auto-created samplesheet with collated metadata and FASTQ paths\"\n macs2_peak.mLb.clN.plots.pdf:\n display: \"Merged library all samples MACS2 peak QC PDF plots\"\n macs2_peak.mRp.clN.plots.pdf:\n display: \"Merged replicate all samples MACS2 peak QC PDF plots\"\n macs2_annotatePeaks.mLb.clN.plots.pdf:\n display: \"Merged library all samples HOMER annotatePeaks.pl QC PDF plots\"\n macs2_annotatePeaks.mRp.clN.plots.pdf:\n display: \"Merged replicate all samples HOMER annotatePeaks.pl QC PDF plots\"\n consensus_peaks.mLb.clN.plots.pdf:\n display: \"Merged library consensus peaks DESeq2 QC PDF plots\"\n consensus_peaks.mRp.clN.plots.pdf:\n display: \"Merged replicate consensus peaks DESeq2 QC PDF plots\"\n consensus_peaks.mLb.clN.boolean.intersect.plot.pdf:\n display: \"Merged library consensus peaks UpSetR intersection PDF plots\"\n consensus_peaks.mRp.clN.boolean.intersect.plot.pdf:\n display: \"Merged replicate consensus peaks UpSetR intersection PDF plots\"\n consensus_peaks.mLb.clN.annotatePeaks.txt:\n display: \"Merged library consensus peaks annotated by HOMER\"\n consensus_peaks.mRp.clN.annotatePeaks.txt:\n display: \"Merged replicate consensus peaks annotated by HOMER\"\n \"*.plotHeatmap.pdf\":\n display: \"Merged library per-sample deepTools plotHeatmap PDF plots\"\n \"*mLb.clN_peaks.broadPeak\":\n display: \"Merged library per-sample MACS2 broadPeak file\"\n \"*mRp.clN_peaks.broadPeak\":\n display: \"Merged replicate per-sample MACS2 broadPeak file\"\n \"*mLb.clN_peaks.narrowPeak\":\n display: \"Merged library per-sample MACS2 narrowPeak file\"\n \"*mRp.clN_peaks.narrowPeak\":\n display: \"Merged replicate per-sample MACS2 narrowPeak file\"\n" }, { "path": "workflows/atacseq.nf", "content": "/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n PRINT PARAMS SUMMARY\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\ninclude { paramsSummaryLog; paramsSummaryMap } from 'plugin/nf-validation'\n\ndef logo = NfcoreTemplate.logo(workflow, params.monochrome_logs)\ndef citation = '\\n' + WorkflowMain.citation(workflow) + '\\n'\ndef summary_params = paramsSummaryMap(workflow)\n\n// Print parameter summary log to screen\nlog.info logo + paramsSummaryLog(workflow) + citation\n\n// Validate input parameters\nWorkflowAtacseq.initialise(params, log)\n\n// Check mandatory parameters\nch_input = file(params.input)\n\n// Check ataqv_mito_reference parameter\nataqv_mito_reference = params.ataqv_mito_reference\nif (!params.ataqv_mito_reference && params.mito_name) {\n ataqv_mito_reference = params.mito_name\n}\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n CONFIG FILES\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\nch_multiqc_config = Channel.fromPath(\"$projectDir/assets/multiqc_config.yml\", checkIfExists: true)\nch_multiqc_custom_config = params.multiqc_config ? Channel.fromPath(params.multiqc_config) : Channel.empty()\nch_multiqc_logo = params.multiqc_logo ? Channel.fromPath(params.multiqc_logo) : Channel.empty()\nch_multiqc_custom_methods_description = params.multiqc_methods_description ? file(params.multiqc_methods_description) : file(\"$projectDir/assets/methods_description_template.yml\", checkIfExists: true)\n\n\n// JSON files required by BAMTools for alignment filtering\nch_bamtools_filter_se_config = file(params.bamtools_filter_se_config)\nch_bamtools_filter_pe_config = file(params.bamtools_filter_pe_config)\n\n// Header files for MultiQC\nch_multiqc_merged_library_peak_count_header = file(\"$projectDir/assets/multiqc/merged_library_peak_count_header.txt\", checkIfExists: true)\nch_multiqc_merged_library_frip_score_header = file(\"$projectDir/assets/multiqc/merged_library_frip_score_header.txt\", checkIfExists: