From 04f6cb2671d65f75a8bd4cc6ba4fc851b7df46c7 Mon Sep 17 00:00:00 2001 From: Rylobyte Date: Fri, 2 Oct 2026 08:49:24 -0400 Subject: [PATCH 01/52] Prepare MetaPathways 3.5.2 Nextflow workflows, reports and release testing --- .github/pull_request_template.md | 14 + .github/workflows/release.yml | 28 +- .github/workflows/smoke.yml | 20 +- .gitignore | 4 + .readthedocs.yaml | 31 -- CITATION.cff | 33 ++ MANIFEST.in | 15 + Makefile | 2 +- README.md | 509 +++++++++++++++--- conda_recipe/meta_template.yaml | 8 +- dev/abund_calc.py | 90 ++-- dev/gff2gtf.py | 27 +- dev/pgdb_build_wf.py | 128 +++-- dev/ptRNAscan.py | 3 +- docker/README.quay.md | 2 + docker/conda_base.yml | 4 +- docker/conda_dev.yml | 2 - docs/benchmarking.md | 118 ++++ docs/cli-reference.md | 508 +++++++++++++++++ docs/commands.md | 98 ++++ docs/conda_env.yml | 5 - docs/getting-started.md | 111 ++++ docs/inputs.md | 113 ++++ docs/pathway-tools.md | 169 ++++++ docs/pr-testing.md | 16 + docs/release-readiness.md | 28 + docs/releasing.md | 63 ++- docs/reports-tutorial.md | 84 +++ docs/reproducibility.md | 59 ++ docs/requirements.txt | 1 - docs/results-schema.md | 137 +++++ docs/reviewer-test.md | 103 ++++ docs/src/conf.py | 59 -- docs/src/index.rst | 31 -- docs/src/install.rst | 34 -- docs/src/overview.rst | 108 ---- docs/src/quick_start.rst | 58 -- docs/src/reproducibility.rst | 133 ----- docs/src/static/glyph.png | Bin 129109 -> 0 bytes docs/src/usage.rst | 316 ----------- docs/workflow.md | 206 +++++++ metapathways/MetaPathways_annotate_fast.py | 28 +- .../MetaPathways_create_genbank_ptinput.py | 8 +- metapathways/MetaPathways_func_search.py | 104 ++-- metapathways/MetaPathways_refscore.py | 15 +- metapathways/MetaPathways_tpm.py | 134 ++--- metapathways/_version.py | 2 +- metapathways/analysis_workflow.py | 374 +++++++++++++ metapathways/build_DBs/metacyc_build_ont.py | 17 +- .../build_DBs/metacyc_mapping_build.py | 6 +- metapathways/cli_logging.py | 41 ++ metapathways/execution.py | 9 +- metapathways/jobscreator.py | 24 +- metapathways/metacyc_db.py | 181 +++++++ metapathways/metapathways_utils.py | 2 +- metapathways/nextflow.py | 459 ++++++++++++++++ metapathways/nf_databases.py | 132 +++++ metapathways/nf_worker.py | 165 ++++++ metapathways/pipeline.py | 391 ++++++++------ metapathways/pt_container.py | 385 +++++++++++++ metapathways/pt_ec.py | 19 + metapathways/pt_sequences.py | 153 ++++++ metapathways/pt_taxonomy.py | 41 ++ .../Gastrointestinal_5.selection.log | 11 + metapathways/regtests/cami_reviewer/README.md | 32 ++ .../cami_reviewer/Skin_28.selection.log | 11 + .../cami_reviewer/Urogenital_22.selection.log | 11 + metapathways/regtests/cami_reviewer/all.tsv | 4 + .../assemblies/Gastrointestinal_5.fasta.gz | Bin 0 -> 42451 bytes .../inputs/assemblies/Skin_28.fasta.gz | Bin 0 -> 41985 bytes .../inputs/assemblies/Urogenital_22.fasta.gz | Bin 0 -> 42805 bytes .../inputs/mag_maps/Gastrointestinal_5.tsv | 3 + .../cami_reviewer/inputs/mag_maps/Skin_28.tsv | 3 + 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scripts/generate_cli_docs.py | 34 ++ scripts/prepare_cami_reviewer.py | 159 ++++++ scripts/release.py | 21 +- setup.py | 11 +- tests/release/test_release.py | 11 + tests/test_analysis_workflow.py | 189 +++++++ tests/test_fast_isolation.py | 81 +++ tests/test_metacyc_db.py | 98 ++++ tests/test_nextflow.py | 270 ++++++++++ tests/test_pt_container.py | 331 ++++++++++++ tests/test_pt_sequences.py | 144 +++++ tests/test_pt_taxonomy.py | 37 ++ tests/test_read_mapping.py | 190 +++++++ tests/test_reporting.py | 151 ++++++ tests/test_rna_abundance.py | 96 ++++ 108 files changed, 7814 insertions(+), 1355 deletions(-) create mode 100644 .github/pull_request_template.md delete mode 100644 .readthedocs.yaml create mode 100644 CITATION.cff create mode 100644 docs/benchmarking.md create mode 100644 docs/cli-reference.md create mode 100644 docs/commands.md delete mode 100644 docs/conda_env.yml create mode 100644 docs/getting-started.md create mode 100644 docs/inputs.md create mode 100644 docs/pathway-tools.md create mode 100644 docs/pr-testing.md create mode 100644 docs/release-readiness.md create mode 100644 docs/reports-tutorial.md create mode 100644 docs/reproducibility.md delete mode 100644 docs/requirements.txt create mode 100644 docs/results-schema.md create mode 100644 docs/reviewer-test.md delete mode 100644 docs/src/conf.py delete mode 100644 docs/src/index.rst delete mode 100644 docs/src/install.rst delete mode 100644 docs/src/overview.rst delete mode 100644 docs/src/quick_start.rst delete mode 100644 docs/src/reproducibility.rst delete mode 100644 docs/src/static/glyph.png delete mode 100644 docs/src/usage.rst create mode 100644 docs/workflow.md create mode 100644 metapathways/analysis_workflow.py create mode 100644 metapathways/cli_logging.py create mode 100644 metapathways/metacyc_db.py create mode 100644 metapathways/nextflow.py create mode 100644 metapathways/nf_databases.py create mode 100644 metapathways/nf_worker.py create mode 100644 metapathways/pt_container.py create mode 100644 metapathways/pt_ec.py create mode 100644 metapathways/pt_sequences.py create mode 100644 metapathways/pt_taxonomy.py create mode 100644 metapathways/regtests/cami_reviewer/Gastrointestinal_5.selection.log create mode 100644 metapathways/regtests/cami_reviewer/README.md create mode 100644 metapathways/regtests/cami_reviewer/Skin_28.selection.log create mode 100644 metapathways/regtests/cami_reviewer/Urogenital_22.selection.log create mode 100644 metapathways/regtests/cami_reviewer/all.tsv create mode 100644 metapathways/regtests/cami_reviewer/inputs/assemblies/Gastrointestinal_5.fasta.gz create mode 100644 metapathways/regtests/cami_reviewer/inputs/assemblies/Skin_28.fasta.gz create mode 100644 metapathways/regtests/cami_reviewer/inputs/assemblies/Urogenital_22.fasta.gz create mode 100644 metapathways/regtests/cami_reviewer/inputs/mag_maps/Gastrointestinal_5.tsv create mode 100644 metapathways/regtests/cami_reviewer/inputs/mag_maps/Skin_28.tsv create mode 100644 metapathways/regtests/cami_reviewer/inputs/mag_maps/Urogenital_22.tsv create mode 100644 metapathways/regtests/cami_reviewer/inputs/reads/Gastrointestinal_5_R1.fastq.gz create mode 100644 metapathways/regtests/cami_reviewer/inputs/reads/Gastrointestinal_5_R2.fastq.gz create mode 100644 metapathways/regtests/cami_reviewer/inputs/reads/Skin_28_R1.fastq.gz create mode 100644 metapathways/regtests/cami_reviewer/inputs/reads/Skin_28_R2.fastq.gz create mode 100644 metapathways/regtests/cami_reviewer/inputs/reads/Urogenital_22_R1.fastq.gz create mode 100644 metapathways/regtests/cami_reviewer/inputs/reads/Urogenital_22_R2.fastq.gz create mode 100644 metapathways/regtests/cami_reviewer/pair.tsv create mode 100644 metapathways/regtests/cami_reviewer/provenance.json create mode 100644 metapathways/regtests/cami_reviewer/single.tsv create mode 100644 metapathways/regtests/cami_reviewer/validation.json create mode 100644 metapathways/report_assets/EDA_portal.html create mode 100644 metapathways/report_assets/portal.css create mode 100644 metapathways/report_assets/portal.js create mode 100644 metapathways/report_server.py create mode 100644 metapathways/reporting.py create mode 100644 scripts/check_docs.py create mode 100644 scripts/check_installed_assets.py create mode 100644 scripts/generate_cli_docs.py create mode 100644 scripts/prepare_cami_reviewer.py create mode 100644 tests/test_analysis_workflow.py create mode 100644 tests/test_fast_isolation.py create mode 100644 tests/test_metacyc_db.py create mode 100644 tests/test_nextflow.py create mode 100644 tests/test_pt_container.py create mode 100644 tests/test_pt_sequences.py create mode 100644 tests/test_pt_taxonomy.py create mode 100644 tests/test_read_mapping.py create mode 100644 tests/test_reporting.py create mode 100644 tests/test_rna_abundance.py diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md new file mode 100644 index 0000000..a4d5a7e --- /dev/null +++ b/.github/pull_request_template.md @@ -0,0 +1,14 @@ +## Problem and resulting behavior + +Describe the concrete change and any compatibility implications. + +## Validation + +- Tested commit: +- Local tests and installed-package checks: +- Single/two-sample reviewer workflow and checkpoint reuse: +- Report/explorer and CSV export: +- Optional Pathway Tools and Slurm checks (or explicitly untested): +- Nonpublishing Release workflow/artifact links: + +See [the tester checklist](https://github.com/hallamlab/MetaPathways/blob/feat/nextflow-controller-db-build/docs/pr-testing.md). Confirm single-server and Slurm benchmark review plus independent tester sign-off before merging to dev/master. Do not include licensed installers/images, credentials, or production outputs. diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index 0a7ccea..420544f 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -9,6 +9,10 @@ on: description: 'Existing tag to publish/recover (blank = build only)' type: string default: '' + test_containers: + description: 'Build/test Docker and SIF without publishing when release_tag is blank' + type: boolean + default: false source_run_id: description: 'Optional successful build run to reuse; requires release_tag' type: string @@ -57,10 +61,13 @@ jobs: if: inputs.source_run_id == '' run: | conda install --yes --override-channels -c conda-forge conda-build conda-index pyyaml 'setuptools>=83,<85' wheel - python -m pip install build + python -m pip install build pandas pybedtools pyfastx tqdm scipy - name: Test release controls if: inputs.source_run_id == '' run: python -m unittest discover -s tests/release -v + - name: Test scheduling, containers, and read mapping + if: inputs.source_run_id == '' + run: python -m unittest discover -s tests -p 'test_*.py' -v - name: Build and test release if: inputs.source_run_id == '' env: @@ -165,7 +172,10 @@ jobs: containers: needs: [build, github-release] - if: github.ref_type == 'tag' || inputs.release_tag != '' + if: >- + always() && needs.build.result == 'success' && + ((needs.github-release.result == 'success' && (github.ref_type == 'tag' || inputs.release_tag != '')) || + (github.ref_type != 'tag' && inputs.release_tag == '' && inputs.test_containers)) runs-on: ubuntu-24.04 timeout-minutes: 90 permissions: @@ -190,7 +200,14 @@ jobs: - name: Build Docker and Apptainer; validate containers env: RELEASE_TAG: ${{ inputs.release_tag || github.ref_name }} - run: python scripts/release.py container-build --ref "$RELEASE_TAG" + RELEASE_REF_TYPE: ${{ github.ref_type }} + RELEASE_TAG_INPUT: ${{ inputs.release_tag }} + run: | + if [[ "$RELEASE_REF_TYPE" == tag || -n "$RELEASE_TAG_INPUT" ]]; then + python scripts/release.py container-build --ref "$RELEASE_TAG" + else + python scripts/release.py container-build + fi - name: Scan container for fixable high and critical vulnerabilities run: | mkdir -p dist/security @@ -224,13 +241,14 @@ jobs: path: dist/containers/ if-no-files-found: warn - name: Attach validated SIF and checksums to GitHub release + if: github.ref_type == 'tag' || inputs.release_tag != '' env: GH_TOKEN: ${{ github.token }} GH_REPO: ${{ github.repository }} RELEASE_TAG: ${{ inputs.release_tag || github.ref_name }} run: python scripts/release.py container-attach --ref "$RELEASE_TAG" - name: Publish Docker image to Quay - if: vars.PUBLISH_QUAY == 'true' + if: (github.ref_type == 'tag' || inputs.release_tag != '') && vars.PUBLISH_QUAY == 'true' env: QUAY_USERNAME: ${{ secrets.QUAY_USERNAME }} QUAY_PASSWORD: ${{ secrets.QUAY_PASSWORD }} @@ -246,7 +264,7 @@ jobs: printf '%s' "$QUAY_PASSWORD" | docker login quay.io --username "$QUAY_USERNAME" --password-stdin python scripts/release.py container-push --ref "$RELEASE_TAG" - name: Synchronize Quay repository overview - if: vars.PUBLISH_QUAY == 'true' + if: (github.ref_type == 'tag' || inputs.release_tag != '') && vars.PUBLISH_QUAY == 'true' env: QUAY_API_TOKEN: ${{ secrets.QUAY_API_TOKEN }} run: | diff --git a/.github/workflows/smoke.yml b/.github/workflows/smoke.yml index 6c3b110..5de5769 100644 --- a/.github/workflows/smoke.yml +++ b/.github/workflows/smoke.yml @@ -2,9 +2,9 @@ name: Package and documentation smoke tests on: push: - branches: [dev] + branches: [master, main, dev, "feat/**"] pull_request: - branches: [dev] + branches: [master, main, dev] workflow_dispatch: permissions: @@ -21,21 +21,27 @@ jobs: - uses: actions/setup-python@v6 with: python-version: '3.11' - - name: Install build, documentation, and CLI import dependencies + - name: Install build and CLI import dependencies run: >- python -m pip install build 'setuptools>=83,<85' wheel - pandas pybedtools pyfastx tqdm scipy -r docs/requirements.txt + pandas pybedtools pyfastx tqdm scipy pyyaml cffconvert + - name: Validate software citation metadata + run: cffconvert --validate - name: Test release controls run: python -m unittest discover -s tests/release -v + - name: Test scheduling, containers, and read mapping + run: python -m unittest discover -s tests -p 'test_*.py' -v - name: Build source and wheel distributions run: python -m build --no-isolation - name: Check installed CLI outside the source directory run: | python -m pip install --no-deps dist/*.whl + cp scripts/check_installed_assets.py "$RUNNER_TEMP/check_installed_assets.py" cd "$RUNNER_TEMP" + python check_installed_assets.py metapathways version - for command in run build_db mag_split ptools; do + for command in run analysis_wf build_db mag_split build_pt ptools report; do metapathways "$command" -h done - - name: Build documentation with warnings treated as errors - run: sphinx-build -W --keep-going -b html docs/src docs/build + - name: Check GitHub documentation and CLI reference + run: python scripts/check_docs.py diff --git a/.gitignore b/.gitignore index dd4943d..a6ac4de 100644 --- a/.gitignore +++ b/.gitignore @@ -85,3 +85,7 @@ global_errors_warnings.txt # Local manuscript figures and their export tools /docs/figures/ + +# Nextflow local metadata; invocation copies are retained with analysis outputs. +/.nextflow/ +/.nextflow.log* diff --git a/.readthedocs.yaml b/.readthedocs.yaml deleted file mode 100644 index c9e01cc..0000000 --- a/.readthedocs.yaml +++ /dev/null @@ -1,31 +0,0 @@ -# Read the Docs configuration file for Sphinx projects -# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details - -# Required -version: 2 - -# Set the OS, Python version and other tools you might need -build: - os: ubuntu-22.04 - tools: - python: "3.10" - # You can also specify other tool versions: - # nodejs: "19" - # rust: "1.64" - # golang: "1.19" - -# Build documentation in the "docs/" directory with Sphinx -sphinx: - configuration: docs/src/conf.py - -# Optionally build your docs in additional formats such as PDF and ePub -# formats: -# - pdf -# - epub - -# Optional but recommended, declare the Python requirements required -# to build your documentation -# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html -python: - install: - - requirements: docs/requirements.txt diff --git a/CITATION.cff b/CITATION.cff new file mode 100644 index 0000000..5ab7654 --- /dev/null +++ b/CITATION.cff @@ -0,0 +1,33 @@ +cff-version: 1.2.0 +message: "Please cite this software and record the release version or Git commit used in your analysis." +type: software +title: MetaPathways +abstract: "A metagenomic analysis pipeline for functional and taxonomic annotation, abundance estimation, genome-bin splitting, pathway inference, and interactive exploration of linked result tables." +repository-code: "https://github.com/hallamlab/MetaPathways" +url: "https://github.com/hallamlab/MetaPathways" +license: MIT +authors: + - family-names: McLaughlin + given-names: Ryan J. + - family-names: Liu + given-names: Tony X. + - family-names: Altman + given-names: Tomer + - family-names: Nallan + given-names: Aditi N. + - family-names: Hahn + given-names: Aria S. + - family-names: Anstett + given-names: Julia + - family-names: Morgan-Lang + given-names: Connor + - family-names: Konwar + given-names: Kishori M. + - family-names: Hallam + given-names: Steven J. +keywords: + - metagenomics + - functional annotation + - pathways + - Nextflow +version: "3.5.2" diff --git a/MANIFEST.in b/MANIFEST.in index 9a73a6e..8de6505 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -13,5 +13,20 @@ recursive-include scripts *.py recursive-include conda_recipe *.py *.yaml include docker/conda_base.yml recursive-include tests/release *.py +include tests/test_read_mapping.py +include tests/test_pt_container.py +include tests/test_nextflow.py include docker/Dockerfile.release include docker/README.quay.md + +recursive-include metapathways/report_assets *.html *.js *.css +include tests/test_reporting.py +recursive-include docs *.md + +include tests/test_analysis_workflow.py +include tests/test_rna_abundance.py +include tests/test_metacyc_db.py +include tests/test_fast_isolation.py +include tests/test_pt_sequences.py + +include CITATION.cff diff --git a/Makefile b/Makefile index aec4b77..5d84101 100644 --- a/Makefile +++ b/Makefile @@ -194,7 +194,7 @@ deploy-conda: release-upload-conda ### Docs: docs-local: - sphinx-build ./docs/src ./docs/build + $(PYTHON) scripts/check_docs.py ### Build & Install Extensions ## diff --git a/README.md b/README.md index 540ce8b..c6fbc67 100644 --- a/README.md +++ b/README.md @@ -1,104 +1,487 @@ # MetaPathways -Functional and taxonomic annotation of environmental genomes, with community- and population-level pathway inference. +Functional and taxonomic annotation of genomes and metagenomes, with community- and MAG-level pathway inference. MetaPathways (MP) takes assemblies, optionally maps reads, creates Pathway Tools inputs, and organizes the results for downstream analysis. -## Quickstart +This source revision uses **Nextflow behind the MP CLI**, supports local and Slurm execution, builds isolated Pathway Tools containers, and provides a searchable results portal. These additions are under development on `feat/nextflow-controller-db-build`; an older published `3.5.1` package or image does **not** necessarily include them. Record the Git revision as well as the package version. -**Linux x86-64 · Conda/Mamba · included K12 example.** Install and run in a writable environment with internet access: +## Start here -```bash -mamba create -n metapathways_env --override-channels \ - -c hallamlab -c conda-forge -c bioconda metapathways=3.5.1 -mamba activate metapathways_env -metapathways --version +New to the terminal? Follow the chapters in order. Already installed MP? Start with the reviewer walkthrough or choose a command below. All documentation is maintained here on GitHub; a separate Read the Docs site is not required. + +1. **[Getting started](docs/getting-started.md):** terminal basics, installation, activation and your first result. +2. **[Reviewer walkthrough](docs/reviewer-test.md):** three tiny CAMI samples for single-sample and two-sample CLI tests, including reads, genome splitting and reports; Pathway Tools is optional. +3. **[Organize your inputs](docs/inputs.md):** automatic matching, symbolic links, custom sample IDs/manifests and genome maps. +4. **[Command cookbook](docs/commands.md):** each module's purpose, required inputs, commands and outputs. +5. **[Pathway Tools](docs/pathway-tools.md):** where to obtain the licensed installer, one-command image builds, MetaCyc reference preparation, taxonomy, transport inference and troubleshooting. +6. **[Explore and export](docs/reports-tutorial.md):** reports, SSH access, related tables and filtered CSVs. +7. **[Resources and Slurm](#resources-and-slurm):** per-tool threads, total budgets, cluster submission and restart behavior. +8. **[Benchmarking](docs/benchmarking.md):** resource measurements, supplementary tables, figures and interpretation limits. +9. **[Maintainer release guide](docs/releasing.md):** PR testing, Conda/Quay publication and Zenodo setup; [current readiness audit](docs/release-readiness.md). + +### Quick start after installation -mkdir -p ~/metapathways-review -cd ~/metapathways-review +Activate the environment, then run the small included installation example: + +```bash +conda activate metapathways +mkdir -p ~/mp-reviewer +cd ~/mp-reviewer metapathways build_db --test metapathways run --test +metapathways report -o test --serve --no-rebuild ``` -**Check the result:** outputs are in `test/k12_test/`. Inspect -`metapathways_steps_log.txt` for successful stages and `errors_warnings_log.txt` -for problems; do not rely on the exit code alone. Key outputs are -`results/annotation_table/k12_test.functional_and_taxonomic_table.txt`, -`genbank/k12_test.gbk`, and `results/rpkm/k12_test.contig_counts.tsv`. +This downloads support records, uses small bundled references, and checks annotation plus paired-read abundance. It does **not** run Pathway Tools or reproduce the manuscript benchmark. Continue to the [reviewer walkthrough](docs/reviewer-test.md) for the complete workflow. On a remote server, follow [SSH browser access](docs/reports-tutorial.md#view-a-remote-report-through-ssh). + +### Which command do I need? -The example includes small K12 FASTA/FASTQ and SwissProt/SILVA fixtures. Database -preparation downloads ExPASy enzyme records and NCBI taxonomy and writes indexes -inside the installed package. This is an installation test; it does not reproduce -the manuscript's CAMI2 benchmark or run Pathway Tools. +| Goal | Command | +| --- | --- | +| Complete workflow for one or many metagenomes | `metapathways analysis_wf` | +| Annotate assemblies, optionally map reads | `metapathways run` | +| Prepare reference databases | `metapathways build_db` | +| Build/register a licensed Pathway Tools SIF | `metapathways build_pt` | +| Split existing community annotations into genome bins | `metapathways mag_split` | +| Infer pathways from prepared community/MAG inputs | `metapathways ptools` | +| Browse existing outputs and export subsets | `metapathways report` | -[Docker / Apptainer instructions](docker/README.quay.md) · -[Release downloads](https://github.com/hallamlab/MetaPathways/releases) · -[Full usage](https://metapathways.readthedocs.io/en/latest/usage.html) · -[Benchmark provenance](docs/src/reproducibility.rst) +### Reference chapters -[![Version 3.5.1](https://img.shields.io/badge/Version-3.5.1-blue.svg)](https://github.com/hallamlab/MetaPathways/releases) -[![Python 3.11](https://img.shields.io/badge/Python-3.11-blue.svg)](https://www.python.org/) -[![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE) +| Guide | Contents | +| --- | --- | +| [CLI reference](docs/cli-reference.md) | Every command, flag and default, generated from current CLI help | +| [Result schema](docs/results-schema.md) | Table units, keys, joins, missing data and SQLite examples | +| [Workflow and output reference](docs/workflow.md) | Stages, directories, caching and detailed diagnostics | +| [Reproducibility](docs/reproducibility.md) | Software/reference records, historical provenance and validation limits | +| [Containers](docker/README.quay.md) | Released MP Docker/Apptainer images; distinct from your licensed Pathway Tools SIF | +| [Maintainer releases](docs/releasing.md) | Packaging, release checks and publication | -## Install this source revision +The remainder of this README is a compact working reference. The linked chapters provide the step-by-step explanations. -For development on Linux x86-64 with Python 3.11: +## Installation + +### Install this source revision + +Use Linux x86-64 with Conda or Mamba. The bundled native executables target that platform. The environment supplies Python, Nextflow, Java through its dependencies, Apptainer and the annotation tools. ```bash git clone https://github.com/hallamlab/MetaPathways.git cd MetaPathways +git checkout feat/nextflow-controller-db-build mamba env create -f docker/conda_base.yml -mamba activate metapathways -mamba install -c conda-forge pip wheel 'setuptools>=83,<85' -python -m pip install --no-deps --no-build-isolation . +conda activate metapathways +python -m pip install --no-deps --no-build-isolation -e . +metapathways version +metapathways run --help +``` + +Use the release tag or branch you intend to evaluate; do not mix an old package's documentation with this checkout. Editable installation makes local code changes visible to the CLI. Install without `-e` for a fixed source installation. + +For MAG splitting and pathway extraction, also install: + +```bash +python -m pip install \ + 'git+https://github.com/hallamlab/MAGSplitter.git@main' \ + 'git+https://bitbucket.org/tomeraltman/camelot-frs@dev#egg=camelot-frs' +``` + +These are moving Git dependencies. Save `pip freeze`, a Conda explicit export and the MP Git commit with your analysis. The report and portal use Python's standard-library SQLite and HTTP server; no web service, JavaScript package installation or external account is required. + +### Published packages and containers + +For a published stable version, use the matching [GitHub release](https://github.com/hallamlab/MetaPathways/releases) and its documentation. The [container guide](docker/README.quay.md) explains Docker and Apptainer images. Installing the released package is distinct from installing the development features described above. + +## Try the included example + +In a writable environment with this checkout installed: + +```bash +mkdir -p ~/metapathways-example +cd ~/metapathways-example +metapathways build_db --test +metapathways run --test +``` + +`build_db --test` indexes the included small SwissProt/SILVA fixtures and downloads ExPASy enzyme records and NCBI taxonomy. It requires internet access and writes to the installed package's test database directory. `run --test` uses the included K12 assembly and paired reads and writes `test/k12_test/`. + +Open `test/reports/MP_run_report.html` for an output inventory, or launch the explorer: + +```bash +metapathways report -o test --serve --no-rebuild +``` + +Check task status and the sample's `errors_warnings_log.txt` as well as the report. This example is an installation check; it does not run Pathway Tools or reproduce the manuscript benchmark. + +## Prepare reference databases + +For a minimal reference database: + +```bash +metapathways build_db -d /data/MPDB --func swissprot -a fast +``` + +SILVA and supporting enzyme/taxonomy files are built alongside functional references. Select multiple functional databases with `--func swissprot cazy uniref50`; `uniref90` is also supported and substantially larger. `-a blast` builds BLAST indexes instead of FAST indexes. Use `--dryrun` to inspect the planned downloads and indexing jobs first. + +The builder downloads public references from their configured upstream locations. These are not all version-pinned. eggNOG requires a local FASTA at `MPDB/functional/eggnog`; the