true)\nch_multiqc_merged_library_peak_annotation_header = file(\"$projectDir/assets/multiqc/merged_library_peak_annotation_header.txt\", checkIfExists: true)\nch_multiqc_merged_library_deseq2_pca_header = file(\"$projectDir/assets/multiqc/merged_library_deseq2_pca_header.txt\", checkIfExists: true)\nch_multiqc_merged_library_deseq2_clustering_header = file(\"$projectDir/assets/multiqc/merged_library_deseq2_clustering_header.txt\", checkIfExists: true)\n\nch_multiqc_merged_replicate_peak_count_header = file(\"$projectDir/assets/multiqc/merged_replicate_peak_count_header.txt\", checkIfExists: true)\nch_multiqc_merged_replicate_frip_score_header = file(\"$projectDir/assets/multiqc/merged_replicate_frip_score_header.txt\", checkIfExists: true)\nch_multiqc_merged_replicate_peak_annotation_header = file(\"$projectDir/assets/multiqc/merged_replicate_peak_annotation_header.txt\", checkIfExists: true)\nch_multiqc_merged_replicate_deseq2_pca_header = file(\"$projectDir/assets/multiqc/merged_replicate_deseq2_pca_header.txt\", checkIfExists: true)\nch_multiqc_merged_replicate_deseq2_clustering_header = file(\"$projectDir/assets/multiqc/merged_replicate_deseq2_clustering_header.txt\", checkIfExists: true)\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n IMPORT LOCAL MODULES/SUBWORKFLOWS\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\ninclude { IGV } from '../modules/local/igv'\ninclude { MULTIQC } from '../modules/local/multiqc'\n\n//\n// SUBWORKFLOW: Consisting of a mix of local and nf-core/modules\n//\ninclude { INPUT_CHECK } from '../subworkflows/local/input_check'\ninclude { PREPARE_GENOME } from '../subworkflows/local/prepare_genome'\ninclude { ALIGN_STAR } from '../subworkflows/local/align_star'\ninclude { BIGWIG_PLOT_DEEPTOOLS as MERGED_LIBRARY_BIGWIG_PLOT_DEEPTOOLS } from '../subworkflows/local/bigwig_plot_deeptools'\ninclude { BAM_FILTER_BAMTOOLS as MERGED_LIBRARY_FILTER_BAM } from '../subworkflows/local/bam_filter_bamtools'\ninclude { BAM_BEDGRAPH_BIGWIG_BEDTOOLS_UCSC as MERGED_LIBRARY_BAM_TO_BIGWIG } from '../subworkflows/local/bam_bedgraph_bigwig_bedtools_ucsc'\ninclude { BAM_BEDGRAPH_BIGWIG_BEDTOOLS_UCSC as MERGED_REPLICATE_BAM_TO_BIGWIG } from '../subworkflows/local/bam_bedgraph_bigwig_bedtools_ucsc'\n\ninclude { BAM_PEAKS_CALL_QC_ANNOTATE_MACS2_HOMER as MERGED_LIBRARY_CALL_ANNOTATE_PEAKS } from '../subworkflows/local/bam_peaks_call_qc_annotate_macs2_homer.nf'\ninclude { BAM_PEAKS_CALL_QC_ANNOTATE_MACS2_HOMER as MERGED_REPLICATE_CALL_ANNOTATE_PEAKS } from '../subworkflows/local/bam_peaks_call_qc_annotate_macs2_homer.nf'\ninclude { BED_CONSENSUS_QUANTIFY_QC_BEDTOOLS_FEATURECOUNTS_DESEQ2 as MERGED_LIBRARY_CONSENSUS_PEAKS } from '../subworkflows/local/bed_consensus_quantify_qc_bedtools_featurecounts_deseq2.nf'\ninclude { BED_CONSENSUS_QUANTIFY_QC_BEDTOOLS_FEATURECOUNTS_DESEQ2 as MERGED_REPLICATE_CONSENSUS_PEAKS } from '../subworkflows/local/bed_consensus_quantify_qc_bedtools_featurecounts_deseq2.nf'\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n IMPORT NF-CORE MODULES/SUBWORKFLOWS\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\n//\n// MODULE: Installed directly from nf-core/modules\n//\ninclude { CUSTOM_DUMPSOFTWAREVERSIONS } from '../modules/nf-core/custom/dumpsoftwareversions/main'\ninclude { PICARD_COLLECTMULTIPLEMETRICS as MERGED_LIBRARY_PICARD_COLLECTMULTIPLEMETRICS } from '../modules/nf-core/picard/collectmultiplemetrics/main'\ninclude { PRESEQ_LCEXTRAP as MERGED_LIBRARY_PRESEQ_LCEXTRAP } from '../modules/nf-core/preseq/lcextrap/main'\ninclude { DEEPTOOLS_PLOTFINGERPRINT as MERGED_LIBRARY_DEEPTOOLS_PLOTFINGERPRINT } from '../modules/nf-core/deeptools/plotfingerprint/main'\ninclude { ATAQV_ATAQV as MERGED_LIBRARY_ATAQV_ATAQV } from '../modules/nf-core/ataqv/ataqv/main'\ninclude { ATAQV_MKARV as MERGED_LIBRARY_ATAQV_MKARV } from '../modules/nf-core/ataqv/mkarv/main'\n\ninclude { PICARD_MERGESAMFILES as PICARD_MERGESAMFILES_LIBRARY } from '../modules/nf-core/picard/mergesamfiles/main'\ninclude { PICARD_MERGESAMFILES as PICARD_MERGESAMFILES_REPLICATE } from '../modules/nf-core/picard/mergesamfiles/main'\n\n//\n// SUBWORKFLOW: Consisting entirely of nf-core/modules\n//\ninclude { FASTQ_FASTQC_UMITOOLS_TRIMGALORE } from '../subworkflows/nf-core/fastq_fastqc_umitools_trimgalore/main'\ninclude { FASTQ_ALIGN_BWA } from '../subworkflows/nf-core/fastq_align_bwa/main'\ninclude { FASTQ_ALIGN_BOWTIE2 } from '../subworkflows/nf-core/fastq_align_bowtie2/main'\ninclude { FASTQ_ALIGN_CHROMAP } from '../subworkflows/nf-core/fastq_align_chromap/main'\n\ninclude { BAM_MARKDUPLICATES_PICARD as MERGED_LIBRARY_MARKDUPLICATES_PICARD } from '../subworkflows/nf-core/bam_markduplicates_picard/main'\ninclude { BAM_MARKDUPLICATES_PICARD as MERGED_REPLICATE_MARKDUPLICATES_PICARD } from '../subworkflows/nf-core/bam_markduplicates_picard/main'\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n RUN MAIN WORKFLOW\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\n// Info required for completion email and summary\ndef multiqc_report = []\n\nworkflow ATACSEQ {\n\n ch_versions = Channel.empty()\n\n //\n // SUBWORKFLOW: Uncompress and prepare reference genome files\n //\n PREPARE_GENOME (\n params.aligner\n )\n ch_versions = ch_versions.mix(PREPARE_GENOME.out.versions)\n\n //\n // SUBWORKFLOW: Read in samplesheet, validate and stage input files\n //\n INPUT_CHECK (\n ch_input,\n params.seq_center,\n params.with_control\n )\n ch_versions = ch_versions.mix(INPUT_CHECK.out.versions)\n // TODO: OPTIONAL, you can use nf-validation plugin to create an input channel from the samplesheet with Channel.fromSamplesheet(\"input\")\n // See the documentation https://nextflow-io.github.io/nf-validation/samplesheets/fromSamplesheet/\n // ! There is currently no tooling to help you write a sample sheet schema\n\n //\n // SUBWORKFLOW: Read QC and trim adapters\n //\n FASTQ_FASTQC_UMITOOLS_TRIMGALORE (\n INPUT_CHECK.out.reads,\n params.skip_fastqc || params.skip_qc,\n false,\n false,\n params.skip_trimming,\n 0,\n params.min_trimmed_reads\n )\n ch_versions = ch_versions.mix(FASTQ_FASTQC_UMITOOLS_TRIMGALORE.out.versions)\n\n //\n // SUBWORKFLOW: Alignment with BWA & BAM QC\n //\n ch_genome_bam = Channel.empty()\n ch_genome_bam_index = Channel.empty()\n ch_samtools_stats = Channel.empty()\n ch_samtools_flagstat = Channel.empty()\n ch_samtools_idxstats = Channel.empty()\n if (params.aligner == 'bwa') {\n FASTQ_ALIGN_BWA (\n FASTQ_FASTQC_UMITOOLS_TRIMGALORE.out.reads,\n PREPARE_GENOME.out.bwa_index,\n false,\n PREPARE_GENOME.out.fasta\n .map {\n [ [:], it ]\n }\n )\n ch_genome_bam = FASTQ_ALIGN_BWA.out.bam\n ch_genome_bam_index = FASTQ_ALIGN_BWA.out.bai\n ch_samtools_stats = FASTQ_ALIGN_BWA.out.stats\n ch_samtools_flagstat = FASTQ_ALIGN_BWA.out.flagstat\n ch_samtools_idxstats = FASTQ_ALIGN_BWA.out.idxstats\n ch_versions = ch_versions.mix(FASTQ_ALIGN_BWA.out.versions)\n }\n\n //\n // SUBWORKFLOW: Alignment with BOWTIE2 & BAM QC\n //\n if (params.aligner == 'bowtie2') {\n FASTQ_ALIGN_BOWTIE2 (\n FASTQ_FASTQC_UMITOOLS_TRIMGALORE.out.reads,\n PREPARE_GENOME.out.bowtie2_index,\n params.save_unaligned,\n false,\n PREPARE_GENOME.out.fasta\n .map {\n [ [:], it ]\n }\n )\n ch_genome_bam = FASTQ_ALIGN_BOWTIE2.out.bam\n ch_genome_bam_index = FASTQ_ALIGN_BOWTIE2.out.bai\n