old builder had no working eggNOG acquisition rule. Licensed MetaCyc reference acquisition is separate from this public builder. Existing compatible MPDB installations can be used directly with `-d`. + +Choose annotation databases actually present in your MPDB. The FAST/BLAST choice in `run` must match its indexes. Keep reference release records and checksums; changing a database can change biological results. + +## Annotate your own data + +### One assembly + +```bash +metapathways run \ + -i sample.fasta \ + -o results \ + -d /data/MPDB +``` + +The sample output is `results/sample/`; the run-wide report is `results/reports/`. Input can be nucleotide FASTA, compressed FASTA, or amino-acid FASTA with `--input_format fasta-amino`. GFF and GenBank are output formats, not accepted primary inputs of this CLI. + +Choose references and inspect the plan: + +```bash +metapathways run -i sample.fasta -o results -d /data/MPDB \ + --annotation_dbs swissprot cazy --annotation_algorithm FAST --dryrun +``` + +A dry run checks dependencies and writes the execution plan and logs without executing annotation tasks. It can create sample directory scaffolding; it does not produce a completed biological report. + +### Read mapping + +Paired reads in separate files: + +```bash +metapathways run -i sample.fasta -o results -d /data/MPDB \ + -1 sample_R1.fastq.gz -2 sample_R2.fastq.gz +``` + +Interleaved paired reads: + +```bash +metapathways run -i sample.fasta -o results -d /data/MPDB \ + -1 sample.interleaved.fastq.gz --interleaved ``` -Tagged releases validate packages and containers through the -[release workflow](docs/releasing.md). Record the release build or container digest -used for a review. Optional MAG splitting and Pathway Tools commands require -additional dependencies; see the [full usage documentation](https://metapathways.readthedocs.io/en/latest/usage.html). +Single-end reads use `-1` alone. With no reads, abundance calculation is skipped. `-1` and `-2` must identify different files; MP now rejects identical paired input paths, including aliases to the same file. The paired command passes the actual reverse file to CoverM. + +Historical output generated by the incorrect mate selection must not be treated as corrected merely because it appears in a report. Repeating the annotation command with the corrected reads can reuse completed annotation stages and recompute mapping. The portal copies existing abundance values; it does not certify their provenance or rerun mapping. + +### Multiple assemblies + +Pass a directory of FASTA files to `-i`; each file becomes a sample with its own output directory. Use unique, simple filenames and `--samples` to select a subset. Read mapping arguments apply to one sample only: run separate commands for samples with different FASTQs. CPU/memory budgets are per invocation, so independent MP commands do not share a global resource limit. + +### Stage controls + +Stage flags accept `yes`, `skip` or `redo`. For example: + +```bash +metapathways run -i sample.fasta -o results -d /data/MPDB \ + --COMPUTE_TPM redo -1 sample_R1.fastq.gz -2 sample_R2.fastq.gz +``` -## Inputs, outputs, and reproducibility +`yes` reuses valid outputs, `redo` executes the stage again, and `skip` requires any needed downstream inputs to already exist. `--force_redo` forces all annotation stages. Changes to tracked inputs or outputs invalidate task receipts. See the [workflow guide](docs/workflow.md) before skipping dependencies. -`metapathways run` accepts nucleotide FASTA or amino-acid FASTA (`--input_format -fasta-amino`). Paired or interleaved FASTQ reads can be supplied for abundance -estimation. The current CLI does not accept GFF or GenBank as primary inputs. +## MAGs and pathway inference -Results include annotation tables, annotated GFF/GenBank files, predicted -sequences, abundance tables when reads are supplied, run statistics, and Pathway -Tools input files. Reference databases are prepared separately with -`metapathways build_db`; see [reproducibility notes](docs/src/reproducibility.rst) -for dependency versions, output locations, and the manuscript benchmark provenance. -The small included example is an installation test, not a reproduction of the -manuscript's CAMI2 performance benchmark. +### Build Pathway Tools once + +Follow the [Pathway Tools licensing and installer guide](docs/pathway-tools.md#get-the-installer) to obtain your licensed Linux x86-64 installer, then provide it to MP: + +```bash +metapathways build_pt \ + -i ./pathway-tools-29.5-linux-64-tier1-install \ + -o ./containers +``` + +Nextflow runs the Apptainer build, validates Pathway Tools startup, and registers the finished SIF in `~/.config/metapathways/ptools.json`. Subsequent `ptools` commands use that image automatically. Without `-o`, images go under `~/.local/share/metapathways/containers`; the XDG equivalents are honored. `--image` on `ptools` or `METAPATHWAYS_PTOOLS_IMAGE` overrides registration. + +Apptainer must support unprivileged builds on your host. Where subordinate UID/GID mappings are configured, its `newuidmap` and `newgidmap` helpers must be installed by the system administrator (Ubuntu provides them in `uidmap`). Building needs internet access for the base image and operating-system packages. Docker is not required. The installer itself is supplied by you; MP does not obtain a license. + +`build_pt -t` controls compression CPUs, default two. If shared storage makes package installation slow, set `APPTAINER_TMPDIR` to sufficiently large local scratch. Startup validation has been exercised with 29.5; do not assume every installer release has the same unattended interface. If the installer was renamed, supply `--ptools_version 29.5` explicitly. + +Every explicit `build_pt` invocation fetches the installer release's official Linux patches from SRI over HTTPS, following the [vendor's patch installation instructions](https://bioinformatics.ai.sri.com/ptools/faq.html). There is no prompt and no custom Pathway Tools code or MetaCyc data patch. Failed patch downloads stop the build. The build loads these patches before freezing the SIF; analysis invocations disable further patch downloads. Each invocation creates a separate image, preserving existing images. The adjacent `.sif.json` records installer/image/recipe hashes, patch source URLs and individual checksums, snapshot hash, and startup validation output; the patch manifest is also embedded in the image. Keep this private image to reproduce its exact patch set. + +New images include NCBI BLAST+ and its configuration. Before registration, validation creates and searches a tiny synthetic protein database, then checks Pathway Tools startup. This BLAST installation supports Pathway Tools' own sequence databases and hole filling; it is separate from the FAST/BLAST annotation indexes in MPDB. Installing official patches or BLAST does not establish that any particular Pathway Tools inference failure has been fixed. + +### MetaCyc from Pathway Tools + +To build the SIF and prepare its bundled MetaCyc reference in an existing MPDB with one command: + +```bash +metapathways build_pt \ + -i ./pathway-tools-29.5-linux-64-tier1-install \ + -o ./containers -d /path/to/MPDB -a fast +``` + +Use `-a blast` for BLAST annotation indexes instead. Nextflow first builds and validates the SIF, then exports its bundled MetaCyc flat files alongside `protseq.fsa` in private staging. It runs the repository's `metacyc_mapping_build.py` and `metacyc_build_ont.py`, checks the reference files and tables, indexes the proteins, and installs: + +| Location relative to MPDB | Contents | +| --- | --- | +| `functional/metacyc` | Protein FASTA from the selected MetaCyc release | +| `functional/formatted/metacyc.*` | Selected FAST or BLAST indexes | +| `functional/formatted/metacyc-names.txt` | Protein identifiers and descriptions | +| `functional_categories/MetaCyc-monomer-rxn-pairs.tsv` | Protein-to-reaction mappings, including containing complexes | +| `functional_categories/MetaCyc-PWY-RXN-CMP-map.tsv` | Pathway, reaction, enzyme and primary compound mappings | +| `functional_categories/MetaCyc_PWY_Ontology.tsv` | Pathway ontology | +| `functional_categories/MetaCyc_reldate.txt`, `MetaCyc_provenance.json` | Release, source/image hashes, input checksums and mapping counts | + +The MetaCyc preparation task uses one CPU. Other MPDB references are not refreshed. Preparation replaces the existing MetaCyc reference and removes obsolete MetaCyc index files, including indexes for the other aligner, so run it when no analyses are reading that MPDB. Annotation runs must use the selected index format. Proteins without reaction mappings are counted in provenance; absence of a reaction assignment is permitted. + +To add MetaCyc later using the registered SIF: + +```bash +metapathways build_db -d /path/to/MPDB --func metacyc -a fast +``` -## Abstract +Select a particular SIF with `--metacyc_source /path/to/pathway-tools.sif`, or provide a complete licensed flat-file `data/` directory. That directory must contain `protseq.fsa`, `proteins.dat`, `enzrxns.dat`, `reactions.dat`, `pathways.dat`, `compounds.dat`, and `classes.dat`. A FASTA alone cannot supply the reaction and pathway mappings. Native installations may contain only sequence files in `data/` because their remaining reference data are built into the executable; the SIF export handles this. Files supplied over SFTP must first be copied locally. -The development of high-throughput sequencing technologies over the past decade has generated a tidal wave of environmental sequence information from a variety of natural and human engineered ecosystems. The resulting flood of information into public databases and archived sequencing projects has exponentially expanded computational resource requirements rendering most local homology-based search methods inefficient. MetaPathways v1.0 is a modular annotation and analysis pipeline for constructing environmental Pathway/Genome Databases (ePGDBs) from environmental sequence information capable of using the Sun Grid engine for external resource partitioning. However, a command-line interface and facile task management introduced user activation barriers with concomitant decrease in fault tolerance. +MetaCyc is opt-in and is not downloaded by the ordinary default `build_db` command. The user supplies the licensed installation/data and remains responsible for its permitted use; MP does not grant a license or publish the installer, reference data, patches, or SIF. `--dryrun` plans either route without exporting references, fetching patches, indexing, or registering an image. -MetaPathways has since advanced as a modular tool, deepening our understanding of microbial metabolism at various biological levels. With this release, we have addressed previous challenges in modularity and database management. v3.5 enhances user accessibility through streamlined installation via package indexes or containers, refined modules, and interface upgrades. It boasts updated algorithm support for sequence feature prediction, annotation, metabolic inference, and coverage metrics. Tested on mock community data, Metapathways v3.5 demonstrates improved performance and usability. With automated installation and database management, this open-source tool makes advanced metagenomic analysis more accessible. Metapathways v3.5 represents a significant step forward in automated, comprehensive metagenomic analysis, facilitating a deeper exploration of microbial interactions and metabolic functions in environmental genomics. +### Community pathways + +```bash +metapathways ptools -o results/sample --taxprune --taxonomic_scope all +``` + +These examples explicitly use broad cellular-life taxonomic pruning, a tested workaround for the separate unpruned rescoring failure in Pathway Tools 29.5. It is not proven equivalent to unpruned inference; see [scope choices](docs/pathway-tools.md#choose-a-taxonomic-scope). + +Each SIF task gets private Pathway Tools data, home and temporary state, allowing concurrent isolated instances. Pathway Tools uses one CPU per PGDB. A community PGDB failure fails the command. Native Pathway Tools is still supported when no image is selected, but serialized to protect shared state. The legacy `--container` flag retains its original meaning and bypasses automatic SIF selection. + +### Add MAG pathways without reannotating + +Create a tab-separated map with **no header**, containing original assembly contig identifiers and MAG identifiers: + +```text +original_contig_1 MAG_001 +original_contig_2 MAG_001 +original_contig_3 MAG_002 +``` + +Then run: + +```bash +metapathways mag_split -o results/sample -m contig_to_mag.tsv +metapathways ptools -o results/sample --taxprune --taxonomic_scope all +``` + +MAG splitting reuses the community annotation and contig mapping. It also preserves the supplied map at `magsplitter/contig_to_mag.tsv`, allowing the report to connect all retained MAG contigs and their ORFs. MAG Pathway Tools inputs are a smaller, selected set and are shown separately. + +Pathway Tools can fail for individual MAGs. These failures are recorded and allowed to remain optional; they do not fail an otherwise successful community workflow. Missing or failed inference is not equivalent to “zero pathways.” Inspect `entities` and execution history in the portal. `--taxprune` enables taxonomic pruning; the default leaves it off. + +## Reports and the EDA portal + +Successful `run`, `mag_split` and `ptools` commands refresh the report automatically. When a sample belongs to an existing parent report, the parent report is refreshed so all samples remain accessible. Report indexing runs on the controller after Nextflow completes, uses SQLite on disk, and does not repeat annotation, mapping or pathway inference. + +For existing or partial results, build a report independently: + +```bash +metapathways report -o results +``` + +`-o` can be one sample output directory or a parent containing sample directories as immediate children. Reports are saved under: + +```text +results/reports/ +├── MP_run_report.html # Accounting, import notes, files and execution links +├── EDA_portal.html # Search and export interface +├── results.sqlite # Relational data for all included samples +├── schema.json # Columns, row counts, keys and relationships +├── output_inventory.tsv # Paths, sizes and modification times +├── portal.js +└── portal.css +``` + +Open `MP_run_report.html` directly for navigation. To search, subset and export: + +```bash +metapathways report -o results --serve --no-rebuild +``` + +This opens a browser and serves the existing snapshot on loopback only. Omit `--no-rebuild` to refresh changed results first. `--no-browser` prints the URL; `--port 8765` chooses a fixed local port. Ctrl-C stops the server. All assets are local, and the explorer makes no third-party requests. Copy the complete output directory to a workstation to retain file links; no cloud upload is involved. + +The workflow in the portal is: + +1. Choose a table: ORFs/taxonomy, functional annotations, pathways, pathway genes, MAG membership, abundance or file inventory. +2. Search text, add column filters, or filter ORF-based tables by linked EC/reaction, reference database and pathway/entity identifiers. +3. Follow a row's related-result buttons. Sample, pathway and entity keys remain attached, avoiding cross-sample collisions. +4. Select export columns, apply filters, and export **all matching rows** as CSV. Pagination does not truncate an export. +5. Save the query definition or bookmark its URL to record your selection. + +The portal is a table explorer: it adds no biological plots or interpretation. The [schema guide](docs/results-schema.md) explains row units, relation keys, safe joins and the distinction between missing output and biological absence. Large joins remain in SQLite; CSV is streamed rather than assembled entirely in browser memory. Broad scans can still take time. Each query has a two-minute execution budget, and at most four queries execute concurrently. + +The full inventory links remaining RNA, sequence, alignment, statistics and raw PGDB products. The relational views cover the recognized formats documented in the schema guide; an arbitrary legacy table is not silently assumed to fit that schema. Missing primary annotations leave explicit placeholder ORFs and import notes; malformed recognized tables stop the rebuild and preserve the previous database. + +## Complete multi-sample analysis + +`analysis_wf` runs annotation, optional read mapping, optional MAG splitting, community/MAG pathway inference, and a combined report. It accepts one or many metagenomes. All computational tasks share **one Nextflow DAG and one resource budget**; samples do not wait for other samples to finish. Community PGDB construction, read mapping, and MAG splitting can proceed together once their annotation inputs are ready. MAG PGDB jobs follow splitting. + +### Analysis wf input layout + +Use this exact layout for automatic discovery (directory and sample names are case-sensitive): + +```text +inputs/ + assemblies/ + SampleA.fasta + SampleB.fasta + reads/ + SampleA_R1.fastq.gz + SampleA_R2.fastq.gz + SampleB_interleaved.fastq.gz + mag_maps/ + SampleA.tsv + SampleB.tsv +``` + +Assembly suffixes are `.fa`, `.fna`, or `.fasta`, optionally `.gz`. Read suffixes are `.fq` or `.fastq`, optionally `.gz`. Read names must end with `_R1` and `_R2` for paired files, `_interleaved` for interleaved pairs, or `_single` for single-end reads. Sample IDs use letters, digits and underscores, beginning with a letter. Names `logs`, `reports`, `inputs`, `assemblies`, `reads`, and `mag_maps` are reserved. + +Every assembly needs exactly one read layout and one map by default. Each map is a **headerless, two-column TSV**: original assembly contig ID, then MAG ID. A contig may appear only once, and its ID must match the assembly FASTA header's first whitespace-delimited token. MAG IDs use letters, digits, underscores and periods, beginning with a letter. Periods become underscores in MAG output directory names; IDs that collide after that conversion are rejected. `community` and IDs containing `non_binned` are reserved. + +```bash +metapathways analysis_wf \ + -i /path/to/inputs \ + -o /path/to/analysis \ + -d /path/to/MPDB \ + --threads 8 --max_cpus 32 +``` + +The registered SIF from `metapathways build_pt` is used automatically; `--image /path/to/ptools.sif` overrides it. Container isolation allows multiple single-CPU Pathway Tools jobs. Annotation tasks default to 16 GB each and PGDB jobs to 4 GB (`--ptools_memory`); memory availability can limit concurrency before CPUs do. Slurm uses the same resource flags described below and requires all inputs, outputs, software and the SIF to be accessible on compute nodes. + +For existing flat directories, point `-i` at the assemblies directory and supply `--reads_dir /path/to/reads` and `--mag_maps_dir /path/to/maps`. If only one of those flags is supplied, the other branch defaults to `reads/` or `mag_maps/` under `-i`. Use `--no_reads` or `--no_mags` to explicitly omit those branches for every sample during discovery. Use `--skip_ptools` to omit PGDB construction while retaining annotation, read mapping, MAG splitting and reporting. The manifest below supports a different combination for each sample. + +Discovery does not recurse, merge sequencing lanes, or guess unmarked FASTQ layouts. Unexpected files/subdirectories, duplicate assembly names, orphan reads/maps, missing mates, reused input files, duplicate contig IDs and map IDs absent from their assembly stop the command **before any jobs are submitted**, with a link to this section. Hidden directory entries are ignored. Explicitly disabled branches are not scanned. Assembly headers and maps are checked fully; FASTQ files are checked for readability and nonzero size, not full sequencing integrity. + +Append `--dryrun` to validate inputs and write the combined task plan without running biological tools. This still creates output directories, logs, staged symlinks and `inputs.resolved.tsv`. Remove `--dryrun` from the same command to execute. Input paths may contain spaces because MP stages symlinks; the output and MPDB paths must currently use letters, digits, underscores, hyphens, periods and slashes for compatibility with legacy tool commands. + +### Custom analysis manifest + +Use a tab-separated file with this **exact header and column order**: + +```text +sample_id assembly read_layout reads_1 reads_2 mag_map +SampleA assemblies/assembly_a.fasta paired reads/a_1.fq.gz reads/a_2.fq.gz maps/a.tsv +SampleB assemblies/assembly_b.fasta interleaved reads/b.fq.gz maps/b.tsv +SampleC assemblies/assembly_c.fasta none "" "" "" +``` + +The example uses actual tabs, with `""` denoting empty fields in the final row. Paths are relative to the manifest's directory or absolute. `read_layout` is `paired`, `interleaved`, `single`, or `none`. Paired reads require both paths; single/interleaved reads require only `reads_1`; `none` requires both paths empty. A blank `mag_map` omits MAG splitting and MAG PGDBs for that sample. Community PGDB construction still runs unless `--skip_ptools` is supplied. Sample IDs come from the manifest, so original filenames do not need to match them. Assemblies must still have a supported FASTA suffix. + +```bash +metapathways analysis_wf \ + --manifest /path/to/samples.tsv \ + -o /path/to/analysis -d /path/to/MPDB \ + --threads 8 --max_cpus 32 +``` + +Do not combine `--manifest` with `-i`, discovery-directory flags, `--no_reads` or `--no_mags`. The single-sample `-1`, `-2`, `--interleaved`, `--samples` and `--test` options are not used by `analysis_wf`; each row declares its own reads and sample ID. Required annotation stages cannot be skipped; successful tasks are reused through receipts. + +### Outputs, restarting and exploration + +Each sample writes to `analysis/SAMPLE/`. The dataset root contains `inputs.resolved.tsv` with absolute original paths, combined `reports/`, and `logs/analysis_wf/RUN/` with the plan, tool logs, resource trace and task statuses. Staged symlinks and receipts stay under `.metapathways/analysis_wf/`; temporary Nextflow work/cache cleanup follows the ordinary MP resource options. + +Repeat the same command/output to resume. The first invocation requires a new output directory. A changed sample list, MAG ID set, or input path mapping requires a new output directory; this prevents silently mixing datasets. Input contents, commands and resource requests are checked through task receipts, and completed outputs without a matching receipt are not adopted by this workflow. `--force_redo` reruns all selected annotation, splitting and PGDB tasks. Do not run another MP command into the same output while an analysis is active. + +A community PGDB failure is a required-task failure. MAG PGDB failures are expected for some MAGs: they are logged as optional failures and do not stop the remaining MAGs. A MAG with no retained `0.pf` input after successful splitting is recorded as `SKIPPED`. The combined report retains per-sample/entity task statuses, including failures and skips. + +After completion, open `analysis/reports/MP_run_report.html`, or start the searchable explorer: + +```bash +metapathways report -o /path/to/analysis --serve --no-rebuild +``` + +The portal combines samples and keeps sample IDs on all related records so identically named MAGs and ORFs in different samples remain distinct. + +## Resources and Slurm + +### Local execution is the default + +| Setting | Default / meaning | +| --- | --- | +| `run -t / --threads` | Eight CPUs per threaded tool, capped by total CPU budget | +| Threaded tools | pProdigal, barrnap, ptRNAscan, FAST, BLAST, CoverM, featureCounts, and samtools sort | +| Serial stages | One CPU each, including Pathway Tools and Python parsers; native math pools are capped too | +| `--max_cpus` | CPUs available to the process, including affinity/cgroup limits | +| `--memory` | Per-task reservation: normally 16 GB; standalone `ptools` defaults to 4 GB | +| `analysis_wf --ptools_memory` | PGDB task reservation within the complete workflow; 4 GB by default | +| `--max_memory` | Currently available host memory, bounded by cgroups | +| `--max_tasks` | Additional concurrency cap; CPU/memory reservations still apply | +| `build_db -t` | Legacy total CPU budget; omitted means available CPUs | +| `build_pt -t` | Image-compression CPUs | + +For example, permit a total of 16 CPUs while allowing eight threads per capable tool: + +```bash +metapathways run -i sample.fasta -o results -d /data/MPDB \ + -t 8 --max_cpus 16 --max_memory '64 GB' +``` + +Independent reference searches may run together, and Nextflow schedules as many eligible tasks as fit their reservations. Memory reservations are scheduling requests, not measured peaks; local execution does not impose a container memory ceiling. Each MP invocation has its own budget. `--threads` controls each threaded task, while `--max_cpus` controls the total: for example, a 16-CPU budget can fit two eight-CPU jobs, one eight-CPU job plus eight single-CPU jobs, or sixteen single-CPU jobs when dependencies and memory permit. ptRNAscan uses that many single-threaded tRNAscan-SE workers; samtools receives one fewer additional thread so its main thread fits the reservation. Thread counts are upper bounds: small inputs and serial portions of a tool may use fewer CPUs. These settings apply when planning a new invocation; they do not resize running jobs. + +### Submit from a Slurm headnode + +Run from an authenticated login/head node where `sbatch`, `squeue` and `scancel` are available: + +```bash +metapathways run -i /shared/sample.fasta -o /shared/results -d /shared/MPDB \ + --executor slurm --account my_project --partition compute \ + -t 8 --max_cpus 32 --max_memory '64 GB' --max_tasks 4 --time_limit 24h +``` + +MP uses your existing Slurm identity; it does not take a password or SSH private key. `--qos` and `--reservation` are optional. Inputs, outputs, references, work/cache paths, the MP installation and its environment must have the same absolute paths on compute nodes. Pathway Tools on Slurm requires a SIF. The report's HTML explorer runs locally; it is not a Slurm service. + +Protected Slurm defaults are 32 aggregate CPUs, 64 GB aggregate reserved memory, at most four submitted jobs, six submissions per minute and 24 hours per task. The job cap is conservatively reduced using the largest CPU/memory request in the plan. This can leave capacity unused for small stages. Adjust `--submit_rate` and other limits to your site's policy. There are no automatic task retries. MP uses an explicit Nextflow configuration so ambient profiles do not silently override these limits. + +Live Slurm execution still needs validation at your site. Configuration and synthetic local scheduling tests do not establish compatibility with every cluster's authentication, filesystem or resource policies. + +## Logs, temporary files and restarting + +Every command with an output location saves its CLI transcript under `OUTPUT/logs/cli/`. Workflow invocations also retain: + +```text +OUTPUT/logs/COMMAND/RUN_ID/ +├── console.log # Controller and labeled tool output +├── tasks.json # Commands, dependencies, resources and paths +├── tasks/ # Individual output logs and status records +├── summary.json # Invocation outcome and per-task results +├── nextflow.log +├── nextflow_tasks/ # Archived .command.