ch_samtools_stats = FASTQ_ALIGN_BOWTIE2.out.stats\n ch_samtools_flagstat = FASTQ_ALIGN_BOWTIE2.out.flagstat\n ch_samtools_idxstats = FASTQ_ALIGN_BOWTIE2.out.idxstats\n ch_versions = ch_versions.mix(FASTQ_ALIGN_BOWTIE2.out.versions)\n }\n\n //\n // SUBWORKFLOW: Alignment with CHROMAP & BAM QC\n //\n if (params.aligner == 'chromap') {\n FASTQ_ALIGN_CHROMAP (\n FASTQ_FASTQC_UMITOOLS_TRIMGALORE.out.reads,\n PREPARE_GENOME.out.chromap_index,\n PREPARE_GENOME.out.fasta\n .map {\n [ [:], it ]\n },\n [],\n [],\n [],\n []\n )\n ch_genome_bam = FASTQ_ALIGN_CHROMAP.out.bam\n ch_genome_bam_index = FASTQ_ALIGN_CHROMAP.out.bai\n ch_samtools_stats = FASTQ_ALIGN_CHROMAP.out.stats\n ch_samtools_flagstat = FASTQ_ALIGN_CHROMAP.out.flagstat\n ch_samtools_idxstats = FASTQ_ALIGN_CHROMAP.out.idxstats\n ch_versions = ch_versions.mix(FASTQ_ALIGN_CHROMAP.out.versions)\n }\n\n //\n // SUBWORKFLOW: Alignment with STAR & BAM QC\n //\n ch_star_multiqc = Channel.empty()\n if (params.aligner == 'star') {\n ALIGN_STAR (\n FASTQ_FASTQC_UMITOOLS_TRIMGALORE.out.reads,\n PREPARE_GENOME.out.star_index,\n PREPARE_GENOME.out.fasta\n .map {\n [ [:], it ]\n },\n params.seq_center ?: ''\n )\n ch_genome_bam = ALIGN_STAR.out.bam\n ch_genome_bam_index = ALIGN_STAR.out.bai\n ch_samtools_stats = ALIGN_STAR.out.stats\n ch_samtools_flagstat = ALIGN_STAR.out.flagstat\n ch_samtools_idxstats = ALIGN_STAR.out.idxstats\n ch_star_multiqc = ALIGN_STAR.out.log_final\n ch_versions = ch_versions.mix(ALIGN_STAR.out.versions)\n }\n\n // Create channels: [ meta, [bam] ]\n ch_genome_bam\n .map {\n meta, bam ->\n def meta_clone = meta.clone()\n meta_clone.remove('read_group')\n meta_clone.id = meta_clone.id - ~/_T\\d+$/\n [ meta_clone, bam ]\n }\n .groupTuple(by: [0])\n .map {\n meta, bam ->\n [ meta, bam.flatten() ]\n }\n .set { ch_sort_bam }\n\n //\n // MODULE: Merge resequenced BAM files\n //\n PICARD_MERGESAMFILES_LIBRARY (\n ch_sort_bam\n )\n ch_versions = ch_versions.mix(PICARD_MERGESAMFILES_LIBRARY.out.versions.first())\n\n //\n // SUBWORKFLOW: Mark duplicates in BAM files\n //\n MERGED_LIBRARY_MARKDUPLICATES_PICARD (\n PICARD_MERGESAMFILES_LIBRARY.out.bam,\n PREPARE_GENOME\n .out\n .fasta\n .map {\n [ [:], it ]\n },\n PREPARE_GENOME.out.fai\n .map {\n [ [:], it ]\n }\n )\n ch_versions = ch_versions.mix(MERGED_LIBRARY_MARKDUPLICATES_PICARD.out.versions)\n\n //\n // SUBWORKFLOW: Filter BAM file\n //\n MERGED_LIBRARY_FILTER_BAM (\n MERGED_LIBRARY_MARKDUPLICATES_PICARD.out.bam.join(MERGED_LIBRARY_MARKDUPLICATES_PICARD.out.bai, by: [0]),\n PREPARE_GENOME.out.filtered_bed.first(),\n PREPARE_GENOME\n .out\n .fasta\n .map {\n [ [:], it ]\n },\n ch_bamtools_filter_se_config,\n ch_bamtools_filter_pe_config\n )\n ch_versions = ch_versions.mix(MERGED_LIBRARY_FILTER_BAM.out.versions)\n\n //\n // MODULE: Preseq coverage analysis\n //\n ch_preseq_multiqc = Channel.empty()\n if (!params.skip_preseq) {\n MERGED_LIBRARY_PRESEQ_LCEXTRAP (\n MERGED_LIBRARY_MARKDUPLICATES_PICARD.out.bam\n )\n ch_preseq_multiqc = MERGED_LIBRARY_PRESEQ_LCEXTRAP.out.lc_extrap\n ch_versions = ch_versions.mix(MERGED_LIBRARY_PRESEQ_LCEXTRAP.out.versions.first())\n }\n\n //\n // MODULE: Picard post alignment QC\n //\n ch_picardcollectmultiplemetrics_multiqc = Channel.empty()\n if (!params.skip_picard_metrics) {\n MERGED_LIBRARY_PICARD_COLLECTMULTIPLEMETRICS (\n MERGED_LIBRARY_FILTER_BAM\n .out\n .bam\n .map {\n [ it[0], it[1], [] ]\n },\n PREPARE_GENOME\n .out\n .fasta\n .map {\n [ [:], it ]\n },\n PREPARE_GENOME\n .out\n .fai\n .map {\n [ [:], it ]\n }\n )\n ch_picardcollectmultiplemetrics_multiqc = MERGED_LIBRARY_PICARD_COLLECTMULTIPLEMETRICS.out.metrics\n ch_versions = ch_versions.mix(MERGED_LIBRARY_PICARD_COLLECTMULTIPLEMETRICS.out.versions.first())\n }\n\n //\n // SUBWORKFLOW: Normalised bigWig coverage tracks\n //\n MERGED_LIBRARY_BAM_TO_BIGWIG (\n MERGED_LIBRARY_FILTER_BAM.out.bam.join(MERGED_LIBRARY_FILTER_BAM.out.flagstat, by: [0]),\n PREPARE_GENOME.out.chrom_sizes\n )\n ch_versions = ch_versions.mix(MERGED_LIBRARY_BAM_TO_BIGWIG.out.versions)\n\n //\n // SUBWORKFLOW: Plot coverage across annotation with deepTools\n //\n ch_deeptoolsplotprofile_multiqc = Channel.empty()\n if (!params.skip_plot_profile) {\n MERGED_LIBRARY_BIGWIG_PLOT_DEEPTOOLS (\n MERGED_LIBRARY_BAM_TO_BIGWIG.out.bigwig,\n PREPARE_GENOME.out.gene_bed,\n PREPARE_GENOME.out.tss_bed\n )\n ch_deeptoolsplotprofile_multiqc = MERGED_LIBRARY_BIGWIG_PLOT_DEEPTOOLS.out.plotprofile_table\n ch_versions = ch_versions.mix(MERGED_LIBRARY_BIGWIG_PLOT_DEEPTOOLS.out.versions)\n }\n\n // Create channels: [ meta, [bam], [bai] ] or [ meta, [ bam, control_bam ] [ bai, control_bai ] ]\n MERGED_LIBRARY_FILTER_BAM\n .out\n .bam\n .join(MERGED_LIBRARY_FILTER_BAM.out.bai, by: [0])\n .set { ch_bam_bai }\n\n if (params.with_control) {\n ch_bam_bai\n .map {\n meta, bam, bai ->\n meta.control ? null : [ meta.id, [ bam ] , [ bai ] ]\n }\n .set { ch_control_bam_bai }\n\n ch_bam_bai\n .map {\n meta, bam, bai ->\n meta.control ? [ meta.control, meta, [ bam ], [ bai ] ] : null\n }\n .combine(ch_control_bam_bai, by: 0)\n .map { it -> [ it[1] , it[2] + it[4], it[3] + it[5] ] }\n .set { ch_bam_bai }\n }\n\n //\n // MODULE: deepTools plotFingerprint QC\n //\n ch_deeptoolsplotfingerprint_multiqc = Channel.empty()\n if (!params.skip_plot_fingerprint) {\n MERGED_LIBRARY_DEEPTOOLS_PLOTFINGERPRINT (\n ch_bam_bai\n )\n ch_deeptoolsplotfingerprint_multiqc = MERGED_LIBRARY_DEEPTOOLS_PLOTFINGERPRINT.out.matrix\n ch_versions = ch_versions.mix(MERGED_LIBRARY_DEEPTOOLS_PLOTFINGERPRINT.out.versions.first())\n }\n\n // Create channel: [ val(meta), bam, control_bam ]\n if (params.with_control) {\n ch_bam_bai\n .map {\n meta, bams, bais ->\n [ meta , bams[0], bams[1] ]\n }\n .set { ch_bam_library }\n } else {\n ch_bam_bai\n .map {\n meta, bam, bai ->\n [ meta , bam, [] ]\n }\n .set { ch_bam_library }\n }\n\n //\n // SUBWORKFLOW: Call peaks with MACS2, annotate with HOMER and perform downstream QC\n //\n MERGED_LIBRARY_CALL_ANNOTATE_PEAKS (\n ch_bam_library,\n PREPARE_GENOME.out.fasta,\n PREPARE_GENOME.out.gtf,\n PREPARE_GENOME.out.macs_gsize,\n \".mLb.clN_peaks.annotatePeaks.txt\",\n ch_multiqc_merged_library_peak_count_header,\n ch_multiqc_merged_library_frip_score_header,\n ch_multiqc_merged_library_peak_annotation_header,\n params.narrow_peak,\n params.skip_peak_annotation,\n params.skip_peak_qc\n )\n ch_versions = ch_versions.mix(MERGED_LIBRARY_CALL_ANNOTATE_PEAKS.out.versions)\n\n //\n // SUBWORKFLOW: Consensus peaks analysis\n //\n ch_macs2_consensus_library_bed = Channel.empty()\n ch_featurecounts_library_multiqc = Channel.empty()\n ch_deseq2_pca_library_multiqc = Channel.empty()\n ch_deseq2_clustering_library_multiqc = Channel.empty()\n if (!params.skip_consensus_peaks) {\n MERGED_LIBRARY_CONSENSUS_PEAKS (\n MERGED_LIBRARY_CALL_ANNOTATE_PEAKS.out.peaks,\n ch_bam_library,\n PREPARE_GENOME.out.fasta,\n PREPARE_GENOME.out.gtf,\n ch_multiqc_merged_library_deseq2_pca_header,\n ch_multiqc_merged_library_deseq2_clustering_header,\n params.narrow_peak,\n params.skip_peak_annotation,\n params.skip_deseq2_qc\n )\n ch_macs2_consensus_library_bed = MERGED_LIBRARY_CONSENSUS_PEAKS.out.consensus_bed\n ch_featurecounts_library_multiqc = MERGED_LIBRARY_CONSENSUS_PEAKS.out.featurecounts_summary\n ch_deseq2_pca_library_multiqc = MERGED_LIBRARY_CONSENSUS_PEAKS.out.deseq2_qc_pca_multiqc\n