* diagnostics +├── trace.tsv +├── report.html +├── timeline.html +├── main.nf +└── nextflow.config +``` -## Team and repository +Console output is displayed and saved. Reports link the retained Nextflow records. Original sample logs remain available as well. Historical workflows without trace files cannot retrospectively gain CPU/RAM measurements by generating a report. -**Current Team:** Ryan J. McLaughlin, Tony X. Liu, Tomer Altman, Aditi N. Nallan, Aria S. Hahn, Julia Anstett, Connor Morgan-Lang, Kishori M. Konwar, and Steven J. Hallam +Default Nextflow work, session cache and Conda package/environment caches live under `OUTPUT/.metapathways/COMMAND/tmp/RUN_ID`. After a completed invocation, including an ordinary task failure, diagnostics are archived and these temporary directories are removed. Interrupted invocations retain them because cancellation may still be in progress. -**Previous Team Members:** Niels W. Hanson and Shang-Ju Wu +Use `--keep_work` to retain the defaults. Explicit `--work_dir` and `--conda_cache` paths are retained automatically; MP does not delete a user-provided shared cache. Nextflow's installed runtime and MP's Conda environment are not per-run caches and are retained. -The canonical source is [hallamlab/MetaPathways](https://github.com/hallamlab/MetaPathways). Earlier code is preserved separately in [MetaPathways-legacy](https://github.com/hallamlab/MetaPathways-legacy). +Durable receipts remain under `OUTPUT/.metapathways/COMMAND/receipts`. Repeating a command checks tracked inputs, outputs and command signatures, permitting reuse even after temporary cleanup. Never remove final outputs expecting receipts alone to recover them. To force one annotation stage, use its `redo` flag; `--force_redo` reruns all annotation stages. Old read-mapping output without a current receipt is deliberately recomputed once. -## [Documentation](https://metapathways.readthedocs.io/en/latest/) +## Troubleshooting and reproducibility -## Support +- **A command fails before execution:** check the CLI/error logs, activate the environment and use `command -v nextflow coverm fastal` to check dependencies. +- **A task exceeds the memory budget:** lower concurrency or adjust `--memory`/`--max_memory` to measured requirements; Slurm can enforce its allocation. +- **Some MAG pathways are missing:** inspect the entity's last task status and logs. Expected MAG inference failure is distinct from missing annotation inputs. +- **The portal says local explorer required:** launch `metapathways report -o OUTPUT --serve --no-rebuild` and open the URL it prints. +- **Results were changed after report generation:** rebuild the report. It is an indexed snapshot, not a live view of files. +- **An old output has no complete MAG map:** preserve its original two-column map as `SAMPLE/magsplitter/contig_to_mag.tsv` before rebuilding. The identifiers must match that sample's original contig names. +- **A report rebuild fails:** inspect the named source and expected schema. Fix/correct the source or report importer; do not invent missing identifiers or replace absent values with zero. -[Technical questions, bug reports, and general inquires can be made here.](https://github.com/hallamlab/MetaPathways/issues) +Record commands, Git commit, software versions, reference versions/checksums and input checksums for reproducible work. See [reproducibility notes](docs/reproducibility.md) for the historical benchmark and the distinction between installation tests, synthetic software tests and full biological validation. -## Citation +## Team, support and citation -If you use MetaPathways in your research, please cite the following article: +Current team: Ryan J. McLaughlin, Tony X. Liu, Tomer Altman, Aditi N. Nallan, Aria S. Hahn, Julia Anstett, Connor Morgan-Lang, Kishori M. Konwar and Steven J. Hallam. Previous contributors include Niels W. Hanson and Shang-Ju Wu. -> Ryan J. McLaughlin, Tony X. Liu, Tomer Altman, Aditi N. Nallan, Aria S. Hahn, Julia Anstett, Connor Morgan-Lang, Kishori M. Konwar, Steven J. Hallam. *MetaPathways v3.5: Modularity and Scalability Improvements for Pathway Inference from Environmental Genomes* bioRxiv (2024): 2024-06. [doi: https://doi.org/10.1101/2024.06.04.597460](https://doi.org/10.1101/2024.06.04.597460) +Source: [hallamlab/MetaPathways](https://github.com/hallamlab/MetaPathways). Historical code: [MetaPathways-legacy](https://github.com/hallamlab/MetaPathways-legacy). Questions and bug reports: [GitHub issues](https://github.com/hallamlab/MetaPathways/issues). License: [MIT](LICENSE), with bundled third-party license notices retained. +Please cite: -## Maintainer releases +> McLaughlin RJ, Liu TX, Altman T, Nallan AN, Hahn AS, Anstett J, Morgan-Lang C, Konwar KM, Hallam SJ. *MetaPathways v3.5: Modularity and Scalability Improvements for Pathway Inference from Environmental Genomes*. bioRxiv (2024). [doi:10.1101/2024.06.04.597460](https://doi.org/10.1101/2024.06.04.597460). -Use [the release controller and CI workflow](docs/releasing.md) to set a version, -build and test packages, and publish downloadable GitHub releases and optional -Anaconda.org packages. The source version is declared in `metapathways/_version.py`. +Maintainers: use the [release controller and CI workflow](docs/releasing.md). The source version is declared in `metapathways/_version.py`. No release or benchmark is launched by editing this documentation. diff --git a/conda_recipe/meta_template.yaml b/conda_recipe/meta_template.yaml index 660719a..62d2715 100644 --- a/conda_recipe/meta_template.yaml +++ b/conda_recipe/meta_template.yaml @@ -9,7 +9,7 @@ source: build: # The bundled FAST/metacount executables target Linux x86-64. skip: true # [not (linux and x86_64)] - number: 1 + number: 0 script: "{{ PYTHON }} -m pip install . --no-deps --no-build-isolation -vv" entry_points: @@ -21,6 +21,12 @@ test: - metapathways version - metapathways run --help - metapathways build_db --help + - metapathways analysis_wf --help + - metapathways build_pt --help + - metapathways mag_split --help + - metapathways ptools --help + - metapathways report --help + - nextflow -version requirements: host: diff --git a/dev/abund_calc.py b/dev/abund_calc.py index 9629248..c756de8 100644 --- a/dev/abund_calc.py +++ b/dev/abund_calc.py @@ -42,60 +42,58 @@ def calculate_tpm(counts, gene_lengths): return tpm_values +def abundance_table(counts_file, gtf_file, gene_lengths_file=None): + """One abundance row per featureCounts gene ID, using its union feature length.""" + counts_df = pd.read_csv(counts_file, sep="\t", index_col=0, comment="#") + if counts_df.index.has_duplicates: + raise ValueError("featureCounts contains duplicate gene IDs") + if 'Length' in counts_df: + lengths = pd.to_numeric(counts_df['Length'], errors='raise') + elif gene_lengths_file: + legacy = pd.read_csv(gene_lengths_file, sep="\t", index_col=0, header=None) + if legacy.index.has_duplicates or set(legacy.index) != set(counts_df.index): + raise ValueError("Legacy gene lengths must contain each counted gene ID exactly once") + lengths = pd.to_numeric(legacy.iloc[:, 0].reindex(counts_df.index), errors='raise') + else: + raise ValueError("Missing featureCounts Length column") + counts = pd.to_numeric(counts_df.iloc[:, -1], errors='raise') + if not np.isfinite(lengths).all() or (lengths <= 0).any(): + raise ValueError("Gene lengths must be finite and positive") + if not np.isfinite(counts).all() or (counts < 0).any(): + raise ValueError("Counts must be finite and nonnegative") + results = pd.DataFrame({ + 'Gene_ID': counts_df.index, 'Count': counts.to_numpy(), + 'Length': lengths.to_numpy(), + 'RPKM': calculate_rpkm(counts, lengths) if counts.sum() else np.zeros(len(counts)), + 'TPM': calculate_tpm(counts, lengths) if counts.sum() else np.zeros(len(counts)), + }) + columns = ['seqname', 'source', 'feature', 'start', 'end', 'score', 'strand', 'frame', 'attributes'] + gtf = pd.read_csv(gtf_file, sep="\t", comment="#", header=None, names=columns, + dtype=str, keep_default_na=False) + gtf['Gene_ID'] = gtf['attributes'].str.extract(r'(?:^|;)\s*gene_id "([^"]+)"') + if gtf['Gene_ID'].isna().any(): + raise ValueError("GTF row is missing gene_id") + missing = set(counts_df.index) - set(gtf['Gene_ID']) + uncounted = set(gtf['Gene_ID']) - set(counts_df.index) + if missing or uncounted: + raise ValueError(f'Gene IDs differ between counts and GTF: missing from GTF={sorted(missing)[:5]}, missing from counts={sorted(uncounted)[:5]}') + if gtf['Gene_ID'].duplicated().any(): + duplicates = gtf.loc[gtf['Gene_ID'].duplicated(), 'Gene_ID'].unique()[:5] + raise ValueError(f"GTF contains duplicate gene IDs: {list(duplicates)}. Regenerate annotations with corrected RNA IDs; do not pool distinct loci.") + return results.merge(gtf, on='Gene_ID', how='left', validate='one_to_one') + + + def main(): parser = argparse.ArgumentParser(description="Calculate RPKM and TPM values for gene expression data.") parser.add_argument("--output", type=str, help="Output file name", required=True) parser.add_argument("--counts-file", type=str, help="Path to the file containing read counts in TSV format", required=True) - parser.add_argument("--gene-lengths-file", type=str, help="Path to the file containing gene lengths in TSV format", required=True) + parser.add_argument("--gene-lengths-file", type=str, help="Legacy length table (optional); featureCounts Length is preferred", required=False) parser.add_argument("--gtf-file", type=str, help="Path to the GTF file", required=True) args = parser.parse_args() - # Read counts and gene lengths from input files using pandas - counts_df = pd.read_csv(args.counts_file, sep="\t", index_col=0, comment="#") - gene_lengths_df = pd.read_csv(args.gene_lengths_file, sep="\t", index_col=0, header=None) - gene_lengths_df.columns = ['counts'] - # Make sure the input DataFrames have the same index (gene IDs) - if not counts_df.index.equals(gene_lengths_df.index): - raise ValueError("Gene IDs in the input files do not match.") - - # Get the read counts from the last column - counts = counts_df.iloc[:, -1].tolist() - # Get the gene lengths as lists - gene_lengths = gene_lengths_df.iloc[:, 0].tolist() - - # Calculate RPKM and TPM values - rpkm_values = calculate_rpkm(counts, gene_lengths) - tpm_values = calculate_tpm(counts, gene_lengths) - - # Create a pandas DataFrame with the results - data = { - "Gene_ID": counts_df.index, - "Count": counts, - "RPKM": rpkm_values, - "TPM": tpm_values - } - results_df = pd.DataFrame(data) - - # Read the GTF file using pandas with specified column names - gtf_columns = ["seqname", "source", "feature", "start", "end", "score", "strand", "frame", "attributes", "gene_id"] - gtf_df = pd.read_csv(args.gtf_file, sep="\t", comment="#", header=None, names=gtf_columns) - - # Extract gene ID information from the GTF file - attributes = gtf_df["attributes"].str.split(';', expand=True) - gtf_df["gene_id"] = attributes[attributes[0].str.contains('gene_id')][0].str.extract(r'gene_id "([^"]+)"') - - # Rename the columns of the GTF DataFrame - gtf_df.rename(columns={0: "seqname", 1: "source", 2: "feature", 3: "start", 4: "end", 5: "score", - 6: "strand", 7: "frame", 8: "attributes"}, inplace=True) - - - # Merge the results table with the GTF information based on gene ID - merged_df = pd.merge(results_df, gtf_df, left_on="Gene_ID", right_on="gene_id", how="left") - merged_df.drop(columns=["gene_id"], inplace=True) - - # Clean up the Gene_ID now that all the merging is done - #merged_df['Gene_ID'] = merged_df.apply(clean_gene_id, axis=1) + merged_df = abundance_table(args.counts_file, args.gtf_file, args.gene_lengths_file) # Save the merged results to a tab-separated file using pandas merged_df.to_csv(args.output, sep="\t", index=False) diff --git a/dev/gff2gtf.py b/dev/gff2gtf.py index 316312d..55b8b34 100644 --- a/dev/gff2gtf.py +++ b/dev/gff2gtf.py @@ -5,20 +5,13 @@ def extract_gene_id(gff_row): - seqname = gff_row['seqname'] - feature = gff_row['feature'] - start = gff_row['start'] - end = gff_row['end'] - attribute_str = gff_row['attribute'] - attributes = attribute_str.split(';') - #if feature == 'CDS': - for attribute in attributes: + for attribute in str(gff_row['attribute']).split(';'): + if '=' not in attribute: + continue key, value = attribute.strip().split('=', 1) - if key == 'ID': - gene_id = "gene_id \"" + value + "\"" - #else: - # gene_id = "gene_id \"" + seqname + "\"" - return gene_id + if key == 'ID' and value: + return 'gene_id "' + value + '";' + raise ValueError(f"GFF feature is missing ID: {gff_row['seqname']}:{gff_row['start']}") def gff_to_gtf(input_file, output_file, feature_types): @@ -40,6 +33,14 @@ def gff_to_gtf(input_file, output_file, feature_types): # Extract gene_id from the attribute column and create a new column 'gene_id' gff_df['gene_id'] = gff_df.apply(extract_gene_id, axis=1) + if gff_df['gene_id'].duplicated().any(): + raise ValueError('Duplicate gene IDs in GFF; regenerate annotations with corrected RNA IDs before counting.') + for column in ('start', 'end'): + values = pd.to_numeric(gff_df[column], errors='raise') + if values.isna().any() or (values < 1).any() or (values % 1 != 0).any(): + raise ValueError(f'Invalid GFF {column} coordinates') + gff_df[column] = values.astype('int64') + # Write the GTF output gff_df.to_csv(output_file, sep='\t', index=False, columns=['seqname', 'source', 'feature', 'start', 'end', 'score', 'strand', 'frame', 'gene_id'], header=False, quoting=3) diff --git a/dev/pgdb_build_wf.py b/dev/pgdb_build_wf.py index 9b7cea9..d43c9c5 100755 --- a/dev/pgdb_build_wf.py +++ b/dev/pgdb_build_wf.py @@ -32,30 +32,36 @@ import html2text import time import traceback - - -def create_pgdb(pt_inputs, pt_outputs, tprune, tag, container): - - rename_pgdb(pt_inputs, tag) - tag_id = tag - # Create output dir if doesn't exist - Path(pt_outputs).mkdir(parents=True, exist_ok=True) - if container: - print("NOTE: Using containerized version of Pathway Tools...") - sh_tax = 'run-pathway-tools-and-copy-pgdb-taxprune.sh' - sh_notax = 'run-pathway-tools-and-copy-pgdb.sh' - else: - sh_tax = 'run-pathway-tools-and-copy-pgdb-taxprune_local.sh' - sh_notax = 'run-pathway-tools-and-copy-pgdb_local.sh' - if tprune == True: - pt_cmd = [sh_tax, pt_inputs, pt_outputs, tag_id] - elif tprune == False: - pt_cmd = [sh_notax, pt_inputs, pt_outputs, tag_id] - subprocess.run(pt_cmd) - # Uncompress PGDB to create PWYs table - pgdb_arc = glob.glob(pt_outputs + '/*.tar.bz2')[0] - tar_cmd = ['tar', '-xf', pgdb_arc, '-C', pt_outputs] - tar_out = subprocess.run(tar_cmd) +import tempfile + + +def create_pgdb(pt_inputs, pt_outputs, tprune, tag, container, image=None, sample_output=None, transport_inference=True, taxon_id=None): + from metapathways.pt_container import run_pgdb + Path(pt_outputs).mkdir(parents=True, exist_ok=True) + # Renaming must not modify the annotation products or another task's inputs. + with tempfile.TemporaryDirectory(prefix='mp-pgdb-input-') as work: + inputs = str(Path(work) / 'input') + shutil.copytree(pt_inputs, inputs) + rename_pgdb(inputs, tag) + if taxon_id is not None: + from metapathways.pt_sequences import set_organism_taxon + set_organism_taxon(inputs, taxon_id) + if image: + run_pgdb(image, inputs, pt_outputs, tag, tprune, sample_output=sample_output, transport_inference=transport_inference) + else: + if not transport_inference: + raise ValueError('--no_transport_inference requires a Pathway Tools SIF') + if sample_output is not None: + from metapathways.pt_sequences import attach_sequences + attach_sequences(inputs, sample_output) + suffix = '' if container else '_local' + pruning = '_taxprune' if tprune else '' + script = f'run-pathway-tools-and-copy-pgdb{pruning}{suffix}.sh' + subprocess.run([script, inputs, pt_outputs, tag], check=True) + archive = Path(pt_outputs) / f'{tag}cyc.tar.bz2' + if not archive.is_file(): + raise RuntimeError(f'Pathway Tools did not produce {archive}') + subprocess.run(['tar', '-xf', str(archive), '-C', pt_outputs], check=True) def rename_pgdb(pt_inputs, tag): @@ -74,9 +80,10 @@ def rename_pgdb(pt_inputs, tag): os.rename(o_params + '.tmp', o_params) -def extract_pwy(pt_outputs): +def extract_pwy(pt_outputs, pt_id=None): ## version.dat file is not in expected directory, create it - pt_id = os.path.basename(glob.glob(pt_outputs + '/*.tar.bz2')[0]).split('cyc', 1)[0] + if pt_id is None: + pt_id = os.path.basename(glob.glob(pt_outputs + '/*.tar.bz2')[0]).rsplit('cyc', 1)[0] flatpath = os.path.join(pt_outputs, '1.0/data') pwy_outfile = os.path.join(pt_outputs, pt_id + '_pwy.tsv') verfile = os.path.join(flatpath.rsplit('/', 2)[0], 'default-version') @@ -257,8 +264,9 @@ def get_present_rxns(pwy_frame): return pwy_rxns -def map_orfs2pwys(mp_outdir, pt_outdir): - pt_id = os.path.basename(glob.glob(pt_outdir + '/*.tar.bz2')[0]).split('cyc', 1)[0] +def map_orfs2pwys(mp_outdir, pt_outdir, pt_id=None): + if pt_id is None: + pt_id = os.path.basename(glob.glob(pt_outdir + '/*.tar.bz2')[0]).rsplit('cyc', 1)[0] orf_mapfile = glob.glob(os.path.join(mp_outdir, 'results/annotation_table/*.EC_RXN_map.tsv'))[0] pwy_outfile = os.path.join(pt_outdir, pt_id + '_pwy.tsv') pwy2orf_outfile = os.path.join(pt_outdir, pt_id + '_pwy2orf.tsv') @@ -297,6 +305,8 @@ def map_orfs2pwys(mp_outdir, pt_outdir): parser = argparse.ArgumentParser(description="Run Ptools on MP output and collect outputs.") parser.add_argument("--mp_out", type=str, help="MP3 output directory.", required=True) parser.add_argument("--tag", type=str, help="Tag for metagenome PGDB.", required=True) +parser.add_argument("--taxon_id", type=int) +parser.add_argument("--no_transport_inference", action="store_true") parser.add_argument("--taxprune", action='store_true', help="Use taxonomic pruning when building PGDBs [True or False; default: False]", required=False @@ -304,6 +314,8 @@ def map_orfs2pwys(mp_outdir, pt_outdir): parser.add_argument("--container", action='store_true', dest="container", default=False, required=False, help="Use when using containerized env", ) +parser.add_argument('--image', help='Pathway Tools Apptainer image') +parser.add_argument('--entity', help=argparse.SUPPRESS) args = parser.parse_args() mp_dir = args.mp_out @@ -312,42 +324,28 @@ def map_orfs2pwys(mp_outdir, pt_outdir): container = args.container -# Build Community-level PGDB -pt_in = os.path.join(mp_dir, 'ptools') -pt_out = os.path.join(mp_dir, 'results/pgdb/community') -print("Building Community-level PGDB.") -create_pgdb(pt_in, pt_out, taxprune, tag, container) -print("Completed Community-level PGDB.") -# Parse PGDB flatfiles to create PWYs TSV table -print("Extracting Community-level PGDB.") -extract_pwy(pt_out) -print("Extracting Complete.") -# Map inferred pwys to ORFs and ECs/RXNs used -print("Mapping ORFs to Inferred Pathways.") -map_orfs2pwys(mp_dir, pt_out) -print("Mapping Complete.") - -# Build MAG-level PGDBs if they exist -ms_dir = os.path.join(mp_dir, 'magsplitter/results') -if os.path.exists(ms_dir): - mag_list = glob.glob(ms_dir + '/*') - for pt_mag in mag_list: - if "non_binned" not in pt_mag: +def run_entity(entity): + if entity == 'community': + inputs = os.path.join(mp_dir, 'ptools') + output = os.path.join(mp_dir, 'results/pgdb/community') + entity_tag = tag + else: + inputs = os.path.join(mp_dir, 'magsplitter/results', entity) + output = os.path.join(mp_dir, 'results/pgdb/MAGs', entity) + entity_tag = entity + create_pgdb(inputs, output, taxprune, entity_tag, container, args.image, mp_dir, transport_inference=not args.no_transport_inference, taxon_id=args.taxon_id) + extract_pwy(output, entity_tag) + map_orfs2pwys(mp_dir, output, entity_tag) + + +if args.entity: + run_entity(args.entity) +else: + run_entity('community') + for mag in sorted(Path(mp_dir, 'magsplitter/results').glob('*')): + if mag.is_dir() and 'non_binned' not in mag.name: try: - mag_id = os.path.basename(pt_mag) - mag_tag = mag_id - pt_out = os.path.join(mp_dir, 'results/pgdb/MAGs/' + mag_id) - print(f"Building PGDB for {mag_id}.") - create_pgdb(pt_mag, pt_out, taxprune, mag_tag, container) - print("Completed PGDB.") - # Parse PGDB flatfiles to create PWYs TSV table - print(f"Extracting PGDB for {mag_id}.") - extract_pwy(pt_out) - print("Extracting Complete.") - # Map inferred pwys to ORFs and ECs/RXNs used - print(f"Mapping {mag_id} ORFs to Inferred Pathways.") - map_orfs2pwys(mp_dir, pt_out) - print("Mapping Complete.") + run_entity(mag.name) except Exception as e: - print(f"PGDB build for {mag_id} failed due to: {e}") - traceback.print_exc() \ No newline at end of file + print(f'PGDB build for {mag.name} failed due to: {e}') + traceback.print_exc() diff --git a/dev/ptRNAscan.py b/dev/ptRNAscan.py index 4b5659d..432d0bf 100755 --- a/dev/ptRNAscan.py +++ b/dev/ptRNAscan.py @@ -24,7 +24,8 @@ def run_tRNAscan(thread_id, args): break print(f"Thread {thread_id}: Processing {input_file}") - cmd = ["tRNAscan-SE", input_file] + # Parallelism is provided by the outer workers; avoid nested CPU pools. + cmd = ["tRNAscan-SE", "--thread", "1", input_file] for flag, file_path in output_files.items(): cmd.extend([flag, file_path]) diff --git a/docker/README.quay.md b/docker/README.quay.md index 287a8d1..be3cc04 100644 --- a/docker/README.quay.md +++ b/docker/README.quay.md @@ -10,6 +10,8 @@ MetaPathways is a pipeline for processing and annotating assembled metagenomic s Release containers contain the validated MetaPathways Conda package and its pinned dependency versions. They include the core annotation pipeline; optional MAGSplitter, camelot-frs, and licensed Pathway Tools require separate installation. +The commands here describe **published MP release images**. They are different from the licensed Pathway Tools SIF created by `metapathways build_pt`. Older release images may not include the Nextflow controller, `analysis_wf` or the report explorer. Use the [source installation guide](../docs/getting-started.md) for this development revision and the [Pathway Tools guide](../docs/pathway-tools.md) for its licensed image. + ## Docker Use a version tag for reproducible work (replace VERSION with a published release, such as 3.5.0): diff --git a/docker/conda_base.yml b/docker/conda_base.yml index e79b5ff..3ca925e 100644 --- a/docker/conda_base.yml +++ b/docker/conda_base.yml @@ -4,8 +4,8 @@ channels: - bioconda dependencies: - python=3.11 - - snakemake-minimal=9.27.0 - - pulp>=2.7,<3.4 + - nextflow>=25.10,<27 + - apptainer>=1.3,<2 - setuptools>=83,<85 - urllib3>=2.8.0,<3 - curl diff --git a/docker/conda_dev.yml b/docker/conda_dev.yml index 7b56410..f10d118 100644 --- a/docker/conda_dev.yml +++ b/docker/conda_dev.yml @@ -6,8 +6,6 @@ dependencies: - boa - anaconda-client - conda-verify - - sphinx - - sphinx_rtd_theme - pip - pip: - twine diff --git a/docs/benchmarking.md b/docs/benchmarking.md new file mode 100644 index 0000000..b261e66 --- /dev/null +++ b/docs/benchmarking.md @@ -0,0 +1,118 @@ +# Benchmarking and supplementary statistics + +[Home](../README.md) · [Reproducibility records](reproducibility.md) · [Result schema](results-schema.md) + +## Define the experiment before starting + +Specify which assemblies, reads, genome assignments, reference releases, tool revisions and resource budgets are being evaluated. Use a complete input manifest and a new output directory for a fresh measurement. A reused task is a cache check, not a newly measured biological stage. + +For CAMI, distinguish ground-truth source-genome bins from recovered MAGs. Ground-truth bins demonstrate annotation reuse, splitting, per-genome inference and report integration; they do not evaluate binning accuracy or robustness to contamination. Report the number of sample-specific bins separately from the number of distinct source genomes. Contig filtering and absence of selected annotated genes can reduce the number of actual PGDB attempts. + +Freeze the MPDB and SIF during the run. Do not change analysis code, dependencies or reference files while tasks are running. Editing documentation does not change the biological workflow, but keep a source record identifying the code actually used. A Git commit alone is insufficient when the working tree has uncommitted changes. + +## Example full workflow + +```bash +metapathways analysis_wf --manifest /project/benchmark/samples.tsv \ + -o /project/benchmark/fresh-results -d /project/MPDB \ + --annotation_dbs swissprot metacyc \ + --taxprune --taxonomic_scope all \ + --threads 8 --max_cpus 32 --max_memory '64 GB' +``` + +The command uses the registered image. Add `--image /path/to/frozen.sif` to pin it explicitly. Include a maximum CPU and memory budget in the methods. Omitting them uses detected local availability, which can vary by host and cgroup. This is a throughput benchmark with concurrency, not necessarily an isolated per-sample latency measurement. + +## What is recorded automatically + +| Record | Location / meaning | +| --- | --- | +| Resolved inputs and sample IDs | Output-root `inputs.resolved.tsv` | +| Planned community/genome entities | Output-root `inputs.entities.json` | +| User command and console | `logs/cli/` and `logs/analysis_wf/RUN_ID/console.log` | +| Planned commands, CPU/memory reservations and dependencies | `tasks.json` in the invocation directory | +| Task status and measured wrapper elapsed time | `summary.json` and `tasks/*.json` | +| Nextflow timing and sampled resource fields | `trace.tsv`, `report.html`, `timeline.html` | +| Tool-specific counts and warnings | Per-task logs and sample `run_statistics/`, annotation/RNA/abundance outputs | +| PGDB build/export status and internal diagnostics | Per-entity `results/pgdb/.../diagnostics/` | +| Indexed biological tables and source accounting | `reports/results.sqlite`, `schema.json`, `output_inventory.tsv` | + +Default Nextflow traces include status/exit, submit time, duration, realtime, CPU utilization, peak RSS/virtual memory and read/write character counters when available. Availability and units depend on the executor and trace format; retain the original headers and values. A missing measurement is unknown, not zero. `rchar`/`wchar` are process I/O counters, not a direct measurement of physical disk traffic. + +Peak RSS is sampled task memory, not its requested reservation and not the peak of the whole concurrent workflow. Do not sum per-task peaks to claim a simultaneous machine peak. CPU utilization can exceed 100% for threaded work; it is not automatically normalized by the requested CPU count. Approximate CPU-seconds derived from utilization and elapsed time must be labeled as derived, not directly measured. + +The standard trace does **not** provide a continuous whole-server CPU/RAM/disk time series, energy usage or complete network-traffic accounting. Those require a separate host monitor started with the benchmark. For the planned stage-runtime/resource figure, task-level trace measurements are appropriate; they do not support claims about an unmeasured whole-host peak. + +## Supplementary table structure + +Keep linked tables rather than forcing differently scoped quantities into one repeated wide table: + +| Table | Recommended fields | +| --- | --- | +| Sample/input inventory | Sample ID, body site/group, assembly/read/map paths and hashes, read layout, original contig count/bases, input genome-bin count | +| Sample result statistics | Retained contigs/bases, predicted/annotated features with feature types, reference-hit counts, read mapping/counting statistics | +| Entity/pathway statistics | Sample/entity, ground-truth or recovered-bin method, selected-input genes, outcome, base pathways, reactions and explicit unique pathway–gene associations | +| Task performance | Invocation, sample, stage, database/entity where applicable, status, requested CPUs/memory, elapsed time, trace CPU and memory/I/O fields | +| Run provenance | Host/OS/CPU/RAM, MP/environment/reference/SIF versions and hashes, complete command, start/end, concurrency budget and notes | + +Obtain each biological statistic from its authoritative source and define its unit. For example, an annotation-table row count is not necessarily the number of unique genes; a pathway-to-ORF export may contain multiple annotation rows per association. Count unique keys when claiming unique genes or links. The schema importer collapses some repeated associations deliberately. + +Separate input bin count, generated PF input count, attempted PGDB count, successful PGDB count, failed count and skipped count. Do not convert a missing/failed inference into zero pathways. Distinguish base pathway counts from superpathways or the total records in `pathways.dat`. + +## Runtime and resource figures + +For stage comparisons, group tasks by stage and, where relevant, reference database or entity. Show distributions across samples/bins rather than hiding all variation in one mean. Report whether a panel includes fresh successes only, failed attempts, or both. + +Parallel task times overlap. Summing their durations measures accumulated task elapsed time, not workflow makespan. Measure end-to-end wall time from controller start through final report completion. Nextflow's task trace does not include all validation/planning and post-workflow report-indexing time. MP's task elapsed time also includes wrapper overhead; it is not necessarily only the biological executable's compute time. + +Keep separate measurements for MPDB construction and Pathway Tools image construction if they are discussed. Sample workflow traces do not retroactively capture setup performed before the run. Copying/downloading inputs is likewise outside sample-stage measurements unless explicitly included in the experiment. + +## Save environment and machine information + +Run these on the analysis host before the benchmark, adapting the checkout path. Save them beside the manifest, not in a temporary Nextflow work directory: + +```bash +mkdir -p /project/benchmark/provenance +conda list --explicit > /project/benchmark/provenance/conda-explicit.txt +python -m pip freeze > /project/benchmark/provenance/pip-freeze.txt +metapathways version > /project/benchmark/provenance/mp-version.txt +nextflow -version > /project/benchmark/provenance/nextflow-version.txt +apptainer --version > /project/benchmark/provenance/apptainer-version.txt +lscpu > /project/benchmark/provenance/lscpu.txt +free -b > /project/benchmark/provenance/memory.txt +git -C /path/to/MetaPathways rev-parse HEAD > /project/benchmark/provenance/mp-commit.txt +git -C /path/to/MetaPathways status --short > /project/benchmark/provenance/mp-working-tree.txt +``` + +Also retain the source snapshot or checksums for uncommitted/untracked implementation files, the SIF and `.sif.json`, MetaCyc provenance, and reference release/checksum files. For very large raw datasets, compute checksums as a separate acquisition/validation step so that extra I/O does not distort measured analysis performance. + +## Finish, inspect, then summarize + +Read `summary.json` and per-entity `execution.json`, not just the top-level completion message. Inspect required task success, optional failures/skips, input coverage and report import notes. Preserve failed-attempt logs when retrying; a final successful attempt does not erase their computational cost. + +Default cleanup removes disposable work/cache state after archiving diagnostics. It retains final results, receipts, logs, traces and Nextflow report/timeline. Explicit `--work_dir`, `--conda_cache` or `--keep_work` retain additional scratch; retaining it is not necessary merely to make the supplementary resource table. Interrupted runs may also retain scratch for diagnosis. + +The final supplementary table and figure still require extraction, joining and quality checks after completion. The explorer provides biological subsets and an inventory; it does not automatically generate a publication-ready benchmark figure or certify manuscript statements. Audit every claim against the frozen final records. + +## Compare one server with a Slurm cluster + +Test the three small reviewer samples on the cluster before submitting the full benchmark. Install the same feature-branch revision on shared storage, and activate its environment before starting MP. Nextflow submits with the logged-in user's Slurm identity; there are no MP password flags. Confirm that `sbatch`, `squeue`, and `scancel` are available and that compute nodes can use the same software, database and input paths. + +For a first three-sample cluster test, adapt the shared paths and allocation names: + +```bash +metapathways analysis_wf \ + --manifest /shared/project/cami-reviewer/all.tsv \ + -o /shared/project/mp-reviewer-slurm \ + -d /shared/project/MPDB \ + --annotation_dbs swissprot \ + --skip_ptools \ + --threads 4 --max_cpus 8 --memory '4 GB' --max_memory '16 GB' \ + --executor slurm --account my_project --partition compute \ + --max_tasks 2 --submit_rate 6 --time_limit 2h +``` + +The example uses the full public SwissProt/SILVA references in your MPDB. If using the bundled test references, select `swissprot_test` and `SILVA_SSU_test SILVA_LSU_test` as in the reviewer walkthrough. The two-hour limit is a small-input example, not a full CAMI task limit. Follow your site's policy for keeping the Nextflow controller running: some sites permit a persistent headnode session, others require a controller allocation. MP preparation and report generation run in that controller, while scheduled biological stages run on compute nodes. + +For the complete benchmark, copy the original assemblies, reads, CAMI genome maps, reference database and your licensed Pathway Tools SIF onto storage accessible to all selected nodes. Write an HPC-specific manifest pointing there; local server paths and symlinks are not portable. Use a new output directory. Supply the same analysis options, reference release, pruning scope, and image content as on the single server. Pass `--image /shared/project/pathway-tools.sif` explicitly if its user registration differs on the cluster. + +Record a run/scenario ID (`local` or `slurm`), Git commit, environment export, input/reference/SIF checksums, task resource requests, node hardware, scheduler settings, start/end times, and log directory. Compare elapsed run time separately from summed task CPU time; cluster queue delays are part of operational elapsed time but not biological compute time. Do not mix a resumed run with a fresh timing run. If total budgets differ, report that as a throughput/scaling scenario rather than attributing the entire speed difference to Nextflow or Slurm. Keep all per-task traces and both scenario manifests for the supplementary tables. diff --git a/docs/cli-reference.md b/docs/cli-reference.md new file mode 100644 index 0000000..7403577 --- /dev/null +++ b/docs/cli-reference.md @@ -0,0 +1,508 @@ +# Complete CLI reference + +[User guide](../README.md) · [Workflow guide](workflow.md) + +Generated by `python scripts/generate_cli_docs.py`. Run `metapathways COMMAND --help` for the help of your installed revision. + +## run + +```text +usage: Metapathways run [options] + +Minimum REQUIRED Command: +MetaPathways run -i INPUT_FILE -o OUTPUT_DIR -d REFDB_DIR + +options: + -h, --help show this help message and exit + --dryrun show the execution plan without running tasks + +Minimum Required Arguments: + -i INPUT_FILE, --input_file INPUT_FILE + path to the input fasta file/input dir [REQUIRED] + -o OUTPUT_DIR, --output_dir OUTPUT_DIR + path to the output directory [REQUIRED] + -d REFDB_DIR, --refdb_dir REFDB_DIR + path to the reference DB [REQUIRED] + +Quality Controls Arguments: + --input_format {fasta,fasta-amino} + Input format, FASTA support only [fasta] + --qc_min_length QC_MIN_LENGTH + Minimum length for quality control [180] + --qc_delete_replicates {yes,no} + Delete replicates in quality control [yes] + +ORF Prediction Arguments: + --orf_strand {pos,neg,both} + Strand for ORF prediction [both] + --orf_algorithm ORF_ALGORITHM + Algorithm for ORF prediction, Prodigal support only [prodigal] + --orf_min_length ORF_MIN_LENGTH + Minimum ORF length [60] + --orf_translation_table ORF_TRANSLATION_TABLE + Translation table for ORF prediction, see Prodigal for translation tables [11] + --orf_mode {single,meta} + Mode for ORF prediction [meta] + +Functional Annotation Arguments: + --annotation_algorithm {FAST,BLAST} + Algorithm for ORF annotation [FAST] + --annotation_dbs ANNOTATION_DBS [ANNOTATION_DBS ...] + Database(s) for annotation, space-separated list [swissprot] + --annotation_min_bsr ANNOTATION_MIN_BSR + Minimum BSR for annotation [0.4] + --annotation_max_evalue ANNOTATION_MAX_EVALUE + Maximum e-value for annotation [0.000001] + --annotation_min_score ANNOTATION_MIN_SCORE + Minimum score for annotation [20] + --annotation_min_length ANNOTATION_MIN_LENGTH + Minimum length for annotation [45] + --annotation_max_hits ANNOTATION_MAX_HITS + Maximum hits for annotation [5] + --annotation_run_mode {default,pervol} + Run mode for annotation, FAST only [pervol] + +rRNA Annotation Arguments: + --rRNA_refdbs RRNA_REFDBS [RRNA_REFDBS ...] + Reference databases for rRNA annotation, space-separated list + [SILVA_138.1_LSURef_NR99_tax_silva_trunc SILVA_138.1_SSURef_NR99_tax_silva_trunc] + --rRNA_max_evalue RRNA_MAX_EVALUE + Maximum e-value for rRNA annotation [0.000001] + --rRNA_min_identity RRNA_MIN_IDENTITY + Minimum identity for rRNA annotation [20] + --rRNA_min_bitscore RRNA_MIN_BITSCORE + Minimum bitscore for rRNA annotation [50] + +Read Mapping Arguments (single sample support only): + -1 FWD_FASTQ, --fastq FWD_FASTQ + location of the raw fastq file, either forward or interleaved + -2 REV_FASTQ, --rev_fastq REV_FASTQ + location of the raw reverse fastq file, if separate paired-end + --interleaved if paired-end is interleaved [False] + +Pipeline Step Arguments: + --PREPROCESS_INPUT {yes,skip,redo} + Step: PREPROCESS_INPUT [yes] + --ORF_PREDICTION {yes,skip,redo} + Step: ORF_PREDICTION [yes] + --FILTER_AMINOS {yes,skip,redo} + Step: FILTER_AMINOS [yes] + --SCAN_rRNA {yes,skip,redo} + Step: SCAN_rRNA [yes] + --SCAN_tRNA {yes,skip,redo} + Step: SCAN_tRNA [yes] + --FUNC_SEARCH {yes,skip,redo} + Step: FUNC_SEARCH [yes] + --PARSE_FUNC_SEARCH {yes,skip,redo} + Step: PARSE_FUNC_SEARCH [yes] + --ANNOTATE_ORFS {yes,skip,redo} + Step: ANNOTATE_ORFS [yes] + --GENBANK_FILE {yes,skip,redo} + Step: GENBANK_FILE [yes] + --CREATE_ANNOT_REPORTS {yes,skip,redo} + Step: CREATE_ANNOT_REPORTS [yes] + --PATHOLOGIC_INPUT {yes,skip,redo} + Step: PATHOLOGIC_INPUT [yes] + --COMPUTE_TPM {yes,skip,redo} + Step: COMPUTE_TPM [yes] + --force_redo Redo all steps [False] + +Execution Resources: + --max_cpus MAX_CPUS total CPUs available to this command [available CPUs] + --memory MEMORY memory reservation per task [16 GB] + --max_memory MAX_MEMORY + total memory available to this command [available host memory; Slurm: 64 GB] + --max_tasks MAX_TASKS + maximum simultaneously running tasks [limited by CPU/memory] + --executor {local,slurm} + execution backend [local]; Slurm uses your logged-in cluster identity + --account ACCOUNT Slurm allocation/account + --partition PARTITION + Slurm partition + --qos QOS Slurm quality of service + --reservation RESERVATION + Slurm reservation + --time_limit TIME_LIMIT + Slurm walltime per task [24h] + --submit_rate SUBMIT_RATE + maximum Slurm submissions per minute [6] + --work_dir WORK_DIR custom Nextflow work directory; retained after the run + --conda_cache CONDA_CACHE + custom Conda cache directory; retained after the run + --keep_work retain automatically allocated work/cache directories + +Miscellaneous Arguments: + -s SAMPLES [SAMPLES ...], --samples SAMPLES [SAMPLES ...] + process only specific samples, space-separated list + -t THREADS, --threads THREADS + threads per capable tool [8], capped by --max_cpus; serial stages use one CPU + -v, --verbose print more information on the stdout + --test use test values for all arguments +``` + +## analysis_wf + +```text +usage: Metapathways analysis_wf [options] + +Annotate multiple metagenomes, split MAGs, build PGDBs and generate a combined report. + +options: + -h, --help show this help message and exit + --dryrun show the execution plan without running tasks + --manifest MANIFEST TSV with sample_id, assembly, read_layout, reads_1, reads_2, mag_map + --reads_dir READS_DIR + Flat reads directory; -i then names the assemblies directory + --mag_maps_dir MAG_MAPS_DIR + Flat contig-to-MAG map directory; -i then names the assemblies directory + --no_reads Explicitly omit read mapping during automatic discovery + --no_mags Explicitly omit MAG splitting during automatic discovery + --skip_ptools Omit community and MAG PGDB construction + --image IMAGE Pathway Tools SIF [registered by build_pt] + --taxon_id TAXON_ID Override PGDB NCBI taxon in private inputs; applies to every selected entity + --taxonomic_scope {all,bacteria,archaea,eukaryotes} + Named PGDB taxon override; all means cellular life; euks aliases eukaryotes. Use --taxprune to retain pruning and avoid unpruned rescoring. Omitting both options preserves the input taxon. + --no_transport_inference + Disable TIP transport inference + --taxprune Enable Pathway Tools taxonomic pruning + --ptools_memory PTOOLS_MEMORY + Memory per single-CPU PGDB task [4 GB] + +Minimum Required Arguments: + -i INPUT_FILE, --input_file INPUT_FILE + dataset root, or assemblies directory with --reads_dir/--mag_maps_dir; alternative: --manifest + -o OUTPUT_DIR, --output_dir OUTPUT_DIR + path to the output directory [REQUIRED] + -d REFDB_DIR, --refdb_dir REFDB_DIR + path to the reference DB [REQUIRED] + +Quality Controls Arguments: + --input_format {fasta,fasta-amino} + Input format, FASTA support only [fasta] + --qc_min_length QC_MIN_LENGTH + Minimum length for quality control [180] + --qc_delete_replicates {yes,no} + Delete replicates in quality control [yes] + +ORF Prediction Arguments: + --orf_strand {pos,neg,both} + Strand for ORF prediction [both] + --orf_algorithm ORF_ALGORITHM + Algorithm for ORF prediction, Prodigal support only [prodigal] + --orf_min_length ORF_MIN_LENGTH + Minimum ORF length [60] + --orf_translation_table ORF_TRANSLATION_TABLE + Translation table for ORF prediction, see Prodigal for translation tables [11] + --orf_mode {single,meta} + Mode for ORF prediction [meta] + +Functional Annotation Arguments: + --annotation_algorithm {FAST,BLAST} + Algorithm for ORF annotation [FAST] + --annotation_dbs ANNOTATION_DBS [ANNOTATION_DBS ...] + Database(s) for annotation, space-separated list [swissprot] + --annotation_min_bsr ANNOTATION_MIN_BSR + Minimum BSR for annotation [0.4] + --annotation_max_evalue ANNOTATION_MAX_EVALUE + Maximum e-value for annotation [0.000001] + --annotation_min_score ANNOTATION_MIN_SCORE + Minimum score for annotation [20] + --annotation_min_length ANNOTATION_MIN_LENGTH + Minimum length for annotation [45] + --annotation_max_hits ANNOTATION_MAX_HITS + Maximum hits for annotation [5] + --annotation_run_mode {default,pervol} + Run mode for annotation, FAST only [pervol] + +rRNA Annotation Arguments: + --rRNA_refdbs RRNA_REFDBS [RRNA_REFDBS ...] + Reference databases for rRNA annotation, space-separated list + [SILVA_138.1_LSURef_NR99_tax_silva_trunc SILVA_138.1_SSURef_NR99_tax_silva_trunc] + --rRNA_max_evalue RRNA_MAX_EVALUE + Maximum e-value for rRNA annotation [0.000001] + --rRNA_min_identity RRNA_MIN_IDENTITY + Minimum identity for rRNA annotation [20] + --rRNA_min_bitscore RRNA_MIN_BITSCORE + Minimum bitscore for rRNA annotation [50] + +Pipeline Step Arguments: + --PREPROCESS_INPUT {yes,skip,redo} + Step: PREPROCESS_INPUT [yes] + --ORF_PREDICTION {yes,skip,redo} + Step: ORF_PREDICTION [yes] + --FILTER_AMINOS {yes,skip,redo} + Step: FILTER_AMINOS [yes] + --SCAN_rRNA {yes,skip,redo} + Step: SCAN_rRNA [yes] + --SCAN_tRNA {yes,skip,redo} + Step: SCAN_tRNA [yes] + --FUNC_SEARCH {yes,skip,redo} + Step: FUNC_SEARCH [yes] + --PARSE_FUNC_SEARCH {yes,skip,redo} + Step: PARSE_FUNC_SEARCH [yes] + --ANNOTATE_ORFS {yes,skip,redo} + Step: ANNOTATE_ORFS [yes] + --GENBANK_FILE {yes,skip,redo} + Step: GENBANK_FILE [yes] + --CREATE_ANNOT_REPORTS {yes,skip,redo} + Step: CREATE_ANNOT_REPORTS [yes] + --PATHOLOGIC_INPUT {yes,skip,redo} + Step: PATHOLOGIC_INPUT [yes] + --COMPUTE_TPM {yes,skip,redo} + Step: COMPUTE_TPM [yes] + --force_redo Redo all steps [False] + +Execution Resources: + --max_cpus MAX_CPUS total CPUs available to this command [available CPUs] + --memory MEMORY memory reservation per task [16 GB] + --max_memory MAX_MEMORY + total memory available to this command [available host memory; Slurm: 64 GB] + --max_tasks MAX_TASKS + maximum simultaneously running tasks [limited by CPU/memory] + --executor {local,slurm} + execution backend [local]; Slurm uses your logged-in cluster identity + --account ACCOUNT Slurm allocation/account + --partition PARTITION + Slurm partition + --qos QOS Slurm quality of service + --reservation RESERVATION + Slurm reservation + --time_limit TIME_LIMIT + Slurm walltime per task [24h] + --submit_rate SUBMIT_RATE + maximum Slurm submissions per minute [6] + --work_dir WORK_DIR custom Nextflow work directory; retained after the run + --conda_cache CONDA_CACHE + custom Conda cache directory; retained after the run + --keep_work retain automatically allocated work/cache directories + +Miscellaneous Arguments: + -t THREADS, --threads THREADS + threads per capable tool [8], capped by --max_cpus; serial stages use one CPU + -v, --verbose print more information on the stdout +``` + +## build_db + +```text +usage: metapathways [-h] [-d PATH] [--func [CATEGORICAL ...]] [-a ALIGNER] + [--metacyc_source METACYC_SOURCE] [-t INT] [--dryrun] + [--snakemake [SNAKEMAKE ...]] [--test] [--max_cpus MAX_CPUS] [--memory MEMORY] + [--max_memory MAX_MEMORY] [--max_tasks MAX_TASKS] [--executor {local,slurm}] + [--account ACCOUNT] [--partition PARTITION] [--qos QOS] + [--reservation RESERVATION] [--time_limit TIME_LIMIT] + [--submit_rate SUBMIT_RATE] [--work_dir WORK_DIR] [--conda_cache CONDA_CACHE] + [--keep_work] + +automated database install + +options: + -h, --help show this help message and exit + -t INT, --threads INT + total database-build CPU budget [available CPUs] + --dryrun show the database execution plan without running tasks + --snakemake [SNAKEMAKE ...] + legacy compatibility flags; use the resource flags for new runs + --test use test values for all arguments + +database arguments: + -d PATH, --refdb_dir PATH + path to save the reference DB, [DEFAULT "./"] + --func [CATEGORICAL ...] + functional references, select any combination from ['swissprot', 'cazy', + 'eggnog', 'uniref50', 'uniref90', 'metacyc'], [DEFAULT ['swissprot']] + -a ALIGNER, --aligner ALIGNER + local aligner to index for, select one of ['fast', 'blast'], [DEFAULT + fast] + --metacyc_source METACYC_SOURCE + licensed MetaCyc data directory or Pathway Tools SIF [registered SIF when + --func includes metacyc] + +Execution Resources: + --max_cpus MAX_CPUS total CPUs available to this command [available CPUs] + --memory MEMORY memory reservation per task [16 GB] + --max_memory MAX_MEMORY + total memory available to this command [available host memory; Slurm: 64 + GB] + --max_tasks MAX_TASKS + maximum simultaneously running tasks [limited by CPU/memory] + --executor {local,slurm} + execution backend [local]; Slurm uses your logged-in cluster identity + --account ACCOUNT Slurm allocation/account + --partition PARTITION + Slurm partition + --qos QOS Slurm quality of service + --reservation RESERVATION + Slurm reservation + --time_limit TIME_LIMIT + Slurm walltime per task [24h] + --submit_rate SUBMIT_RATE + maximum Slurm submissions per minute [6] + --work_dir WORK_DIR custom Nextflow work directory; retained after the run + --conda_cache CONDA_CACHE + custom Conda cache directory; retained after the run + --keep_work retain automatically allocated work/cache directories +``` + +## mag_split + +```text +usage: Metapathways mag_split [options] + +Minimum REQUIRED Command: +Metapathways mag_split -o output_dir -m contig_mag_map + +options: + -h, --help show this help message and exit + -o OUTPUT_DIR, --output_dir OUTPUT_DIR + path where MP output was saved [REQUIRED] + -m MAG_MAP, --contig_mag_map MAG_MAP + TSV file that contains contig-to-MAG mapping [REQUIRED] + +Execution Resources: + --max_cpus MAX_CPUS total CPUs available to this command [available CPUs] + --memory MEMORY memory reservation per task [16 GB] + --max_memory MAX_MEMORY + total memory available to this command [available host memory; Slurm: 64 GB] + --max_tasks MAX_TASKS + maximum simultaneously running tasks [limited by CPU/memory] + --executor {local,slurm} + execution backend [local]; Slurm uses your logged-in cluster identity + --account ACCOUNT Slurm allocation/account + --partition PARTITION + Slurm partition + --qos QOS Slurm quality of service + --reservation RESERVATION + Slurm reservation + --time_limit TIME_LIMIT + Slurm walltime per task [24h] + --submit_rate SUBMIT_RATE + maximum Slurm submissions per minute [6] + --work_dir WORK_DIR custom Nextflow work directory; retained after the run + --conda_cache CONDA_CACHE + custom Conda cache directory; retained after the run + --keep_work retain automatically allocated work/cache directories +``` + +## build_pt + +```text +usage: metapathways build_pt [-h] -i INSTALLER [--ptools_version PTOOLS_VERSION] [-d REFDB_DIR] + [-a {fast,blast}] [-o OUTPUT_DIR] [-t THREADS] [--dryrun] + [--max_cpus MAX_CPUS] [--memory MEMORY] [--max_memory MAX_MEMORY] + [--max_tasks MAX_TASKS] [--executor {local,slurm}] + [--account ACCOUNT] [--partition PARTITION] [--qos QOS] + [--reservation RESERVATION] [--time_limit TIME_LIMIT] + [--submit_rate SUBMIT_RATE] [--work_dir WORK_DIR] + [--conda_cache CONDA_CACHE] [--keep_work] + +Build a Pathway Tools SIF from a local Linux installer using Nextflow and Apptainer. + +options: + -h, --help show this help message and exit + -i INSTALLER, --installer INSTALLER + local Pathway Tools Linux x86-64 installer + --ptools_version PTOOLS_VERSION + release number if the installer was renamed; otherwise inferred from its + filename + -d REFDB_DIR, --refdb_dir REFDB_DIR + also export and prepare the licensed MetaCyc reference in this MPDB after + building the SIF + -a {fast,blast}, --aligner {fast,blast} + MetaCyc reference index format with -d [fast] + -o OUTPUT_DIR, --output_dir OUTPUT_DIR + container directory [~/.local/share/metapathways/containers] + -t THREADS, --threads THREADS + CPUs for image compression [2]; Pathway Tools uses one CPU + --dryrun write and show the build plan without building or registering + +Execution Resources: + --max_cpus MAX_CPUS total CPUs available to this command [available CPUs] + --memory MEMORY memory reservation per task [4 GB] + --max_memory MAX_MEMORY + total memory available to this command [available host memory; Slurm: 64 + GB] + --max_tasks MAX_TASKS + maximum simultaneously running tasks [limited by CPU/memory] + --executor {local,slurm} + execution backend [local]; Slurm uses your logged-in cluster identity + --account ACCOUNT Slurm allocation/account + --partition PARTITION + Slurm partition + --qos QOS Slurm quality of service + --reservation RESERVATION + Slurm reservation + --time_limit TIME_LIMIT + Slurm walltime per task [24h] + --submit_rate SUBMIT_RATE + maximum Slurm submissions per minute [6] + --work_dir WORK_DIR custom Nextflow work directory; retained after the run + --conda_cache CONDA_CACHE + custom Conda cache directory; retained after the run + --keep_work retain automatically allocated work/cache directories +``` + +## ptools + +```text +usage: Metapathways ptools [options] + +Minimum REQUIRED Command: +Metapathways ptools -o output_dir + +options: + -h, --help show this help message and exit + -o OUTPUT_DIR, --output_dir OUTPUT_DIR + path where MP output was saved [REQUIRED] + --tag TAG Custom name for ePGDB [optional] + --container Flag only used in containerized env [special flag] + --taxprune Set taxonomic pruning in pathway tools to True + --taxon_id TAXON_ID Override PGDB NCBI taxon in private inputs; applies to every selected entity + --taxonomic_scope {all,bacteria,archaea,eukaryotes} + Named PGDB taxon override; all means cellular life; euks aliases eukaryotes. Use --taxprune to retain pruning and avoid unpruned rescoring. Omitting both options preserves the input taxon. + --no_transport_inference + Disable TIP transport inference (SIF only) + --entity ENTITY Build only community or the specified MAG ID + --image IMAGE Pathway Tools SIF [registered by build_pt] + +Execution Resources: + --max_cpus MAX_CPUS total CPUs available to this command [available CPUs] + --memory MEMORY memory reservation per task [4 GB] + --max_memory MAX_MEMORY + total memory available to this command [available host