ch_deseq2_clustering_library_multiqc = MERGED_LIBRARY_CONSENSUS_PEAKS.out.deseq2_qc_dists_multiqc\n ch_versions = ch_versions.mix(MERGED_LIBRARY_CONSENSUS_PEAKS.out.versions)\n }\n\n // Create channels: [ meta, bam, bai, peak_file ]\n MERGED_LIBRARY_MARKDUPLICATES_PICARD\n .out\n .bam\n .join(MERGED_LIBRARY_MARKDUPLICATES_PICARD.out.bai, by: [0])\n .join(MERGED_LIBRARY_CALL_ANNOTATE_PEAKS.out.peaks, by: [0])\n .set { ch_bam_peaks }\n\n //\n // MODULE: ATAQV QC\n //\n if (!params.skip_ataqv) {\n MERGED_LIBRARY_ATAQV_ATAQV (\n ch_bam_peaks,\n 'NA',\n ataqv_mito_reference ?: '',\n PREPARE_GENOME.out.tss_bed,\n [],\n PREPARE_GENOME.out.autosomes\n )\n ch_versions = ch_versions.mix(MERGED_LIBRARY_ATAQV_ATAQV.out.versions.first())\n\n MERGED_LIBRARY_ATAQV_MKARV (\n MERGED_LIBRARY_ATAQV_ATAQV.out.json.collect{it[1]}\n )\n ch_versions = ch_versions.mix(MERGED_LIBRARY_ATAQV_MKARV.out.versions)\n }\n\n //\n // Merged replicate analysis\n //\n ch_markduplicates_replicate_stats = Channel.empty()\n ch_markduplicates_replicate_flagstat = Channel.empty()\n ch_markduplicates_replicate_idxstats = Channel.empty()\n ch_markduplicates_replicate_metrics = Channel.empty()\n ch_ucsc_bedgraphtobigwig_replicate_bigwig = Channel.empty()\n ch_macs2_replicate_peaks = Channel.empty()\n ch_macs2_frip_replicate_multiqc = Channel.empty()\n ch_macs2_peak_count_replicate_multiqc = Channel.empty()\n ch_macs2_plot_homer_annotatepeaks_replicate_multiqc = Channel.empty()\n ch_macs2_consensus_replicate_bed = Channel.empty()\n ch_featurecounts_replicate_multiqc = Channel.empty()\n ch_deseq2_pca_replicate_multiqc = Channel.empty()\n ch_deseq2_clustering_replicate_multiqc = Channel.empty()\n if (!params.skip_merge_replicates) {\n\n // Check if we have multiple replicates\n MERGED_LIBRARY_FILTER_BAM\n .out\n .bam\n .map {\n meta, bam ->\n def meta_clone = meta.clone()\n meta_clone.id = meta_clone.id - ~/_REP\\d+$/\n meta_clone.control = meta_clone.control ? meta_clone.control - ~/_REP\\d+$/ : \"\"\n [ meta_clone.id, meta_clone, bam ]\n }\n .groupTuple()\n .map {\n id, metas, bams ->\n if (bams.size() > 1) {\n return [ metas[0], bams ]\n }\n }\n .set { ch_merged_library_replicate_bam }\n\n //\n // MODULE: Merge replicate BAM files\n //\n PICARD_MERGESAMFILES_REPLICATE (\n ch_merged_library_replicate_bam\n )\n ch_versions = ch_versions.mix(PICARD_MERGESAMFILES_REPLICATE.out.versions.first())\n\n //\n // SUBWORKFLOW: Mark duplicates & filter BAM files after merging\n //\n MERGED_REPLICATE_MARKDUPLICATES_PICARD (\n PICARD_MERGESAMFILES_REPLICATE.out.bam,\n PREPARE_GENOME\n .out\n .fasta\n .map {\n [ [:], it ]\n },\n PREPARE_GENOME.out.fai\n .map {\n [ [:], it ]\n }\n )\n ch_markduplicates_replicate_stats = MERGED_REPLICATE_MARKDUPLICATES_PICARD.out.stats\n ch_markduplicates_replicate_flagstat = MERGED_REPLICATE_MARKDUPLICATES_PICARD.out.flagstat\n ch_markduplicates_replicate_idxstats = MERGED_REPLICATE_MARKDUPLICATES_PICARD.out.idxstats\n ch_markduplicates_replicate_metrics = MERGED_REPLICATE_MARKDUPLICATES_PICARD.out.metrics\n ch_versions = ch_versions.mix(MERGED_REPLICATE_MARKDUPLICATES_PICARD.out.versions)\n\n // SUBWORKFLOW: Normalised bigWig coverage tracks\n //\n MERGED_REPLICATE_BAM_TO_BIGWIG (\n MERGED_REPLICATE_MARKDUPLICATES_PICARD.out.bam.join(MERGED_REPLICATE_MARKDUPLICATES_PICARD.out.flagstat, by: [0]),\n PREPARE_GENOME.out.chrom_sizes\n )\n ch_ucsc_bedgraphtobigwig_replicate_bigwig = MERGED_REPLICATE_BAM_TO_BIGWIG.out.bigwig\n ch_versions = ch_versions.mix(MERGED_REPLICATE_BAM_TO_BIGWIG.out.versions)\n\n // Create channels: [ meta, bam, ([] for control_bam) ]\n if (params.with_control) {\n