memory; Slurm: 64 GB] + --max_tasks MAX_TASKS + maximum simultaneously running tasks [limited by CPU/memory] + --executor {local,slurm} + execution backend [local]; Slurm uses your logged-in cluster identity + --account ACCOUNT Slurm allocation/account + --partition PARTITION + Slurm partition + --qos QOS Slurm quality of service + --reservation RESERVATION + Slurm reservation + --time_limit TIME_LIMIT + Slurm walltime per task [24h] + --submit_rate SUBMIT_RATE + maximum Slurm submissions per minute [6] + --work_dir WORK_DIR custom Nextflow work directory; retained after the run + --conda_cache CONDA_CACHE + custom Conda cache directory; retained after the run + --keep_work retain automatically allocated work/cache directories +``` + +## report + +```text +usage: metapathways [-h] -o OUTPUT_DIR [--serve] [--no-rebuild] [--port PORT] [--no-browser] + +Build a navigable report from existing MP outputs; no analyses are rerun. + +options: + -h, --help show this help message and exit + -o OUTPUT_DIR, --output_dir OUTPUT_DIR + sample output or parent containing sample outputs + --serve open the local searchable portal and serve until Ctrl-C + --no-rebuild use an existing report snapshot + --port PORT local port [automatically selected] + --no-browser print the local URL without opening a browser +``` diff --git a/docs/commands.md b/docs/commands.md new file mode 100644 index 0000000..f4a9ec9 --- /dev/null +++ b/docs/commands.md @@ -0,0 +1,98 @@ +# Command cookbook: run only the modules you need + +[Home](../README.md) · [Complete CLI reference](cli-reference.md) · [Stage/output reference](workflow.md) + +Use `metapathways COMMAND --help` for your installed revision. `metapathways version` reports the package version; also record the source Git revision. These examples assume an activated environment and writable output paths. Replace `/path/to/MPDB` and input filenames before running them. + +## Choose a command + +| Goal | Command | Meaning of `-o` | +| --- | --- | --- | +| Annotate one or more assemblies | `run` | Parent of sample directories | +| Annotate, map reads, split genomes, infer pathways and report | `analysis_wf` | Parent of sample directories | +| Prepare public/licensed reference indexes and tables | `build_db` | Use `-d` for the MPDB root | +| Build the licensed Pathway Tools image | `build_pt` | Directory holding generated SIF images | +| Split existing annotations by genome | `mag_split` | One existing sample directory | +| Infer community/genome pathways from existing annotations | `ptools` | One existing sample directory | +| Index/view existing results | `report` | One sample or a parent of samples | + +## build_db: references before analysis + +```bash +metapathways build_db -d /path/to/MPDB --func swissprot -a fast --dryrun +metapathways build_db -d /path/to/MPDB --func swissprot -a fast +``` + +The first command plans; the second downloads/formats. `--func` selects functional references; RNA, enzyme and taxonomy support are also prepared. Public options include SwissProt, CAZy and UniRef50/90. eggNOG requires the documented pre-supplied FASTA rather than an automatic acquisition rule. MetaCyc requires a licensed source; see [Pathway Tools](pathway-tools.md). + +`-a fast` and `-a blast` choose the annotation index format. Match them with `run/analysis_wf --annotation_algorithm FAST` or `BLAST`. Build into a new directory when changing reference versions during an ongoing experiment. Database download/build time is separate from sample-analysis runtime. + +On this command `-t` is the legacy aggregate CPU limit, unlike per-tool `run --threads`. Prefer explicit `--max_cpus` when communicating a shared resource budget. `--dryrun` performs no downloading/indexing. Historical Snakefiles are not the supported execution path. + +## run: annotations and optional abundance + +```bash +metapathways run -i SampleA.fasta -o results -d /path/to/MPDB \ + -1 SampleA_R1.fastq.gz -2 SampleA_R2.fastq.gz \ + --annotation_dbs swissprot metacyc \ + --threads 8 --max_cpus 16 --max_memory '64 GB' +``` + +This writes `results/SampleA/`. For interleaved pairs replace the two read arguments with `-1 SampleA_interleaved.fastq.gz --interleaved`. Single-end uses `-1` alone. No reads means no read abundance. MP passes the actual R2 to CoverM and uses the exact expected CoverM BAM for counting; a leftover sorted BAM is not a replacement for missing mapping output. + +The command prepares Pathway Tools inputs but does not run Pathway Tools. For protein FASTA, standalone `run --input_format fasta-amino` uses compatible annotation stages; the complete nucleotide workflow and DNA/read/genome-splitting examples do not apply unchanged. + +To inspect the plan add `--dryrun`. To rerun only read mapping/counting with the original other arguments, add `--COMPUTE_TPM redo`. Stage defaults, dependencies and outputs are documented in [workflow stages](workflow.md#annotation-stages). Do not use `--force_redo` merely to retry a failed downstream task: it forces annotation-stage recomputation. + +## analysis_wf: one complete run for N samples + +```bash +metapathways analysis_wf --manifest /project/samples.tsv \ + -o analysis -d /path/to/MPDB \ + --annotation_dbs swissprot metacyc \ + --taxprune --taxonomic_scope all \ + --threads 8 --max_cpus 32 --max_memory '64 GB' +``` + +Use [automatic directories or a manifest](inputs.md). All samples share one scheduling budget and dependency graph. Independent tasks can overlap, including mapping and PGDB work. `--skip_ptools` omits inference; discovery's `--no_reads` and `--no_mags` explicitly omit those inputs. In a manifest, blank optional input columns express per-sample omissions. + +The workflow validates inputs and writes a resolved manifest before submitting analyses. Required annotation stages cannot be skipped through `skip`; valid completed tasks are reused automatically. `--ptools_memory '8 GB'` changes only each PGDB reservation. `--memory` changes the general task reservation. Increasing the total memory budget does not automatically increase either per-task setting. + +## mag_split: reuse community annotation + +```bash +metapathways mag_split -o results/SampleA -m /project/SampleA.tsv \ + --max_cpus 8 --max_memory '32 GB' +``` + +This needs the sample's completed annotation/PF files, original-contig mapping, authoritative feature table, and your headerless contig-to-genome map. It does not perform binning or redo reference searches. It produces MAG-specific Pathway Tools inputs and preserves the original map for full membership reporting. + +Changing assignments can change per-genome pathway inference even if the community annotation is unchanged. Run `ptools` afterward, or let `analysis_wf` manage the dependency. + +## build_pt and ptools: licensed setup, then inference + +```bash +metapathways build_pt -i /path/to/pathway-tools-29.5-linux-64-tier1-install \ + -o ~/mp-containers -d /path/to/MPDB -a fast +metapathways ptools -o results/SampleA \ + --taxprune --taxonomic_scope all --max_cpus 8 --max_memory '32 GB' +``` + +The first builds/registers the image and optionally prepares MetaCyc annotation references. The second uses existing sample annotations to infer community and available MAG pathways. Use `--entity community` or `--entity MAG_001` to select a single entity. The [Pathway Tools chapter](pathway-tools.md) covers installer acquisition, image selection, patches, licensing, taxonomy, TIP, errors and outputs in detail. + +## report: inspect and export without reanalysis + +```bash +metapathways report -o results +metapathways report -o results --serve --no-rebuild +``` + +The first indexes current results. The second serves that snapshot for searching and CSV exports. Omit `--no-rebuild` when you want a refreshed index. Reports can be built from partial outputs, but cannot reconstruct missing resource measurements or repair old biological results. [Explorer instructions](reports-tutorial.md) include SSH access and safe table joins. + +## Resources, failure and restart + +Use the [resource and Slurm guide](../README.md#resources-and-slurm) for CPU/memory budgets and cluster flags. With `--threads 8 --max_cpus 32`, up to four ready eight-CPU tasks can fit, or a mixture of threaded and single-CPU tasks, subject to memory. Local execution is default; Slurm uses your logged-in identity, not credentials passed to MP. + +Repeat the same command and output location after a recoverable failure. MP checks durable receipts and tracked files, reuses successful compatible tasks, and retries failed work. No explicit Nextflow `-resume` is required on the MP CLI. A new output directory is appropriate for a fresh benchmark, not for a simple restart. + +Changing parameters, references, image, inputs or software can change reuse behavior. Output existence alone is not proof of provenance. Preserve `logs/` and `.metapathways/` receipts if you want to resume. See [restart details](../README.md#logs-temporary-files-and-restarting). diff --git a/docs/conda_env.yml b/docs/conda_env.yml deleted file mode 100644 index d77f331..0000000 --- a/docs/conda_env.yml +++ /dev/null @@ -1,5 +0,0 @@ -channels: - - conda-forge -dependencies: - - sphinx - - sphinx_rtd_theme==2.0.0 diff --git a/docs/getting-started.md b/docs/getting-started.md new file mode 100644 index 0000000..7641a11 --- /dev/null +++ b/docs/getting-started.md @@ -0,0 +1,111 @@ +# Getting started: from a terminal to your first result + +[Home and reading order](../README.md#start-here) · Next: [reviewer walkthrough](reviewer-test.md) + +## What you will do + +Install MP on a Linux computer, activate its software environment, run a small included example, and open a report. You do not need a Pathway Tools license for the first example. Add pathway inference after the example works. + +If you already have a working MP installation, go directly to the [reviewer walkthrough](reviewer-test.md). If your lab manages the software centrally, ask for the activation command and MPDB path rather than installing a second copy. + +## Before typing commands + +A **terminal** accepts commands. A **working directory** is the folder relative paths refer to. `pwd` displays it; `ls` lists its contents; `cd DIRECTORY` changes it. `~` means your home directory. `/data/project/sample.fasta` is an absolute path; `sample.fasta` means a file in the working directory. Linux distinguishes `SampleA` from `samplea`. + +Copy commands inside the code blocks, without Markdown backticks or a shell prompt. A backslash at the end of a line continues the command on the next line: do not put spaces after it. Values such as `/path/to/MPDB` are placeholders; replace them with real paths. Use simple project and sample names without spaces or shell punctuation, because some legacy tool wrappers construct shell commands. + +An **environment** is a collection of compatible software. Activating it makes your terminal find the intended MP and tool executables. Activate it again in each new terminal. It does not require setting an MP-specific environment variable. + +On a remote server, the analysis commands run in the SSH terminal on that server. Your web browser normally runs on your own computer. The [SSH report instructions](reports-tutorial.md#view-a-remote-report-through-ssh) connect the two. For a long run, use your site's persistent terminal/session practice so disconnecting SSH does not interrupt your controller. + +## Install on Linux x86-64 + +The supported source-install path uses Linux x86-64, Conda/Mamba, and Git. Windows and macOS users can connect to a Linux server. This guide does not claim a tested native Windows, Apple Silicon, or WSL installation. + +If `conda --version` and `mamba --version` do not work, follow the official [Miniforge installation instructions](https://github.com/conda-forge/miniforge). Reopen your terminal after shell initialization. Ask your administrator about Git and cluster installation policies if needed. + +Use a writable source checkout. The following commands put it in `~/src/MetaPathways`, which the reviewer walkthrough also uses: + +```bash +mkdir -p ~/src +cd ~/src +git clone https://github.com/hallamlab/MetaPathways.git +cd MetaPathways +git checkout feat/nextflow-controller-db-build +mamba env create -f docker/conda_base.yml +conda activate metapathways +python -m pip install --no-deps --no-build-isolation -e . +python -m pip install \ + 'git+https://github.com/hallamlab/MAGSplitter.git@main' \ + 'git+https://bitbucket.org/tomeraltman/camelot-frs@dev#egg=camelot-frs' +``` + +This is the development branch documented here. For a release, use its tag and matching documentation. The environment installs the workflow and biological dependencies; MAGSplitter handles genome-bin splitting and Camelot handles pathway extraction. The installation can require substantial downloads. Do not use `sudo pip` to install MP into the operating system's Python. + +`-e .` installs MP in editable mode: Python modules are read from this checkout. Some helper scripts are copied into the environment, so rerun the MP `pip install` command after updating the checkout. Package version `3.5.1` alone does not distinguish this feature branch from older code. + +Confirm the installation: + +```bash +which python +which metapathways +metapathways version +metapathways analysis_wf --help +nextflow -version +java -version +apptainer --version +magsplitter --help +``` + +`which` should point into your activated environment, or to an intentional site-managed executable. `analysis_wf --help` should list manifest and resource options. A help command does not run an analysis. If a command is missing, first confirm you activated the correct environment. On hosts that restrict user namespaces, Apptainer setup may require an administrator; see [Pathway Tools build prerequisites](pathway-tools.md#host-prerequisites). + +## First installation check + +```bash +mkdir -p ~/mp-reviewer +cd ~/mp-reviewer +metapathways build_db --test +metapathways run --test +``` + +The database command formats the bundled small reference fixtures and downloads support records for enzymes and taxonomy; it needs internet access and a writable installed fixture directory. The run command uses the bundled K12 assembly and paired reads, forces one thread for this example, and writes `~/mp-reviewer/test/k12_test/`. It does not invoke Pathway Tools. Do not pass your production data to `--test`: that flag selects its own inputs and output location. + +Expect annotation files under `test/k12_test/results/annotation_table/`, abundance under `test/k12_test/results/rpkm/`, and `test/reports/MP_run_report.html`. Inspect task status and logs if any expected output is absent. A report file existing is not by itself proof that all stages succeeded. + +```bash +metapathways report -o test --serve --no-rebuild +``` + +Keep this terminal running while browsing. Ctrl-C stops the report server, not the already completed analysis. On a remote server, use `--no-browser --port 8765` and the SSH tunnel instructions. + +## Your first real assembly + +The tiny test references are only for the example. Build or obtain a production MPDB before interpreting your own data: + +```bash +metapathways build_db -d ~/MPDB --func swissprot -a fast +metapathways run -i /path/to/sample.fasta -o ~/mp-results -d ~/MPDB \ + --threads 8 --max_cpus 8 --max_memory '32 GB' +``` + +The assembly goes through quality control, gene/RNA prediction, reference searches, and annotation. Without reads, there is no measured read abundance. Without a separate `ptools` step, there are no inferred PGDB pathways. A single `analysis_wf` command can combine these steps once the inputs and licensed container are ready. + +Continue with the [reviewer walkthrough](reviewer-test.md), [command cookbook](commands.md), and [input organization](inputs.md). + +## Terms used in the guides + +| Term | Meaning in MP | +| --- | --- | +| Assembly / contig | DNA sequences assembled from reads; each FASTA record is a contig | +| FASTA / FASTQ | Sequence file / read file with per-base quality scores | +| Paired / interleaved | Two mate files / one file with alternating mate records | +| ORF | Predicted protein-coding region; RNA features are also retained in relevant outputs | +| MAG / genome bin | A group of contigs assigned to a genome; MP consumes assignments, not a binning algorithm | +| MPDB | MP's reference sequences, indexes, taxonomy and functional mapping tables | +| MetaCyc | Reference pathways/reactions and associated proteins; not a sample's pathway predictions | +| PGDB | Pathway/Genome Database inferred for one community or genome bin | +| SIF | An Apptainer image containing the licensed Pathway Tools installation | +| Nextflow / task | Scheduler behind MP / one scheduled unit of work | +| Manifest | A TSV listing sample IDs and exact input paths | +| Receipt | MP's record used to decide whether a completed task can be reused | +| TSV / CSV | Table with tab-separated / comma-separated fields | diff --git a/docs/inputs.md b/docs/inputs.md new file mode 100644 index 0000000..72c3b5a --- /dev/null +++ b/docs/inputs.md @@ -0,0 +1,113 @@ +# Organize assemblies, reads and genome assignments + +[Home](../README.md) · [Command cookbook](commands.md) · [Manifest reference](../README.md#custom-analysis-manifest) + +## Decide what each sample means + +A sample is one assembly with its own reads and optional contig-to-genome assignments. The assembly is required. Reads add abundance measurements. A genome map adds genome-level splitting and PGDBs. MP does not assemble reads or infer bins itself. + +Choose sample IDs that begin with a letter and contain only letters, digits and underscores, for example `Oral_15`. Keep them stable between reruns. IDs such as `sample`, `Sample` and `SAMPLE` are distinct. Do not use reserved directory names such as `reports`, `logs`, `inputs`, `assemblies`, `reads` or `mag_maps`. + +`run -i ASSEMBLY_DIRECTORY` annotates multiple files, but it is not the automatic per-sample read/map matcher. Use `analysis_wf` for that complete workflow. It requires nucleotide FASTA; standalone `run` also has a protein-input mode. + +## Automatic discovery + +```text +my_inputs/ +├── assemblies/ +│ ├── SampleA.fasta +│ └── SampleB.fasta.gz +├── reads/ +│ ├── SampleA_R1.fastq.gz +│ ├── SampleA_R2.fastq.gz +│ └── SampleB_interleaved.fastq.gz +└── mag_maps/ + ├── SampleA.tsv + └── SampleB.tsv +``` + +Use `.fa`, `.fna` or `.fasta` for assemblies, optionally `.gz`. For reads use `.fq` or `.fastq`, optionally `.gz`. The suffixes `_R1`, `_R2`, `_interleaved` and `_single` specify the read layout. Matching is by sample ID, not file ordering or fuzzy similarity. Maps end in `.tsv`. + +```bash +metapathways analysis_wf -i my_inputs -o analysis -d /path/to/MPDB \ + --annotation_dbs swissprot metacyc \ + --taxprune --taxonomic_scope all \ + --threads 8 --max_cpus 32 --max_memory '64 GB' +``` + +Every sample needs one unambiguous layout and one map by default. MP stops on missing, unmatched or ambiguous inputs instead of guessing. Do not place both paired files and an interleaved file for the same sample in this discovery directory. Use `--no_reads` or `--no_mags` to omit that input type for the entire discovered dataset. `--no_mags` still allows community pathway inference; `--skip_ptools` skips all PGDB construction. + +If your directories are already separate: + +```bash +metapathways analysis_wf \ + -i /project/assemblies --reads_dir /project/reads --mag_maps_dir /project/maps \ + -o /project/analysis -d /project/MPDB \ + --taxprune --taxonomic_scope all +``` + +## Organize with links, without copying large reads + +A symbolic link gives an existing file another path without duplicating its data. Use absolute targets so moving the working directory does not change what they point to: + +```bash +mkdir -p my_inputs/assemblies my_inputs/reads my_inputs/mag_maps +ln -s /data/original/anonymous_gsa.fasta my_inputs/assemblies/SampleA.fasta +ln -s /data/original/anonymous_reads.fq.gz my_inputs/reads/SampleA_interleaved.fastq.gz +ln -s /data/original/contig_to_genome.tsv my_inputs/mag_maps/SampleA.tsv +``` + +The original files must remain readable throughout the workflow. The same assembly or read file cannot be reused under multiple manifest samples via hard/symbolic aliases; this catches accidental duplicated inputs. Independent reviewer fixture copies are intentional and documented separately. + +## Custom manifest: keep every file where it is + +Use a tab-separated file with this exact header: + +```text +sample_id assembly read_layout reads_1 reads_2 mag_map +``` + +The columns are real tabs, not the literal characters `\t`. A spreadsheet can save “tab-delimited text”; do not save an Excel workbook and rename it `.tsv`. Blank cells must remain blank, not `None` or `NA`. + +| Column | What to put in it | +| --- | --- | +| `sample_id` | Your chosen stable sample name; independent of assembly basename | +| `assembly` | Path to that sample's nucleotide FASTA | +| `read_layout` | `paired`, `interleaved`, `single` or `none` | +| `reads_1` | R1, the interleaved file, or the single-end file; blank for `none` | +| `reads_2` | R2 only for `paired`; blank otherwise | +| `mag_map` | Headerless contig-to-bin TSV, or blank to omit bins for that sample | + +Relative paths are resolved against the manifest's directory. Absolute paths make files easier to locate across terminal sessions; on a cluster, they must also work on compute nodes. Different samples can use different read layouts and omit different optional inputs through the manifest. + +```bash +metapathways analysis_wf --manifest /project/samples.tsv \ + -o /project/analysis -d /project/MPDB \ + --annotation_dbs swissprot metacyc \ + --taxprune --taxonomic_scope all \ + --threads 8 --max_cpus 32 --max_memory '64 GB' +``` + +Do not combine `--manifest` with discovery flags, `-1`, `-2` or `--interleaved`. The manifest carries those choices per sample. The resolved manifest and planned entities are saved in the output root as `inputs.resolved.tsv` and `inputs.entities.json`. + +## Contig-to-genome map format + +MAGSplitter needs exactly two tab-separated columns and **no header**: + +```text +contig_001 GenomeA +contig_002 GenomeA +contig_003 GenomeB +``` + +The first column is the original FASTA record ID: the token after `>` up to the first whitespace. Do not use MP's renamed `Sample-C123` IDs here. The second column is the bin ID. Contigs may be absent if unbinned, but every supplied contig must belong to the assembly and must occur at most once in the map. Periods in bin names become underscores; avoid names that collide after normalization. Use names beginning with a letter and consisting of letters, numbers or underscores; `community` and names containing `non_binned` are reserved. + +A contig removed by assembly QC cannot contribute features downstream. A mapped genome with no usable annotated features may have no generated PGDB input. Therefore the number of genome IDs in a map is an input inventory, not a promise of that many successful PGDBs. + +## CAMI ground-truth bins versus recovered MAGs + +CAMI `gsa_mapping.tsv` files provide original contig-to-source-genome assignments, often with taxon, source-sequence and coordinate columns. Convert only the anonymous contig ID and genome ID columns to the two-column format; keep the original file and an ID lookup if bin names are normalized. + +These maps are suitable for demonstrating MP's splitting and per-genome analysis features. Describe them as **ground-truth genome bins**, not experimentally recovered MAGs. They do not test a binning algorithm or realistic contamination/recovery errors. A source genome appearing in several samples creates several sample-specific bins, not several distinct reference genomes. + +For custom maps, validate duplicate IDs and completeness explicitly before a large benchmark. MP's workflow validation checks supplied IDs against assemblies, but assignment correctness remains a property of your source data. diff --git a/docs/pathway-tools.md b/docs/pathway-tools.md new file mode 100644 index 0000000..7e82cec --- /dev/null +++ b/docs/pathway-tools.md @@ -0,0 +1,169 @@ +# Pathway Tools: licensing, image builds, databases and inference + +[Home](../README.md) · [Reviewer walkthrough](reviewer-test.md) · [Complete flags](cli-reference.md) + +## Understand the three different databases + +| Name | What it contains | How you use it | +| --- | --- | --- | +| MPDB | Reference protein/RNA sequences, search indexes, taxonomy and mapping tables | `-d /path/to/MPDB` on annotation/workflow commands | +| MetaCyc in Pathway Tools | Reference biochemical knowledge used for pathway inference | Bundled in an appropriate licensed Pathway Tools distribution | +| Your PGDB | Inferred pathways/reactions and gene associations for a community or genome bin | Created by `ptools` or `analysis_wf` under the sample output | + +Adding MetaCyc to **MPDB** enables another protein annotation search. Pathway Tools can infer pathways from SwissProt-derived annotations without that search: it still consults its own bundled MetaCyc knowledge base. Therefore “without MetaCyc annotation” does not mean “without MetaCyc pathway knowledge.” + +EcoCyc describes E. coli; MetaCyc is a multi-organism reference; BioCyc is the collection of organism PGDBs. Compare sample pathway counts with the appropriate kind of database and counting unit. Base pathways, superpathways, and signaling pathways are not interchangeable totals. + +## Get the installer + +Start at the official [Pathway Tools site](https://www.pathwaytools.org/) and its licensing/download link. SRI provides separate academic and commercial licensing routes. The [academic license page](https://bioinformatics.ai.sri.com/ptools/licensing/ptools-academic-license.shtml) describes eligibility and the request process; SRI sends download instructions to the approved technical contact. Use the terms supplied by SRI for your organization. + +Download the **Linux x86-64 installer**, even if your browser is on a Mac or Windows laptop: MP builds a Linux container on the analysis server. Choose a licensed distribution containing MetaCyc; the vendor describes its editions in the [installation guide](https://www.pathwaytools.org/installation-guide/released/index.html). Retain the installer filename, version, download records and checksum. Download addresses provided in license correspondence need not be public. + +If it is on your laptop, copy it to the server using your normal file-transfer method. For example, in a local terminal, replacing the username and host: + +```bash +scp ~/Downloads/pathway-tools-29.5-linux-64-tier1-install user@server:~/Downloads/ +``` + +Create the destination directory on the server first if needed. Do not unpack or manually run the installer before giving it to `build_pt`. MP performs the unattended installation within the build. Version 29.5 is a tested example, not a claim that it is the newest version. Consult the vendor's [release notes](https://bioinformatics.ai.sri.com/ptools/release-notes.html) for newer releases and verify their installer compatibility separately. + +## Host prerequisites + +Activate the MP environment and check `apptainer --version` and `nextflow -version`. Building requires network access for the container base, operating-system packages and official patches, plus writable space for the installer, temporary build and finished SIF. A build can temporarily use substantially more disk than the final image. Use `df -h` to inspect free space. + +The host must permit Apptainer's unprivileged/fakeroot build path. Administrators may need to configure subordinate UID/GID ranges and the `newuidmap`/`newgidmap` helpers (`uidmap` on Ubuntu). Installing a Conda executable cannot override a host security policy. Ask your administrator if a user-namespace or fakeroot error appears. Docker is not required. + +Use shared storage for a finished image that compute nodes need to read. Local scratch can accelerate building on slow network filesystems. `APPTAINER_TMPDIR` is an optional Apptainer troubleshooting setting, not required to run MP. See your site's Apptainer setup when choosing scratch; it must have enough space. + +## Build and register once + +Run on the server, with the environment active: + +```bash +metapathways build_pt \ + -i ~/Downloads/pathway-tools-29.5-linux-64-tier1-install \ + -o ~/mp-containers +``` + +MP uses Nextflow to build the image, download official release-specific SRI patches, validate the installation, and register the resulting SIF. Validation checks Pathway Tools startup and a small BLAST database/search. Wait for the build command to complete successfully before launching dependent analyses. + +`-o` is the image directory. Without it, the default is `~/.local/share/metapathways/containers` (or its XDG equivalent). Registration is stored at `~/.config/metapathways/ptools.json` (or its XDG equivalent). The adjacent `.sif.json` records provenance, including hashes and patch records. `--ptools_version 29.5` supplies a version when MP cannot recognize a renamed installer. `-t 2` controls compression CPUs, not the number of CPUs used by later PGDB tasks. + +An explicit new build creates a new image and preserves older images. Automatic patch downloads are disabled during analyses, so runs use the patch snapshot built into that image. There are no MP-authored edits to licensed Pathway Tools code or MetaCyc frames. A successful image validation does not prove that every possible genome will infer successfully. + +Subsequent `ptools` and `analysis_wf` commands use the registered SIF automatically. No image environment variable is necessary. To pin a particular image for a comparison, add: + +```text +--image /absolute/path/to/pathway-tools-VERSION-HASH.sif +``` + +Explicit `--image` takes precedence over the environment override and registration. Do not delete a SIF referenced by a running task. Rebuilding an image or changing the selected path can invalidate PGDB task reuse. On Slurm the selected path must be readable at the same location on all compute nodes. + +## Build the MPDB MetaCyc annotation reference at the same time + +Prepare public references first, then build the licensed image and add its MetaCyc reference: + +```bash +metapathways build_db -d ~/MPDB --func swissprot -a fast +metapathways build_pt \ + -i ~/Downloads/pathway-tools-29.5-linux-64-tier1-install \ + -o ~/mp-containers -d ~/MPDB -a fast +``` + +The second command exports the bundled MetaCyc protein sequences and biochemical flat files from the SIF, constructs protein-to-reaction mappings and pathway/compound/ontology tables, and indexes the proteins for FAST. It does not refresh SwissProt or the other existing references. The [installed-file table](../README.md#metacyc-from-pathway-tools) lists the exact MPDB destinations. + +To add or rebuild MetaCyc later using the registered image: + +```bash +metapathways build_db -d ~/MPDB --func metacyc -a fast +``` + +To choose a different licensed source: + +```bash +metapathways build_db -d ~/MPDB --func metacyc -a fast \ + --metacyc_source /path/to/pathway-tools.sif +``` + +`--metacyc_source` also accepts a local complete exported MetaCyc `data/` directory. It needs `protseq.fsa`, `proteins.dat`, `enzrxns.dat`, `reactions.dat`, `pathways.dat`, `compounds.dat`, and `classes.dat`. A `protseq.fsa` alone is insufficient even if its sequence statistics match another FASTA. Some native installs keep most knowledge-base data in the executable; the SIF export obtains the missing flat files. + +Use `-a blast` if subsequent annotation will use `--annotation_algorithm BLAST`. MetaCyc rebuilding replaces its existing reference and removes obsolete index files, including the other aligner's indexes. **Do not rebuild a reference directory while analyses are reading it.** Use a separate MPDB for a concurrent reference-version comparison. + +The ordinary public-reference build does not acquire licensed MetaCyc. You supply the authorized installer or data. MP does not grant permission to redistribute the installer, SIF, patches or reference files; preserve them according to the applicable vendor terms. + +## Run pathway inference + +For an annotated sample at `results/SampleA`: + +```bash +metapathways ptools -o results/SampleA \ + --entity community --taxprune --taxonomic_scope all \ + --max_cpus 8 --max_memory '32 GB' +``` + +For all available entities, omit `--entity`: + +```bash +metapathways mag_split -o results/SampleA -m /path/to/SampleA.tsv +metapathways ptools -o results/SampleA \ + --taxprune --taxonomic_scope all \ + --max_cpus 8 --max_memory '32 GB' +``` + +`--entity MAG_001` selects one actual normalized MAG ID. There is no `--entity MAGS` keyword. Omitting the flag includes the community and available genome bins; successful unchanged entities can be reused. + +`-o` here is the **sample directory**, unlike `run` and `analysis_wf`, whose `-o` is the parent output directory. A wrong level can make MP look for missing `ptools/0.pf` inputs. + +Every PGDB task uses one CPU. Concurrency comes from multiple independent PGDB tasks; assigning eight threads does not make one Pathway Tools process eight times faster. `ptools --memory` controls each standalone PGDB reservation; `analysis_wf --ptools_memory` controls PGDB reservations within the complete workflow (default 4 GB). The total `--max_memory` still bounds scheduled reservations. Local reservations are not hard memory ceilings. + +SIF tasks receive private home, data and temporary state. MP also isolates X-display sockets; independent PGDBs can run together without the native installation's shared state. Native Pathway Tools remains a legacy serialized option for standalone `ptools`; the complete `analysis_wf` requires the SIF route. The old `--container` flag is not a synonym for `--image`; use the image route shown here. + +## Choose a taxonomic scope + +`--taxprune` enables taxonomic pruning. `--taxonomic_scope` selects the organism taxon assigned to the staged PGDB inputs: + +| Scope | NCBI taxon | Use | +| --- | ---: | --- | +| `all` | 131567 | Broad cellular-life scope for a mixed community | +| `bacteria` | 2 | A bacterial community or bacterial genome | +| `archaea` | 2157 | An archaeal community or archaeal genome | +| `eukaryotes` (`euks`) | 2759 | Eukaryotic inputs | + +`all` includes multicellular eukaryotes; it is not a microbial-only or unicellular filter. There is no supported `prokaryotes` union scope. `--taxon_id NCBI_ID` allows a more specific positive numeric taxon and is mutually exclusive with the convenience scope flag. + +The scope applies to all selected entities in that invocation. It guides pathway inference; it does not remove contigs or rewrite MP's gene-level taxonomic annotations. To use different scopes for different MAGs, run separate entity-specific `ptools` commands. + +**Set both flags intentionally.** Specifying `--taxonomic_scope all` alone does not turn pruning on. Omitting the flags preserves historical behavior: pruning is off by default and the input taxon is retained. In Pathway Tools 29.5 the no-pruning route includes a second unpruned rescore pass. We observed a compound/inverse-link failure in that pass; `--taxprune --taxonomic_scope all` avoided it in tested community/MAG runs. This is not proven equivalent to unpruned inference and does not disable all other pathway-selection rules. Record the choice in your methods. + +See the vendor User Guide's batch PathoLogic discussion and [MP's diagnostic detail](workflow.md#pathway-tools-failure-diagnostics). The installed PDF is authoritative for the installed version. + +## Transport inference and sequence-backed inputs + +Transport inference (TIP) is enabled by default for SIF runs. It uses annotations to identify probable transport proteins and associate or create transport reactions. High- and low-confidence predictions are reported separately. Low-confidence or ambiguous annotations are not equivalent to experimentally demonstrated transport. + +`--no_transport_inference` disables TIP for a controlled comparison. It is accepted by `ptools` and `analysis_wf`. Record it when comparing pathway/reaction totals; TIP can change reactions without changing the number of base pathways. + +MP stages real per-contig DNA sequences, feature coordinates, strands and available Prodigal genetic codes before invoking Pathway Tools. This allows Pathway Tools to derive its protein BLAST database. The BLAST tools **inside the SIF** serve that function; they are separate from FAST/BLAST annotation indexes **in MPDB**. + +Annotations with multiple EC assignments are written as separate EC entries. Provisional EC identifiers are retained and may be rejected by Pathway Tools. Recognized tRNA display names separate amino-acid labels from anticodons, while stable feature IDs are preserved. Some ID-parsing warnings can remain. Neither formatting step invents biological assignments. + +## Outputs, warnings and failures + +Look under `results/SampleA/results/pgdb/community/` and `.../MAGs/MAG_ID/` for the archive, pathway table and pathway-to-ORF table. Each attempt retains `diagnostics/ATTEMPT/execution.json` and available logs. `input/pathologic.log` contains the internal inference messages; `build-xvfb.log` and `export-xvfb.log` contain display-wrapper diagnostics in the corrected version. + +| Symptom | What to check or do | +| --- | --- | +| No registered image | Complete `build_pt`, or specify an existing readable `--image` | +| Installer version not recognized | Keep its original filename or supply `--ptools_version` | +| `debconf: delaying package configuration` | This message alone is normal in a minimal image; inspect the final build status | +| Missing compound / inverse-link failure | Check `pathologic.log`, image/patch provenance and scope flags; do not delete reference compounds to suppress it | +| Protein BLAST DB cannot be created | Check sequence staging and the internal log; installing BLAST alone cannot supply missing sequence | +| `Done` followed by failure | Check the recorded phase and wrapper logs; `Done` is not a substitute for successful export/archive | +| Provisional EC or ambiguous transport warning | Keep the evidence; a formatting change cannot establish a missing biological assignment | +| MAG lacks selected genes | The complete workflow can skip a bin with no generated PF input; distinguish this from zero inferred pathways | +| Nonzero exit during export | Preserve the saved PGDB and diagnostics; do not label the result complete from build messages alone | + +Community failures fail the workflow. MAG failures may be optional, allowing other entities to finish, but remain failures in task records. `SUCCESS` at the overall scheduler level can coexist with optional failures. Never use it alone to claim all MAGs succeeded. The report distinguishes output availability from latest task outcome. + +Failed on-disk PGDBs are retained under `diagnostics/ATTEMPT/failed-pgdbs/`. MP does not automatically certify or publish partial recovery. Retry with the same parameters after fixing the cause, and inspect the new execution record. [Restart guidance](../README.md#logs-temporary-files-and-restarting) explains reuse and targeted reruns. diff --git a/docs/pr-testing.md b/docs/pr-testing.md new file mode 100644 index 0000000..13cf64a --- /dev/null +++ b/docs/pr-testing.md @@ -0,0 +1,16 @@ +# PR tester checklist + +[Home](../README.md) · [Reviewer commands](reviewer-test.md) · [Release process](releasing.md) + +Test the feature branch before merging to `dev` or `master`. Use a clean installation and a fresh output directory. Record `git rev-parse HEAD`, the platform, and the installed dependency versions. Version 3.5.1 alone does not identify this branch. + +1. Follow [source installation](getting-started.md). Check out the PR's exact commit after cloning; do not test an older editable installation by accident. Record the MAGSplitter and Camelot revisions installed separately. +2. Follow the [CAMI reviewer walkthrough](reviewer-test.md), running its single-sample and two-sample commands with `--skip_ptools`. Check required task outcomes, nonempty abundance outputs, the three genome-bin assignments per sample, and distinct paired read paths. +3. Repeat the two-sample command unchanged. All successful workflow tasks, including `COMPUTE_TPM`, should report `ALREADY_COMPUTED`. Report rebuilding may still run. A repeat is not a fresh performance measurement. +4. Run all three inputs through automatic discovery with a new output directory. Confirm the same sample IDs and input associations as `all.tsv`. Test an intentionally mismatched filename in a separate copy: planning must stop with an actionable input-layout error. +5. Serve the report and open `EDA_portal.html`. Filter each sample, search annotations, and export a CSV. Confirm sample/entity IDs and absence of mixed sample records. Sparse annotations and empty RNA/pathway tables may be expected with the tiny reference fixture; skipped pathways must not appear as successful inference. +6. If licensed, build a Pathway Tools image from your installer. Repeat a small workflow into a fresh output with `--taxprune --taxonomic_scope all` and without `--skip_ptools`. Confirm community/MAG status, sequence-backed inputs, archives and pathway exports. Keep licensed inputs/images private. Record expected no-pathway outcomes separately from failures. +7. If a cluster is available, test a small submission using the documented Slurm settings. Confirm scheduler resource requests and bounded concurrent submissions. Otherwise explicitly mark Slurm untested. +8. Have a maintainer manually run the Release workflow on this branch with **blank `release_tag` and `source_run_id`**, optionally enabling `test_containers`. Review the Conda installed-package integration, container validation, and security reports. No release tags or public uploads are needed for this step. + +Attach the tested commit, commands, task summaries, dependency versions, and relevant logs to the PR, with local credentials and private input paths removed as needed. State which optional checks were not performed. A maintainer should resolve failures and obtain sign-off on the final commit before merging; subsequent code changes require retesting the affected behavior. diff --git a/docs/release-readiness.md b/docs/release-readiness.md new file mode 100644 index 0000000..90b8b0c --- /dev/null +++ b/docs/release-readiness.md @@ -0,0 +1,28 @@ +# Nextflow feature release readiness + +[Release instructions](releasing.md) · [Tester checklist](pr-testing.md) + +This records the local preparation audit on 2026-10-02 for `feat/nextflow-controller-db-build`. It is not a published-release certificate. The selected next version is 3.5.2, prepared locally at the user’s request. No release tag has been published. + +## Prepared and locally checked + +- PR/push smoke checks cover `master`, `main`, `dev`, and feature-branch pushes. +- Release publishing requires a clean `dev`/`master` checkout; a feature branch cannot use the publish helper. +- Manual Release dispatch with blank publication inputs builds/test artifacts without public uploads. `test_containers` additionally validates Docker/SIF and scans the image. +- Conda recipe includes Nextflow and Apptainer, expanded CLI checks, and an exact source SHA256. Rendering passed; full package solve/build remains a CI check. +- Core CI integration has explicit small-fixture resource budgets. +- Source archive and Linux x86-64 CPython 3.11 wheel built successfully from an isolated copy of the working tree. The native-binary wheel is no longer marked `py3-none-any`. +- Wheel installed in a temporary environment; all eight CLI entry/help checks passed outside the source checkout. This environment shared runtime dependencies with the existing environment; it was not a fresh Conda solve. +- Installed workflow modules, native binaries, report assets, all three CAMI manifests, and fixture SHA256 hashes passed inspection. +- 102 runtime/unit tests passed across the initial run and the report-test rerun with localhost permission; 17 release-control tests passed. These include fake local Git remotes; no actual publication occurred. +- CFF schema validation passed; release preparation updates its version. Documentation links, CLI examples and shell syntax passed. + +## Required before merge/release + +1. Commit and push the reviewed feature work, open a PR targeting `dev` or `master`, and record its exact commit. No branch push, PR creation or publication was performed by this local audit. +2. Run PR smoke checks and the nonpublishing Release workflow on that commit. Confirm a fresh Conda solve/build/install, K12 integration, Docker integration, SIF startup and security scan. These full builds were not run locally during the benchmark. +3. Obtain independent tester sign-off using the CAMI single/pair commands, checkpoint reuse, explorer exports, and any applicable Pathway Tools/Slurm checks. MAGSplitter and Camelot remain separately installed dependencies; the public container does not certify the complete licensed workflow. +4. Verify account-side Anaconda/Quay credentials and permissions, GitHub branch protection, and the Zenodo repository connection. None of these settings were verified locally. Review software authors and third-party fixture redistribution terms before public release. +5. Use the selected version 3.5.2, merge after testing, and publish only through the documented release process. Confirm actual uploaded artifacts, checksums/digests and Zenodo record contents/DOI afterward. + +The source/archive audit artifacts are local temporary files under `/data/tmp/mp-package-audit-xpb6ytrx`; retain CI artifacts for the actual reviewed commit instead of treating this uncommitted snapshot as the release. diff --git a/docs/releasing.md b/docs/releasing.md index ed15991..07fd584 100644 --- a/docs/releasing.md +++ b/docs/releasing.md @@ -1,8 +1,12 @@ # Releasing MetaPathways +[User documentation](../README.md) · [Reproducibility](reproducibility.md) + +This chapter is for maintainers publishing packages, not users installing or running MP. Its release examples describe the existing 3.5.x release process. The Nextflow feature branch must undergo release validation before its behavior is claimed for a published package. + The source version in `metapathways/_version.py` is authoritative. An installed `3.5.0.dev64` package is an older distribution; changing GitHub does not upgrade -that environment. The first stable release from this checkout is **3.5.0**. +that environment. The original stable release in this release series was **3.5.0**. Use **3.5.1**, **3.5.2**, etc. for subsequent patch releases, or **3.5.1rc1** for a preview. Tags have a leading `v`; package versions do not. @@ -14,21 +18,21 @@ and silently include them in the Conda package. ## Normal release using GitHub CI -From a normal checkout of `dev`, using your existing Git SSH/HTTPS credentials: +After tester sign-off and merging the PR, from a clean checkout of the reviewed release branch (`dev` by default), using your existing Git SSH/HTTPS credentials: ```bash -python scripts/release.py prepare 3.5.0 +python scripts/release.py prepare 3.5.2 git diff -git add README.md metapathways/_version.py conda_recipe/meta_template.yaml -git commit -m "Prepare MetaPathways 3.5.0" -python scripts/release.py publish +git add README.md CITATION.cff metapathways/_version.py conda_recipe/meta_template.yaml +git commit -m "Prepare MetaPathways 3.5.2" +python scripts/release.py publish --branch dev ``` Commit the release script, workflow, tests, and other implementation files as well when installing this workflow for the first time. If `prepare` changes nothing, there is no version-only commit to make. -`publish` requires a clean checkout on `dev`. It creates an annotated tag and +`publish` requires a clean checkout on the selected release branch (`dev` by default; `--branch master` selects `master`). It creates an annotated tag and pushes the branch and tag atomically to `hallamlab/MetaPathways`. It never force pushes, moves a published tag, or automatically commits your work. GitHub CLI login is unnecessary on your machine. @@ -50,7 +54,7 @@ GitHub prereleases and use the `hallamlab/label/rc` Conda channel; stable versio use `hallamlab` / label `main`. No wheel is advertised as platform-independent. To test CI without publishing, select **Actions → Release → Run workflow** on -the `dev` branch. Assets are retained as an Actions artifact. Dispatching the +the feature branch (or the reviewed `dev`/`master` branch). Leave `release_tag` and `source_run_id` blank; optionally enable `test_containers` to build and scan Docker/SIF artifacts too. This does not publish packages, registry images, a GitHub release, or a DOI. Assets are retained as an Actions artifact. Dispatching the workflow on a release tag also enables publishing. ## Enable Anaconda.org uploads @@ -71,8 +75,8 @@ build/test environment: ```bash mamba create -n metapathways-build -c conda-forge \ - python=3.10 conda-build conda-index anaconda-client pyyaml \ - pip wheel 'setuptools<81' + python=3.11 conda-build conda-index anaconda-client pyyaml \ + pip wheel 'setuptools>=83,<85' conda activate metapathways-build python -m pip install build @@ -206,10 +210,10 @@ Licensed Pathway Tools is not included in public release containers. ## Security rebuilds without changing the application version -The security rebuild of MetaPathways 3.5.1 uses Python 3.11, Snakemake minimal +The historical security rebuild of MetaPathways 3.5.1 used Python 3.11, Snakemake minimal 9.27.0, urllib3 >=2.8.0, and setuptools >=83. The minimal Snakemake distribution provides the local CLI used for database preparation without the legacy stopit -runtime dependency. Container builds refresh the base image and apply Debian +runtime dependency. This records that release configuration; the current development workflow uses Nextflow, as described in the user guide. Container builds refresh the base image and apply Debian package updates before installing the validated Conda environment. A nonzero Conda build number produces a separate Git tag and release, for example @@ -219,7 +223,7 @@ original tag and published files. Prepare it with: ```bash python scripts/release.py prepare 3.5.1 --build-number 1 # Commit the reviewed changes, then: -python scripts/release.py publish +python scripts/release.py publish --branch dev ``` Quay receives `3.5.1-build1` and `v3.5.1-build1` tags as well as updated `3.5.1`, @@ -237,3 +241,36 @@ the runner and blocks publication when it finds a high/critical vulnerability for which a fix is available. Both the full scan and filtered gate reports are retained as `container-security-report`. Unfixed distribution advisories need separate review; passing this gate does not mean the image has no vulnerabilities. + +## Feature-branch review before publication + +The intended sequence is **feature branch → single-server and HPC benchmarks plus tester review → PR merge to dev/master → release tag → publication**. Pushing a branch or opening a PR does not publish a release. Smoke checks run for PRs targeting `master`, `dev`, or a future `main`, and pushes to those branches or `feat/**`. They validate the citation file, unit tests, docs, source/wheel builds, installed CLI entry points, and packaged reviewer/report assets. + +Use the [PR tester checklist](pr-testing.md) for independent installation, the single- and two-sample CAMI workflows, restart behavior, optional licensed Pathway Tools, and report exports. Record the tested Git commit. The currently installed version number alone is insufficient while development still reports 3.5.1. + +The selected next release is **3.5.2**. Preparing this version does not publish it; branch and PR testing still happen before a release tag is pushed. Do not reuse 3.5.1 or its existing tags. Change the version with `prepare` only at the release step; it also updates the citation version and resets the Conda build number for a new version. Avoid editing runtime code/version files while a benchmark is executing from an editable checkout. + +Before merging, manually dispatch the Release workflow on the feature branch with blank publication inputs. Select `test_containers` to test the exact Conda artifact inside Docker and its SIF conversion. Download `release-assets`, `container-assets`, and the security reports from Actions for review. Core integration uses explicit 2 GB task reservations, a 4 GB memory budget, and two CPUs so the small fixture fits CI runners. These limits are not production metagenome sizing recommendations. + +The public Conda package/container includes the Nextflow controller and reporting assets, but MAGSplitter and Camelot are still separately installed optional dependencies. The public build gate exercises the core K12 workflow; **passing that gate does not certify `analysis_wf` with MAGs, Slurm, nested Apptainer, or licensed Pathway Tools**. Those require the tester checks. A container containing Apptainer does not guarantee the host permits nested container execution. Test licensed inference with the recommended host Conda installation and your own image first. + +## Zenodo and software citation + +`CITATION.cff` supplies software authors (from MP's existing author