MERGED_REPLICATE_MARKDUPLICATES_PICARD\n .out\n .bam\n .map {\n meta, bam ->\n meta.control ? null : [ meta.id, bam ]\n }\n .set { ch_bam_merged_control }\n\n MERGED_REPLICATE_MARKDUPLICATES_PICARD\n .out\n .bam\n .map {\n meta, bam ->\n meta.control ? [ meta.control, meta, bam ] : null\n }\n .combine( ch_bam_merged_control, by: 0)\n .map { it -> [ it[1] , it[2], it[3] ] }\n .set { ch_bam_replicate }\n } else {\n MERGED_REPLICATE_MARKDUPLICATES_PICARD\n .out\n .bam\n .map {\n meta, bam ->\n [ meta , bam, [] ]\n }\n .set { ch_bam_replicate }\n }\n //\n // SUBWORKFLOW: Call peaks with MACS2, annotate with HOMER and perform downstream QC\n //\n MERGED_REPLICATE_CALL_ANNOTATE_PEAKS (\n ch_bam_replicate,\n PREPARE_GENOME.out.fasta,\n PREPARE_GENOME.out.gtf,\n PREPARE_GENOME.out.macs_gsize,\n \".mRp.clN_peaks.annotatePeaks.txt\",\n ch_multiqc_merged_replicate_peak_count_header,\n ch_multiqc_merged_replicate_frip_score_header,\n ch_multiqc_merged_replicate_peak_annotation_header,\n params.narrow_peak,\n params.skip_peak_annotation,\n params.skip_peak_qc\n )\n ch_macs2_replicate_peaks = MERGED_REPLICATE_CALL_ANNOTATE_PEAKS.out.peaks\n ch_macs2_frip_replicate_multiqc = MERGED_REPLICATE_CALL_ANNOTATE_PEAKS.out.frip_multiqc\n ch_macs2_peak_count_replicate_multiqc = MERGED_REPLICATE_CALL_ANNOTATE_PEAKS.out.peak_count_multiqc\n ch_macs2_plot_homer_annotatepeaks_replicate_multiqc = MERGED_REPLICATE_CALL_ANNOTATE_PEAKS.out.plot_homer_annotatepeaks_tsv\n ch_versions = ch_versions.mix(MERGED_REPLICATE_CALL_ANNOTATE_PEAKS.out.versions)\n\n //\n // SUBWORKFLOW: Consensus peaks analysis\n //\n if (!params.skip_consensus_peaks) {\n MERGED_REPLICATE_CONSENSUS_PEAKS (\n MERGED_REPLICATE_CALL_ANNOTATE_PEAKS.out.peaks,\n ch_merged_library_replicate_bam,\n PREPARE_GENOME.out.fasta,\n PREPARE_GENOME.out.gtf,\n ch_multiqc_merged_replicate_deseq2_pca_header,\n ch_multiqc_merged_replicate_deseq2_clustering_header,\n params.narrow_peak,\n params.skip_peak_annotation,\n params.skip_deseq2_qc\n )\n ch_macs2_consensus_replicate_bed = MERGED_REPLICATE_CONSENSUS_PEAKS.out.consensus_bed\n ch_featurecounts_replicate_multiqc = MERGED_REPLICATE_CONSENSUS_PEAKS.out.featurecounts_summary\n ch_deseq2_pca_replicate_multiqc = MERGED_REPLICATE_CONSENSUS_PEAKS.out.deseq2_qc_pca_multiqc\n ch_deseq2_clustering_replicate_multiqc = MERGED_REPLICATE_CONSENSUS_PEAKS.out.deseq2_qc_dists_multiqc\n ch_versions = ch_versions.mix(MERGED_REPLICATE_CONSENSUS_PEAKS.out.versions)\n }\n }\n\n //\n // MODULE: Create IGV session\n //\n if (!params.skip_igv) {\n IGV (\n PREPARE_GENOME.out.fasta,\n PREPARE_GENOME.out.fai,\n MERGED_LIBRARY_BAM_TO_BIGWIG.out.bigwig.collect{it[1]}.ifEmpty([]),\n MERGED_LIBRARY_CALL_ANNOTATE_PEAKS.out.peaks.collect{it[1]}.ifEmpty([]),\n ch_macs2_consensus_library_bed.collect{it[1]}.ifEmpty([]),\n ch_ucsc_bedgraphtobigwig_replicate_bigwig.collect{it[1]}.ifEmpty([]),\n ch_macs2_replicate_peaks.collect{it[1]}.ifEmpty([]),\n ch_macs2_consensus_replicate_bed.collect{it[1]}.ifEmpty([]),\n \"${params.aligner}/merged_library/bigwig\",\n { [\"${params.aligner}/merged_library/macs2\",\n params.narrow_peak? '/narrow_peak' : '/broad_peak'\n ].join('') },\n { [\"${params.aligner}/merged_library/macs2\",\n params.narrow_peak? '/narrow_peak' : '/broad_peak',\n \"/consensus\"\n ].join('') },\n \"${params.aligner}/merged_replicate/bigwig\",\n { [\"${params.aligner}/merged_replicate/macs2\",\n params.narrow_peak? '/narrow_peak' : '/broad_peak'\n ].join('') },\n { [\"${params.aligner}/merged_replicate/macs2\",\n params.narrow_peak? '/narrow_peak' : '/broad_peak',\n \"/consensus\"\n ].join('') },\n )\n ch_versions = ch_versions.mix(IGV.out.versions)\n }\n\n //\n // MODULE: Pipeline reporting\n //\n CUSTOM_DUMPSOFTWAREVERSIONS (\n ch_versions.unique().collectFile(name: 'collated_versions.yml')\n )\n\n //\n // MODULE: MultiQC\n //\n if (!params.skip_multiqc) {\n workflow_summary = WorkflowAtacseq.paramsSummaryMultiqc(workflow, summary_params)\n ch_workflow_summary = Channel.value(workflow_summary)\n\n methods_description = WorkflowAtacseq.methodsDescriptionText(workflow, ch_multiqc_custom_methods_description, params)\n ch_methods_description = Channel.value(methods_description)\n\n MULTIQC (\n ch_multiqc_config,\n ch_multiqc_custom_config.collect().ifEmpty([]),\n CUSTOM_DUMPSOFTWAREVERSIONS.out.mqc_yml.collect(),\n ch_workflow_summary.collectFile(name: 'workflow_summary_mqc.yaml'),\n\n FASTQ_FASTQC_UMITOOLS_TRIMGALORE.out.fastqc_zip.collect{it[1]}.ifEmpty([]),\n FASTQ_FASTQC_UMITOOLS_TRIMGALORE.out.trim_zip.collect{it[1]}.ifEmpty([]),\n FASTQ_FASTQC_UMITOOLS_TRIMGALORE.out.trim_log.collect{it[1]}.ifEmpty([]),\n\n ch_samtools_stats.collect{it[1]}.ifEmpty([]),\n ch_samtools_flagstat.collect{it[1]}.ifEmpty([]),\n ch_samtools_idxstats.collect{it[1]}.ifEmpty([]),\n\n MERGED_LIBRARY_MARKDUPLICATES_PICARD.out.stats.collect{it[1]}.ifEmpty([]),\n MERGED_LIBRARY_MARKDUPLICATES_PICARD.out.flagstat.collect{it[1]}.ifEmpty([]),\n MERGED_LIBRARY_MARKDUPLICATES_PICARD.out.idxstats.collect{it[1]}.ifEmpty([]),\n MERGED_LIBRARY_MARKDUPLICATES_PICARD.out.metrics.collect{it[1]}.ifEmpty([]),\n\n MERGED_LIBRARY_FILTER_BAM.out.stats.collect{it[1]}.ifEmpty([]),\n MERGED_LIBRARY_FILTER_BAM.out.flagstat.collect{it[1]}.ifEmpty([]),\n MERGED_LIBRARY_FILTER_BAM.out.idxstats.collect{it[1]}.ifEmpty([]),\n ch_picardcollectmultiplemetrics_multiqc.collect{it[1]}.ifEmpty([]),\n\n ch_preseq_multiqc.collect{it[1]}.ifEmpty([]),\n\n ch_deeptoolsplotprofile_multiqc.collect{it[1]}.ifEmpty([]),\n ch_deeptoolsplotfingerprint_multiqc.collect{it[1]}.ifEmpty([]),\n\n MERGED_LIBRARY_CALL_ANNOTATE_PEAKS.out.frip_multiqc.collect{it[1]}.ifEmpty([]),\n MERGED_LIBRARY_CALL_ANNOTATE_PEAKS.out.peak_count_multiqc.collect{it[1]}.ifEmpty([]),\n MERGED_LIBRARY_CALL_ANNOTATE_PEAKS.out.plot_homer_annotatepeaks_tsv.collect().ifEmpty([]),\n ch_featurecounts_library_multiqc.collect{it[1]}.ifEmpty([]),\n\n ch_markduplicates_replicate_stats.collect{it[1]}.ifEmpty([]),\n ch_markduplicates_replicate_flagstat.collect{it[1]}.ifEmpty([]),\n ch_markduplicates_replicate_idxstats.collect{it[1]}.ifEmpty([]),\n ch_markduplicates_replicate_metrics.collect{it[1]}.ifEmpty([]),\n\n ch_macs2_frip_replicate_multiqc.collect{it[1]}.ifEmpty([]),\n ch_macs2_peak_count_replicate_multiqc.collect{it[1]}.ifEmpty([]),\n ch_macs2_plot_homer_annotatepeaks_replicate_multiqc.collect().ifEmpty([]),\n ch_featurecounts_replicate_multiqc.collect{it[1]}.ifEmpty([]),\n\n ch_deseq2_pca_library_multiqc.collect().ifEmpty([]),\n ch_deseq2_clustering_library_multiqc.collect().ifEmpty([]),\n ch_deseq2_pca_replicate_multiqc.collect().ifEmpty([]),\n ch_deseq2_clustering_replicate_multiqc.collect().ifEmpty([])\n )\n multiqc_report = MULTIQC.out.report.toList()\n }\n}\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n COMPLETION EMAIL AND SUMMARY\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n\nworkflow.onComplete {\n if (params.email || params.email_on_fail) {\n NfcoreTemplate.email(workflow, params, summary_params, projectDir, log, multiqc_report)\n }\n\n if (params.hook_url) {\n NfcoreTemplate.IM_notification(workflow, params, summary_params, projectDir, log)\n }\n\n NfcoreTemplate.summary(workflow, params, log)\n}\n\n/*\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n THE END\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n*/\n" } ]