metadata), title, repository, and license. Confirm the author list before publication. No DOI or release date has been invented. `prepare` adds/updates the selected software version. We maintain one citation metadata file; Zenodo prioritizes `.zenodo.json` over CFF if both exist, so do not add a conflicting second file. See [Zenodo's supported metadata](https://help.zenodo.org/docs/github/describe-software/). + +A repository administrator must link their GitHub account to Zenodo, grant the required organization access, and enable `hallamlab/MetaPathways` in Zenodo's GitHub settings. See [enable a repository](https://help.zenodo.org/docs/github/enable-repository/). This connection is account-side configuration and cannot be inferred from committed files or the existence of an earlier release. Our GitHub Actions workflow does not call the Zenodo API or store a Zenodo token. + +Keep pre-merge tests as branches, PRs, and Actions artifacts. Once enabled, the integration ingests new releases; do not publish a release candidate casually if you are not ready for it to become an archive record. After the intended release, verify its Zenodo record, version, source commit/tag, author metadata, license, and DOI before announcing it. Record both the version-specific DOI and concept DOI where applicable, and use the version-specific DOI for an exact release citation. + +Treat the software snapshot, built packages/container assets, and manuscript benchmark data as separate deliverables. Do not assume the GitHub integration copies every release attachment or later-added SIF, nor that it deposits your benchmark outputs. Inspect the archive contents and arrange a separate data deposit with its own provenance if required. Never deposit the licensed Pathway Tools installer, SIF, or MetaCyc databases as public MP assets. + +## Account-side release checklist + +| Service | Repository preparation | Maintainer verification before publishing | +| --- | --- | --- | +| GitHub | PR smoke checks, manual package/container validation, tag workflow | Protect the target branch, require smoke checks and tester approval; choose a new version | +| Anaconda.org | Recipe, installed-package integration, checksums, RC/main labels | `ANACONDA_API_TOKEN` has upload access to `hallamlab`; `PUBLISH_CONDA=true` | +| Quay | Build from validated package, Docker test, SIF conversion, vulnerability gate | Repository exists; robot has Write permission; `QUAY_USERNAME`, `QUAY_PASSWORD`, `PUBLISH_QUAY=true` | +| Zenodo | CFF metadata and documented release process | GitHub integration enabled, correct organization authorization, archived release/DOI verified | + +Secret values must never be committed or printed. Repository files alone cannot verify the current account permissions or secret configuration. A local source build is not proof of a successful Conda solve, registry upload, or Zenodo deposit. diff --git a/docs/reports-tutorial.md b/docs/reports-tutorial.md new file mode 100644 index 0000000..8720a2e --- /dev/null +++ b/docs/reports-tutorial.md @@ -0,0 +1,84 @@ +# Explore results, follow links and export tables + +[Home](../README.md) · [Exact schema and SQL](results-schema.md) · [Benchmark statistics](benchmarking.md) + +## Open the report or start the explorer + +The report and explorer serve different purposes. `MP_run_report.html` provides accounting and navigation to results/logs. `EDA_portal.html` queries the SQLite index so you can search, filter, follow related records and export CSVs. The explorer requires its local Python server; double-clicking the explorer HTML alone does not start that server. + +After a completed workflow: + +```bash +metapathways report -o /path/to/analysis --serve --no-rebuild +``` + +Keep the terminal open. MP prints a local address and normally opens your browser. Ctrl-C stops the server. To refresh the index after results change, omit `--no-rebuild`. Report generation reads existing output; it does not rerun annotation or infer missing pathways. + +Use the parent directory containing sample folders to combine samples in one report. Using a single sample directory limits that report to the sample. Report files live under the selected root's `reports/` directory. + +## View a remote report through SSH + +On the **remote server**, activate the MP environment and run: + +```bash +metapathways report -o /remote/path/to/analysis \ + --serve --no-rebuild --no-browser --port 8765 +``` + +On **your local computer**, in a second terminal, replacing `user@server` with the same SSH destination you normally use: + +```bash +ssh -N -L 8765:127.0.0.1:8765 user@server +``` + +The tunnel command may appear idle; that is normal. Leave both terminals running. Open these addresses in your local browser: + +- Explorer: +- Run report: + +`-L` forwards the local port to the server's loopback port, and `-N` asks SSH to provide forwarding without a remote shell. Use your site's SSH host alias or jump-host configuration when required. MP listens only on loopback; you do not need to expose the server publicly or open a firewall port. + +If local port 8765 is busy, forward another local port with `-L 8766:127.0.0.1:8765`, then browse to `localhost:8766`. If the remote port is busy, choose a different `--port` and update the tunnel's destination port too. A page that loads but cannot query may be an old static copy or an HTML file opened without the server. + +## Start with accounting + +Open the run report before interpreting tables. Review which samples and products were found, source/import notes, and task execution records. Optional MAG failures can coexist with overall workflow success. A file from an earlier successful attempt can coexist with a failed newer attempt; output availability and latest task status answer different questions. + +Check a few known sample IDs and original contig IDs. If expected tables are empty, inspect the inventory and task logs before interpreting zeros. Missing output does not mean the organism lacks a function. + +## Follow one annotation through the results + +1. Choose **ORFs and taxonomy** and filter to a sample. +2. Search for an ORF ID or product term you recognize. +3. Follow its related annotation records to inspect database accessions and EC/reaction assignments. +4. Follow pathway associations, keeping both sample and entity IDs selected. +5. Export the filtered table with identifying columns included. + +A primary ORF annotation is not identical to all database hits. **Functional annotations** retains reference records; a gene can have more than one. **Pathway genes** contains pathway/ORF associations, so a gene in several pathways appears several times. The [schema](results-schema.md) describes each row unit and join key. + +## Select useful subsets + +| Question | Starting table and filters | +| --- | --- | +| Which SwissProt annotations mention kinase in this sample? | Functional annotations: sample, reference database, product text | +| Which genes support a particular MAG pathway? | Pathways: sample, entity, pathway ID; follow Pathway genes | +| What are all reported genes on contigs assigned to a MAG? | MAG ORFs: sample and entity | +| Which genes were supplied to MAG pathway inference? | MAG input genes: sample and entity | +| What abundance measurements exist for an ORF? | Abundance: sample, feature type, feature ID, measurement | +| Where is the raw GFF, RNA output, BAM or PGDB archive? | File inventory / run-report output links | + +**MAG ORFs** uses the full contig map. **MAG input genes** is the smaller set selected for Pathway Tools; it is not the total gene content of the bin. Similarly, input genome-bin counts need not equal successful PGDB counts. + +The portal provides text searches and column/related-result filters, not biological plotting. Choose the columns needed for downstream work and export all matching rows as CSV. Pagination limits what is displayed, not the full filtered export. Retain the query definition or bookmarked URL and record the report snapshot used for an analysis. + +## Avoid accidental double counting + +Always keep `sample_id`. Keep `entity_id` for pathways and genome results. The same ORF-looking identifier can occur in different samples, and the same pathway can occur in the community and many bins. + +Do not sum abundance after joining each gene to all its annotations and all its pathways: many-to-many joins multiply rows. Decide whether you need unique genes, annotation records or pathway associations before aggregating. Pathway scores are reported inference values, not universal probabilities of biological truth. See [safe SQL examples](results-schema.md#sql-with-explicit-joins). + +## Share or archive a result + +Filtered CSVs can be shared independently. To retain the explorer and original-file navigation, preserve the complete output root, including its `reports/`, sample results and logs, and serve it with a compatible MP installation. `results.sqlite` and `schema.json` also support direct read-only analysis in Python/R/SQLite. + +Not every raw product becomes a relational table: the inventory links additional sequences, alignments, RNA reports and PGDB products. Import notes identify missing or unsupported sources. The portal does not silently infer missing data, recalculate abundance or validate historical mapping provenance. diff --git a/docs/reproducibility.md b/docs/reproducibility.md new file mode 100644 index 0000000..977728f --- /dev/null +++ b/docs/reproducibility.md @@ -0,0 +1,59 @@ +# Reproducibility and validation + +[User guide](../README.md) · [Release process](releasing.md) + +## Record the actual revision and inputs + +MetaPathways is distributed under the [MIT license](../LICENSE); bundled third-party sources retain their notices. GitHub tags, Conda packages and container images are separate publications. A tag alone does not update the other distributions. Record the source Git commit, package build or immutable container digest used for each analysis. + +Preserve: + +- Assembly/read identifiers, layout (single, paired or interleaved), checksums and sample naming. +- Original contig-to-MAG maps, including the binning version/method and QC decisions. +- MP commands, workflow parameters, tool versions and environment exports. +- Reference releases, acquisition dates and file checksums; public downloads can change. +- The Pathway Tools installer/image checksum, version and taxonomic-pruning setting. +- Final outputs, run logs, Nextflow trace/report/timeline and report `sources`/`schema.json`. + +Example environment records: + +```bash +git rev-parse HEAD > metapathways-commit.txt +conda list --explicit > conda-explicit.txt +python -m pip freeze > pip-freeze.txt +metapathways version > metapathways-version.txt +``` + +The environment specification in `docker/conda_base.yml` is not an exact lock. Optional MAGSplitter/Camelot installations from branch URLs move over time; the resolved Git revisions in `pip freeze` matter. The source revision's setup checks used Nextflow 26.04.6, Python 3.11 and Apptainer 1.5.4, with Pathway Tools 29.5 startup validation. This does not establish end-to-end biological equivalence for the orchestration migration. + +## Installation example versus biological validation + +`build_db --test` formats bundled SwissProt/SILVA sequence fixtures and downloads current ExPASy/NCBI support records into the installed package. `run --test` uses the included K12 FASTA and paired reads. It is neither offline nor fully pinned, and it does not run Pathway Tools. + +The current feature work has synthetic/unit checks for read-layout arguments, task ordering/resources, resume/cleanup, container isolation interfaces, report joins and export behavior. Real synthetic Nextflow tasks exercise scheduling and logging; concurrent Pathway Tools startup checks exercise private container state. These checks do not substitute for real annotations, PGDB construction, or execution on an actual Slurm cluster. The small reviewer walkthrough and any user-run benchmarks must be evaluated through their retained results and task records. Do not infer full biological validation from unit-test success. See the [reviewer protocol](reviewer-test.md) and [benchmark measurement guide](benchmarking.md). + +Run the software checks from the checkout: + +```bash +python -m unittest discover -s tests -p 'test_*.py' +python -m unittest discover -s tests/release -p 'test_*.py' +python scripts/check_docs.py +``` + +The report HTTP tests require permission to bind a temporary loopback socket. Biological integration checks require the full Conda environment, appropriate references and an explicit decision to run them. Reports created from existing outputs perform indexing only. + +## Historical benchmark provenance + +The repository's previous reproducibility notes describe the [v1 preprint](https://doi.org/10.1101/2024.06.04.597460), section 3.1, as reporting 15 CAMI2 Human Microbiome metagenomes and 622 MAGs from five body sites, SwissProt 2023_05, MetaCyc 27.1, MetaBAT2 2.15 and Pathway Tools 27.0, with 16 cores on Ubuntu 20.04.6. These are historical settings, not the defaults or a newly verified reproduction of this source revision. + +The [CAMI2 study](https://doi.org/10.1038/s41592-022-01431-4) identifies the human collection at [PUBLISSO, DOI 10.4126/FRL01-006425518](https://doi.org/10.4126/FRL01-006425518). A collection DOI does not identify the exact assembly/read/bin selections used by a particular benchmark. The K12 installation fixture does not substitute for those records. + +A fresh benchmark needs a complete sample/input manifest, contig maps, reference/software versions, resource limits, commands and retained task traces. Historical output affected by the paired-read mapping bug must have mapping corrected before abundance is used. Expected MAG Pathway Tools failures should be recorded as such; they are not evidence that no pathways exist. + +Only measured trace fields should support resource plots. A report rebuilt over old outputs cannot recreate missing peak RAM, CPU time or stage runtime. Reused tasks, failed tasks, incomplete output and successful fresh tasks must be distinguished when making supplementary tables or benchmark claims. Report database row counts are data-accounting units, not performance measurements. + +## Documentation and release records + +Documentation is maintained in this README-led GitHub tree. CI checks local Markdown links and generated CLI reference freshness; no Sphinx/Read the Docs deployment is required. Git history retains the former RST documentation. + +No new version DOI or archive has been assigned by this feature work. Publish and archive a validated release before claiming a corresponding version DOI in a manuscript. Use [maintainer release instructions](releasing.md) for package/container publication. diff --git a/docs/requirements.txt b/docs/requirements.txt deleted file mode 100644 index 4fedba9..0000000 --- a/docs/requirements.txt +++ /dev/null @@ -1 +0,0 @@ -sphinx_rtd_theme==2.0.0 diff --git a/docs/results-schema.md b/docs/results-schema.md new file mode 100644 index 0000000..090cdb7 --- /dev/null +++ b/docs/results-schema.md @@ -0,0 +1,137 @@ +# Results schema and EDA portal + +[User guide](../README.md#reports-and-the-eda-portal) · [CLI reference](cli-reference.md) + +For step-by-step browsing and SSH setup, start with the [explorer tutorial](reports-tutorial.md). This page defines the exact table meanings and relationships. + +## What the report does + +`metapathways report -o OUTPUT` reads existing outputs and writes `OUTPUT/reports/`. It never launches annotation, read mapping, MAG splitting or Pathway Tools. Successful analysis commands also refresh the report. The report follows ASPIRE/BASINS' accounting-and-navigation approach: sample inventory, available products, import limitations, source records and links to execution diagnostics. It adds no biological interpretation or new plots. + +The HTML report is readable directly from disk. The EDA portal's queries and CSV exports require `metapathways report -o OUTPUT --serve --no-rebuild`. A loopback-only server reads `results.sqlite`; the browser receives one page at a time. HTML, CSS and JavaScript are packaged with MP. There are no CDN dependencies or third-party requests. + +The schema version is recorded in `schema.json`, together with generation time, source root, table/view columns, row counts, primary keys and foreign keys. SQLite is also usable from Python, R or the `sqlite3` CLI. All paths in the inventory and source tables are relative to the selected output root. + +## Relationships + +```mermaid +erDiagram + samples ||--o{ contigs : contains + contigs ||--o{ orfs : contains + orfs ||--o{ annotations : has + annotations ||--o{ annotation_terms : describes + samples ||--o{ entities : contains + entities ||--o{ contig_mags : assigns + contigs ||--o{ contig_mags : belongs + entities ||--o{ entity_orfs : supplies + orfs ||--o{ entity_orfs : supplies + entities ||--o{ pathways : infers + pathways ||--o{ pathway_orfs : supports + orfs ||--o{ pathway_orfs : participates + orfs ||--o{ orf_groups : groups +``` + +Always scope contig and ORF identifiers by `sample_id`. Scope a pathway by `(sample_id, entity_id, pathway_id)`: the same pathway in a community and a MAG is two inference records. `community` is the reserved community entity identifier. MAG identifiers come from output directories or the preserved contig map. As in MAGSplitter, periods in original MAG names become underscores in entity IDs; `contig_mags.original_mag_id` retains the supplied identifier. Sources use database-local integer `source_id` values; these IDs may change on rebuild and are not global identifiers. + +## Tables and their row units + +| Table | One row represents | Main keys and provenance | +| --- | --- | --- | +| `samples` | A sample output directory | `sample_id`; output path relative to the report root | +| `contigs` | A retained contig | `(sample_id, contig_id)`; original ID and length from `preprocessed/*.mapping.txt` | +| `orfs` | An ORF | `(sample_id, orf_id)`; contig, coordinates, strand, primary target/product and taxonomy from `*.functional_and_taxonomic_table.txt` | +| `annotations` | One reference annotation record | `annotation_id`; sample/ORF, database, accession, product, score, original EC/reaction strings, `source_id` | +| `annotation_terms` | One term on one annotation | `(annotation_id, term_type, term)`; pipe-separated EC/reaction values are split without creating EC×reaction combinations | +| `entities` | A community, MAG or unbinned entity | `(sample_id, entity_id)`; type, pathway output availability, latest recorded Pathway Tools task status | +| `contig_mags` | An explicit contig-to-MAG assignment | `(sample_id, contig_id, entity_id)`; source is preserved `magsplitter/contig_to_mag.tsv` | +| `entity_orfs` | A gene explicitly present in a MAG Pathway Tools input | `(sample_id, entity_id, orf_id)` from `magsplitter/results/*/0.pf`; **not full MAG gene membership** | +| `orf_groups` | A representative/member association | `(sample_id, representative_orf_id, member_orf_id)` from `ptools/orf_map.txt`; includes the representative itself | +| `pathways` | An entity-specific pathway inference | Composite pathway key; common name, reported score/reaction counts/ORF count and source | +| `pathway_orfs` | An explicitly reported pathway/ORF association | Composite pathway key plus `orf_id`; duplicates in an ORF list are collapsed | +| `abundance` | One original measurement for one feature | `(sample_id, feature_type, feature_id, measurement)`; numeric value and source | +| `execution` | A retained task invocation | Run identifier, command, label, outcome, duration, error and summary file; contains reruns/cache hits too | +| `sources` | A parsed source file | Relative path, size, SHA-256 and role | +| `files` | An inventoried output file | Relative path, size and modification time; large raw files are not all checksummed | +| `issues` | An import limitation or discrepancy | Sample, source and explanation | + +The primary annotations and the EC/reaction mapping have different meanings. The primary table contains MP's selected target/product and reported taxonomy. `annotations` retains individual database records. It uses `*.EC_RXN_map.tsv` when available, otherwise `*.1.txt`; importing both would duplicate hits. Blank repeated ORF cells in the compact `.1.txt` format are forward-filled within that file. + +ORF lengths and coordinates are copied in their source units/conventions; the importer does not recompute them. Taxonomy strings remain as reported, rather than being converted into assumed ranks. Reference scores are not relabeled as universal confidence probabilities. + +Abundance retains the original measurement names, including read-file labels in CoverM's contig table. ORF `Count`, `RPKM` and `TPM` are separate measurements. The `(feature_type, sample_id, feature_id)` relation identifies a contig or ORF; SQLite cannot express this polymorphic relation as one ordinary foreign key. Abundance values are not recalculated, and historical incorrect mate mapping is not repaired by importing it. + +## Ready-made explorer views + +| Portal table / SQL view | Grain and joins | +| --- | --- | +| ORFs and taxonomy / `orf_explorer` | One ORF with original contig ID and length | +| Functional annotations / `annotation_explorer` | One reference annotation with contig and taxonomy | +| Pathways / `pathway_explorer` | One pathway inference with entity type and count of distinct explicit ORF links | +| Pathway genes / `pathway_gene_explorer` | One pathway/ORF link with primary product, taxonomy and contig | +| MAG ORFs / `mag_orf_explorer` | All reported ORFs on explicitly mapped contigs; requires the full contig map | +| MAG input genes / `mag_gene_explorer` | Only the selected genes in MAG Pathway Tools input files | + +These views do not join all annotation hits onto all pathway memberships. Such a join creates a many-to-many expansion and makes naive counts or abundance sums wrong. The browser's related filters use `EXISTS` to select matching ORFs/annotations without multiplying rows. EC, reaction and reference-database restrictions in one related filter must match the same annotation record; pathway and entity restrictions must match the same pathway association. + +An entity-only related filter selects the explicit MAG Pathway Tools input genes. For complete MAG membership, open **MAG ORFs** and filter `entity_id`; then follow the ORF's annotation/pathway links. This distinction is deliberate when old results lack the full contig map. + +## Subsetting examples + +### Taxon and function + +1. Choose **Functional annotations**. +2. Add `taxonomy contains Bacteria` and `product contains kinase`. +3. Add `reference_db equals swissprot` if only that database is desired. +4. Select columns, click **Apply filters**, then export CSV. + +### Genes supporting a pathway in one MAG + +1. Choose **Pathways** and filter `sample_id`, `entity_id` and `pathway_id` by exact equality. +2. Click **Pathway genes** on that row. All three identifiers carry into the next query. +3. Filter further by taxonomy or product, and export the matching associations. +4. Use **ORF annotations** to see the gene's individual reference hits and EC/reaction terms. + +### All reported ORFs assigned to a MAG + +Choose **MAG ORFs** and set exact sample and entity filters. This uses the contig membership map, including ORFs absent from the selected Pathway Tools input. If the map was not preserved in old outputs, the report leaves this table empty rather than inferring membership from pathway genes. You can supply the original headerless two-column map as `SAMPLE/magsplitter/contig_to_mag.tsv` and rebuild, without rerunning biological analyses. + +### SQL with explicit joins + +```python +import sqlite3 +from pathlib import Path + +uri = Path('results/reports/results.sqlite').resolve().as_uri() + '?mode=ro' +with sqlite3.connect(uri, uri=True) as db: + rows = db.execute(''' + SELECT g.sample_id, g.entity_id, g.pathway_id, + g.orf_id, o.contig_id, o.taxonomy + FROM pathway_orfs AS g + JOIN orfs AS o USING (sample_id, orf_id) + WHERE g.sample_id = ? AND g.entity_id = ? AND g.pathway_id = ? + ''', ('sample', 'MAG_001', 'PWY-6167')).fetchall() +``` + +To count genes use `COUNT(DISTINCT orf_id)` **within a sample**, or distinct `(sample_id, orf_id)` pairs across samples. A gene participating in several pathways remains one gene. Pathway-associated ORFs are not automatically expanded through `orf_groups`: expanding a representative across MAG boundaries without checking membership would invent associations. + +## Missing, partial and historical outputs + +- Missing source tables produce import notes and empty/partially populated views. Referenced ORFs absent from the primary table are retained with `annotation_present=0` and null unknown fields. +- `pathway_status=available` means a pathway TSV exists, including a valid empty table. `unavailable` means no recognized pathway TSV was found. `last_task_status` records the latest retained Pathway Tools task outcome when known; an old output file can coexist with a failed latest attempt. +- Failed MAG inference is optional in MP, but not converted into a confident biological absence. Historical outputs without Nextflow summaries have unknown task status. +- The reported pathway ORF count is preserved separately from the count of unique parsed links. Disagreement is recorded in `issues`. +- Contig assignments missing from the retained contig map are counted in import notes; QC can remove original contigs. +- Malformed recognized tables or duplicate primary keys abort a rebuild. The prior database is retained. Input files are never edited by reporting. +- Reports are snapshots. `--no-rebuild` deliberately shows the old snapshot even if files have changed since generation. Rebuild when you want updated data. + +## Outputs that stay as source files + +The file inventory links RNA tables, FASTA/GFF/GenBank files, alignment results, run statistics, Pathway Tools flat files/archives and redundant annotation/pathway exports. Their arbitrary formats are not silently normalized into the biological core schema. The canonical pathway associations come from `*_pwy.tsv`; the denormalized `*_pwy2orf.tsv` remains accessible as its original file. + +The inventory omits hidden runtime state, report products, symlinked files/directories, and standard work/cache directories. The source importer rejects resolved paths outside the selected output tree. Report generation parses result tables and hashes its indexed source files; it does not read large sequence/aligner files merely to checksum every byte. + +## Exports and local service + +CSV export streams every matching row with the selected columns, independent of the visible page. Null values are blank. Text that would look like a spreadsheet formula is prefixed with an apostrophe; original values remain unchanged in SQLite. A query-definition JSON records filters, columns, ordering, schema version and report timestamp. The URL hash also records the query and is bookmarkable while the corresponding report snapshot remains available. + +The server binds only to `127.0.0.1`, uses a random URL prefix, checks Host/Origin, opens SQLite read-only and accepts only declared views/columns/operators. It does not execute arbitrary submitted SQL. Source-file links are restricted to the report tree and inventoried output paths. Do not expose it as a public web service. For a remote workstation, copy the results or use your site's approved SSH forwarding of a chosen loopback port. diff --git a/docs/reviewer-test.md b/docs/reviewer-test.md new file mode 100644 index 0000000..96ed6d0 --- /dev/null +++ b/docs/reviewer-test.md @@ -0,0 +1,103 @@ +# Reviewer walkthrough: three tiny CAMI samples + +[Home](../README.md) · Previous: [getting started](getting-started.md) · Next: [your inputs](inputs.md) + +This walkthrough uses ordinary MP commands and three distinct CAMI II samples included in the checkout. No Pathway Tools license, installer or container is needed for the default commands. They run annotation, paired-read mapping and abundance, genome splitting, and the report/explorer. Pathway inference is explicitly skipped; licensed users can enable it in the optional section below. + +The input bundle is about **2.4 MiB**, separate from software and reference-database downloads. Each sample contains three 50 kb assembly regions assigned to three CAMI source genomes: + +| Sample | Assembly bases | Read pairs | Genome bins | Manifest | +| --- | ---: | ---: | ---: | --- | +| Urogenital_22 | 150,000 | 3,000 | 3 | `single.tsv` | +| Gastrointestinal_5 | 150,000 | 2,326 | 3 | `pair.tsv` | +| Skin_28 | 150,000 | 3,000 | 3 | `pair.tsv` | + +These are real subsets of simulated CAMI reads and gold-standard assemblies, not duplicated samples. Bins contain small genome fragments, not complete genomes or recovered MAGs. We selected abundant contigs and matching reads to exercise the interfaces. Do not use these coverage-biased subsets to assess biological accuracy, abundance, genome completeness, pathway recovery or publication performance. + +## 1. Install MP and prepare the small reference database + +Follow [getting started](getting-started.md), including environment activation. The examples assume your checkout is `~/src/MetaPathways`; substitute your actual path if different. + +```bash +mkdir -p ~/mp-reviewer +cd ~/mp-reviewer +metapathways build_db --test +ln -s ~/src/MetaPathways/metapathways/regtests/test_db MPDB +cp -r ~/src/MetaPathways/metapathways/regtests/cami_reviewer cami-reviewer +``` + +Run the link and copy commands once in a new work directory. `build_db --test` formats the tiny bundled SwissProt/SILVA fixtures and downloads enzyme/taxonomy support records. It needs internet access and a writable installation. This is not an offline test, and the input bundle size is not the total installation size. + +The small reference fixture is intentionally incomplete and is largely E. coli oriented. CAMI annotations can therefore be sparse, and RNA tables can be empty. To test richer annotations with your existing production MPDB, replace `-d MPDB` with its path, replace `--annotation_dbs swissprot_test` with `--annotation_dbs swissprot`, and omit the `--rRNA_refdbs` line to use the standard SILVA references. The small input samples remain the same. See [database commands](commands.md). + +## 2. Run the single-sample workflow + +```bash +cd ~/mp-reviewer +metapathways analysis_wf \ + --manifest cami-reviewer/single.tsv \ + -o single -d MPDB \ + --annotation_dbs swissprot_test \ + --rRNA_refdbs SILVA_SSU_test SILVA_LSU_test \ + --skip_ptools \ + --threads 4 --max_cpus 8 --memory '4 GB' --max_memory '16 GB' +``` + +This uses `Urogenital_22`. These explicit resource settings suit a small interface test; use resources actually available on your machine. They are not recommended memory estimates for full metagenomes. Append `--dryrun` first if you want to inspect the plan, then repeat without that flag to execute it. Do not add `--test` to `analysis_wf`: that mode belongs to the separate bundled installation check and selects its own inputs. + +## 3. Run two distinct samples together + +```bash +metapathways analysis_wf \ + --manifest cami-reviewer/pair.tsv \ + -o pair -d MPDB \ + --annotation_dbs swissprot_test \ + --rRNA_refdbs SILVA_SSU_test SILVA_LSU_test \ + --skip_ptools \ + --threads 4 --max_cpus 8 --memory '4 GB' --max_memory '16 GB' +``` + +This uses `Gastrointestinal_5` and `Skin_28`. Ready tasks can overlap within the CPU and memory budgets; dependencies still determine when each task may start. Repeat the same command once to check reuse: successful unchanged tasks should report `ALREADY_COMPUTED`. That repeat is not a fresh runtime benchmark. + +`all.tsv` selects all three samples. The manifests use paths relative to the manifest, so you can move the entire `cami-reviewer` folder without editing them. The `sample_id` column controls output names independently of assembly filenames. + +To exercise automatic discovery on all three samples, replace `--manifest cami-reviewer/pair.tsv` with `-i cami-reviewer/inputs`, and choose a new output such as `-o all-auto`. The discovery root contains only `assemblies/`, `reads/`, and `mag_maps/`. Manifests and provenance live outside it so strict discovery does not reject extra files. + +## 4. Check outputs and explore tables + +| Check | Single-sample location | +| --- | --- | +| Resolved sample ID and paired read paths | `single/inputs.resolved.tsv` | +| Functional/taxonomic annotation tables | `single/Urogenital_22/results/annotation_table/` | +| Contig and ORF abundance | `single/Urogenital_22/results/rpkm/` | +| Genome assignments and split inputs | `single/Urogenital_22/magsplitter/` | +| Task outcomes and resource records | `single/logs/analysis_wf/RUN_ID/` | +| Report and explorer | `single/reports/` | + +`RUN_ID` means the generated invocation directory, not a literal directory name. Inspect `summary.json` and the linked logs. Required tasks must succeed; a report existing alone does not prove success. Both paired-read paths must be distinct, all three genome bins should have split inputs, and the pair report should contain both sample IDs. Pathway tables are absent by design with `--skip_ptools`. + +```bash +metapathways report -o single --serve --no-rebuild +``` + +In `EDA_portal.html`, select a sample, search an annotation, follow an ORF to its related records, and export a filtered CSV. Check that sample/entity identifiers remain in the export. Stop the server with Ctrl-C and use `-o pair` to inspect the two-sample output. Follow [the report tutorial](reports-tutorial.md) for remote SSH access and table relationships. + +## 5. Optional: include licensed Pathway Tools + +Follow [the license and installer guide](pathway-tools.md#get-the-installer). Build and register your own image: + +```bash +metapathways build_pt \ + -i ~/Downloads/pathway-tools-29.5-linux-64-tier1-install \ + -o ~/mp-reviewer/containers +``` + +Repeat either workflow command with a new output directory, remove `--skip_ptools`, and add `--taxprune --taxonomic_scope all`. MP uses the registered image. This adds community and per-bin PGDB inference/export. It does not require MetaCyc as a sequence annotation database: inference uses the licensed MetaCyc inside the image. See the Pathway Tools guide if you also want to build MetaCyc annotation references. + +Tiny genome fragments and sparse annotation references may yield few or no pathways. Check task outcomes and exports rather than requiring a universal pathway count. A full-reference test is more informative biologically. + +## Provenance and validation + +The bundle's [README](../metapathways/regtests/cami_reviewer/README.md), `provenance.json`, and `validation.json` describe selection, original sample paths, retained contig regions, matching read counts, hashes, and checks performed. The preparation script is [scripts/prepare_cami_reviewer.py](../scripts/prepare_cami_reviewer.py). No Pathway Tools software or MetaCyc sequence/database material is included. + +Input validation covers all manifests, automatic discovery, intact mate pairing, complete contig-to-genome maps and gene prediction on every retained contig. It does not substitute for the reviewer executing the full workflow above. See [benchmarking](benchmarking.md) before collecting publication statistics from the complete CAMI samples. diff --git a/docs/src/conf.py b/docs/src/conf.py deleted file mode 100644 index a4b49de..0000000 --- a/docs/src/conf.py +++ /dev/null @@ -1,59 +0,0 @@ -# Configuration file for the Sphinx documentation builder. -# -# This file only contains a selection of the most common options. For a full -# list see the documentation: -# https://www.sphinx-doc.org/en/master/usage/configuration.html - -# -- Path setup -------------------------------------------------------------- - -# If extensions (or modules to document with autodoc) are in another directory, -# add these directories to sys.path here. If the directory is relative to the -# documentation root, use os.path.abspath to make it absolute, like shown here. -# -#import os -#import sys -#sys.path.insert(0, os.path.abspath('..')) - - -# -- Project information ----------------------------------------------------- - -project = 'MetaPathways' -copyright = '2024, BCB2 Developers' -author = 'BCB2' - - -# -- General configuration --------------------------------------------------- - -# Add any Sphinx extension module names here, as strings. They can be -# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom -# ones. -extensions = [ -] - -# Add any paths that contain templates here, relative to this directory. -templates_path = ['_templates'] - -# List of patterns, relative to source directory, that match files and -# directories to ignore when looking for source files. -# This pattern also affects html_static_path and html_extra_path. -exclude_patterns = ['_*', 'Thumbs.db', '.DS_Store'] - - -# -- Options for HTML output ------------------------------------------------- - -# The theme to use for HTML and HTML Help pages. See the documentation for -# a list of builtin themes. -# -html_theme = 'sphinx_rtd_theme' -# source_suffix = ['.rst', '.md'] -source_suffix = '.rst' - -# The master toctree document. -master_doc = 'index' - -# Add any paths that contain custom static files (such as style sheets) here, -# relative to this directory. They are copied after the builtin static files, -# so a file named "default.css" will overwrite the builtin "default.css". -html_static_path = ['static'] - -numfig = True diff --git a/docs/src/index.rst b/docs/src/index.rst deleted file mode 100644 index 92e6ec8..0000000 --- a/docs/src/index.rst +++ /dev/null @@ -1,31 +0,0 @@ -.. MetaPathways documentation master file, created by - sphinx-quickstart on Wed Sep 23 13:09:29 2020. - You can adapt this file completely to your liking, but it should at least - contain the root `toctree` directive. - - -MetaPathways -============ - -.. toctree:: - :maxdepth: 2 - :caption: Documentation - - overview - quick_start - install - usage - reproducibility - -.. Indices and tables -.. ================== - -.. * :ref:`genindex` -.. * :ref:`modindex` -.. * :ref:`search` - -.. Contact -.. ======= - -.. :ref:`contact` - diff --git a/docs/src/install.rst b/docs/src/install.rst deleted file mode 100644 index 9e7cc9b..0000000 --- a/docs/src/install.rst +++ /dev/null @@ -1,34 +0,0 @@ -Installation -************ - -Metapathways can be installed with conda or obtained as a container. -The fastest install is via Mamba (recommended) or by pulling down the container. - -.. note:: - - Metapathways has been built and tested on Linux OS. - Lightly tested on Mac OS. - And not currently supported on native Windows. - - -Mamba (recommended) -------------------- - -.. code-block:: bash - - mamba create -n metapathways_env -c hallamlab -c bioconda -c conda-forge metapathways - -Conda ------ - -.. code-block:: bash - - conda create -n metapathways_env -c hallamlab -c bioconda -c conda-forge metapathways - -Docker ---------- - -.. code-block:: bash - - docker pull quay.io/hallamlab/metapathways - diff --git a/docs/src/overview.rst b/docs/src/overview.rst deleted file mode 100644 index b7c8d94..0000000 --- a/docs/src/overview.rst +++ /dev/null @@ -1,108 +0,0 @@ -Overview -******** - -MetaPathways [1]_ is a meta'omic analysis pipeline for the annotation and analysis for environmental sequence information. -MetaPathways include metagenomic or metatranscriptomic sequence data in one of several file formats -(nucleotide FASTA or amino-acid FASTA). The pipeline consists of five operational stages including - -Pipeline -~~~~~~~~ - -.. figure:: static/glyph.png - :align: center - :alt: alternate text - :figclass: align-center - -MetaPathways is composed of four general stages, encompassing a number of analytical or data handling steps **(Figure 1)**: - -.. |nbsp| unicode:: 0xA0 - :trim: - -|nbsp| - -#. **Quality Control**: - Basic quality control (QC) is performed with includes filtering out sequences below a set - length threshold (default 180bp). - -#. **Feature Prediction**: - Several sequence features can be predicted on the QC'ed contigs. Open-reading frames - (ORFs) are predicted by default and (optionally) ribosomal subunits (rRNAs) and - transfer RNAs (tRNAs) can be predicted. To improve the runtime and efficiency, Prodigal - [2]_ is run through a parallel version (pProdigal) [3]_ and - tRNAscan-SE [4]_ is run using a wrapper script that allows for more - efficient multi-threading. BARRNAP [5]_ is used for the prediction of rRNAs - including: 16S, 23S, and 5S. MetaPathways provides an overlap-aware identification so - that users can make informed decisions about features when they overlap each other. - Additionally, users can define the minimum length of ORFs to keep for downstream analysis. - -#. **Functional Annotation**: - Using a seed-and-extend homology search algorithm, either BLAST [6]_ or FAST [7]_, - users can conduct searches against both functional and taxonomic (optional) databases. - Currently supported databases include: Uniprot SwissProt [8]_, Uniprot UniRef90 - [9]_, MetaCyc [10]_, CAZymes [11]_ for functional annotations, and SILVA [12]_ for - taxonomic. However, users can create custom databases for any preferred databases. - Optionally, reads can be used to calculate abundance information at both the contig - and ORF-level. - -#. **Pathway Inference**: - MetaPathways then predicts `MetaCyc pathways `_ using the - `Pathway Tools software `_ and its pathway prediction - algorithm PathoLogic [13]_, resulting in the creation of a community-level environmental - Pathway/Genome Database (ePGDB), an integrative data structure of sequences, genes, pathways, - and literature annotations for integrative interpretation. Optionally, if metagenome-assembled - genomes (MAGs) are available for the metagenome, these MAGs can be used to create - population-level ePGDBs. MetaCyc pathways are exported in a tabular format for - downstream analysis. - -Bibliography -~~~~~~~~~~~~ - -Please see the following `Zotero Library `_ for a bibliography. - -.. [1] K. M. Konwar, N. W. Hanson, A. P. Pagé, S. J. Hallam, MetaPathways: a modular - pipeline for constructing pathway/genome databases from environmental sequence information. - BMC Bioinformatics 14, 202 (2013) http://www.biomedcentral.com/1471-2105/14/202 - -.. [2] D. Hyatt, P. F. LoCascio, L. J. Hauser, and E. C. Uberbacher. Gene and - translation initiation site prediction in metagenomic sequences. Bioinformatics, 28(17):2223–2230, 2012. - -.. [3] S. Jaenicke. PProdigal: Parallelized gene prediction based on Prodigal. - https://github.com/sjaenick/pprodigal, Dec. 2023. original-date: 2019-08-10T10:51:03Z. - -.. [4] P. P. Chan and T. M. Lowe. tRNAscan-SE: Searching for tRNA genes - in genomic sequences. Methods in molecular biology (Clifton, N.J.), 1962:1–14, 2019. - -.. [5] T. Seemann. Barrnap: BAsic Rapid Ribosomal RNA Predictor. - https://github.com/tseemann/barrnap, Dec. 2023. original-date: 2013-08-03T08:25:45Z. - -.. [6] Z. Zhang, W. Miller, and D. J. Lipman. Gapped BLAST and PSIBLAST: a new - generation of protein database search programs. Nucleic Acids Research, 25(0):17, 1997. - -.. [7] D. Kim, A. S. Hahn, N. W. Hanson, K. M. Konwar, and S. J. Hallam. - FAST: Fast annotation with synchronized threads. In 2016 IEEE Conference on Computational - Intelligence in Bioinformatics and Computational Biology (CIBCB), pages 1–8, 2016. - -.. [8] Boutet, Emmanuel, Damien Lieberherr, Michael Tognolli, Michel Schneider, - and Amos Bairoch. "UniProtKB/Swiss-Prot: the manually annotated section of the UniProt - KnowledgeBase." In Plant bioinformatics: methods and protocols, pp. 89-112. Totowa, NJ: - Humana Press, 2007. - -.. [9] Suzek, B.E., Wang, Y., Huang, H., McGarvey, P.B., Wu, C.H. and UniProt Consortium, - 2015. UniRef clusters: a comprehensive and scalable alternative for improving sequence - similarity searches. Bioinformatics, 31(6), pp.926-932. - -.. [10] Caspi, R., Altman, T., Billington, R., Dreher, K., Foerster, H., Fulcher, C.A., - Holland, T.A., Keseler, I.M., Kothari, A., Kubo, A. and Krummenacker, M., 2014. The MetaCyc - database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome - Databases. Nucleic acids research, 42(D1), pp.D459-D471. - -.. [11] Garron, M.L. and Henrissat, B., 2019. The continuing expansion of CAZymes and their - families. Current opinion in chemical biology, 53, pp.82-87. - -.. [12] Pruesse, E., Quast, C., Knittel, K., Fuchs, B.M., Ludwig, W., Peplies, J. and Glöckner, - F.O., 2007. SILVA: a comprehensive online resource for quality checked and aligned ribosomal - RNA sequence data compatible with ARB. Nucleic acids research, 35(21), pp.7188-7196. - -.. [13] P. D. Karp, M. Latendresse, R. Caspi, The pathway tools pathway prediction algorithm. - Stand Genomic Sci 5, 424–429 (2011). - diff --git a/docs/src/quick_start.rst b/docs/src/quick_start.rst deleted file mode 100644 index 828234b..0000000 --- a/docs/src/quick_start.rst +++ /dev/null @@ -1,58 +0,0 @@ -Quick Start (TLDR;) -******************* -Are you a reviewer or just need to test this out quickly? -The commands below will allow you to install and test MP-3.5 quickly and efficiently. -Sorry you still need Conda/Mamba. - -.. note:: - - If you run the last two commands, make sure to replace the ${variables} with real values. - -Try it with Mamba (recommended) -=============================== - -.. code-block:: bash - - # install metapathways with Mamba - mamba create -n metapathways_env -c hallamlab -c bioconda -c conda-forge metapathways - mamba activate metapathways_env - - # test the install - metapathways build_db --test - metapathways run --test # results in `${CWD}/test` - - ### Try your own data! ### - - # build the minimal reference DB - metapathways build_db -d ${path/to/MPDB} --func swissprot -a fast - - # run minimal DB on your personal data - metapathways run -i ${your_metagenome.fa} -o ${path/to/output_dir} -d ${path/to/MPDB} - -.. note:: - - The build_db test does not create a DB that is to be used for downstream DB builds. - For the full reference build the use is to provide a location with acceptable storage - capacity and accessibility. - -Try it with Docker -===================== - -.. code-block:: bash - - # pull down with docker - docker pull quay.io/hallamlab/metapathways - docker run -it quay.io/hallamlab/metapathways /bin/bash - - # test the install (within docker) - metapathways build_db --test - metapathways run --test # results in `${CWD}/test` - - ### Try your own data! ### - - # build the minimal reference DB - metapathways build_db -d ${path/to/MPDB} --func swissprot -a fast - - # run minimal DB on your personal data - metapathways run -i ${your_metagenome.fa} -o ${path/to/output_dir} -d ${path/to/MPDB} - diff --git a/docs/src/reproducibility.rst b/docs/src/reproducibility.rst deleted file mode 100644 index ebf257d..0000000 --- a/docs/src/reproducibility.rst +++ /dev/null @@ -1,133 +0,0 @@ -Reproducibility -*************** - -Source and license -================== - -The canonical v3.5 source is `hallamlab/MetaPathways -`_. MetaPathways is distributed under -the MIT license; bundled third-party source retains its own license notices. -The historical GitHub codebase is separate from v3.5. - -The Conda package and Quay container are distributed separately. A GitHub tag -alone does not update either distribution. Record the package version or -container digest used for an analysis, alongside the Git commit when installing -from source. - -Installation test -================= - -In a writable environment with the dependencies from ``docker/conda_base.yml`` -and this checkout installed, run: - -.. code-block:: bash - - metapathways build_db --test - metapathways run --test - -The package includes the compressed K12 nucleotide FASTA, paired FASTQ reads, -and small SwissProt/SILVA sequence fixtures in ``metapathways/regtests``. -The first command formats these fixtures and downloads the current ExPASy enzyme -records and NCBI taxonomy. It needs internet access and writes into the installed -package's test database directory. It is not an offline or fully pinned benchmark. -The second command writes results to ``./test/``. Inspect command output, -``metapathways_steps_log.txt`` and ``errors_warnings_log.txt`` in the sample output -directory; do not rely on the process exit code alone. - -Keep generated databases and outputs outside version control. Preserve their -checksums and download dates when recording an analysis. The raw sequence fixtures -are versioned with the source; they must not be removed as generated data. - -Supported inputs and outputs -============================ - -The current ``run`` CLI accepts nucleotide FASTA (``--input_format fasta``) or -amino-acid FASTA (``--input_format fasta-amino``). Compressed FASTA is used by the -included test. FASTQ reads supplied with ``-1``/``-2`` or ``--interleaved`` enable -abundance calculations. GFF and GenBank are outputs, not supported primary input -formats of this CLI. - -Outputs under each sample directory include: - -* ``preprocessed/`` and ``orf_prediction/``: processed nucleotide/protein sequences - and predicted features. -* ``genbank/``: annotated GFF and GenBank files when their stages are enabled. -* ``results/annotation_table/``: tab-separated functional/taxonomic annotations. -* ``results/rpkm/``: abundance/count tables when read mapping is enabled. -* ``results/rRNA/`` and ``results/tRNA/``: RNA annotations and statistics. -* ``run_statistics/`` and the sample log files: processing counts and step status. -* ``ptools/``: Pathway Tools input files. Creating an ePGDB is a separate - ``metapathways ptools`` command requiring a licensed Pathway Tools installation - and the optional PGDB dependencies. - -Dependency versions -=================== - -``docker/conda_base.yml`` specifies the runtime environment; optional development, -MAG splitting and PGDB dependencies are listed in ``docker/conda_dev.yml`` and -``conda_recipe/meta_template.yaml``. These environment specifications are not -complete version locks. The migration validation environment on Linux x86-64 used: - -.. list-table:: Validation environment - :header-rows: 1 - - * - Dependency - - Version - * - Python - - 3.10.19 - * - Snakemake - - 7.32.4 - * - Prodigal / PProdigal - - 2.6.3 / 1.0.1 - * - BLAST+ - - 2.17.0 - * - BWA / SAMtools - - 0.7.19 / 1.22.1 - * - CoverM - - 0.7.0 - * - tRNAscan-SE / Barrnap - - 2.0.12 / 0.9 - * - pandas / pybedtools / pysam / pyfastx - - 2.3.3 / 0.12.0 / 0.23.3 / 2.2.0 - -FAST and metacount executables are included in the package. Their native source, -Makefiles, and relevant third-party tests are retained under ``extensions/``. -The bundled executables target Linux; native Windows is not supported. Record an -explicit environment export and checksums of reference files for reproducible -analyses. - -Manuscript benchmark provenance -=============================== - -The `v1 preprint `_, section 3.1, -reports 15 CAMI2 Human Microbiome metagenomes and 622 MAGs across five body sites. -It specifies SwissProt release 2023_05, MetaCyc 27.1, MetaBAT2 2.15, and Pathway -Tools 27.0, with 16 cores on Ubuntu 20.04.6. These historical reference/software -versions differ from the moving downloads used by the installation test. - -The `CAMI2 study `_ identifies the -human dataset at `PUBLISSO, DOI 10.4126/FRL01-006425518 -`_. This identifies the source collection; -it does not establish the exact input files used for the MetaPathways results. - -Before claiming reproduction of the manuscript benchmark, the authors still need -to provide the exact 15-sample input/assembly manifest with checksums, commands -for preparing the 622 MAGs and contig mappings, reference acquisition/version -records, the pipeline revision and environment, benchmark commands, and the -result tables underlying the reported metrics. These artifacts were not found in -the current source checkout. The bundled K12 example does not substitute for -this benchmark archive. - -No Zenodo DOI has been assigned by this migration. After the validated GitHub -release is published and archived through Zenodo, cite the actual version DOI -in the manuscript and data-availability statement. - -Automated checks -================ - -The GitHub Actions smoke workflow builds the source/wheel distributions, checks -installed CLI startup on Python 3.10, and builds documentation. The full -bioinformatics example above is a separate integration check requiring the -Conda dependencies and public database downloads. It is not run by the lightweight -smoke workflow. The old Python 3.6--3.8 CircleCI/tox configuration was retired -because it referenced a removed test suite and requirements file. diff --git a/docs/src/static/glyph.png b/docs/src/static/glyph.png deleted file mode 100644 index a8aab087d42fd1cc6e824e98842118f2662d510e..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 129109 zcmeEP1wfQZ`&UE(rBk{=K)MzQ=@4m@6r`JlrIs`(K{`Yvlu$}U1*Jg&2|-X13`$y& z1_`PEEbJ=A-T&^s)6?%e1NNPrcjkR(p6B=E%!H_`D&Xv;*t=uL4jd&#S*@fvw6V9?!OSnS^@*8}#~SM5%FHjz z%*SWqsv~UGQ;ClzCxs9cbh51$;J{~@PPF`M49${@hUS@tNUP17K zkB5tw52C+S-^9wo5!s*$)XT=+-h`P?UXY6iG<86i7u+KaJ{`4jbc2K6aEOqxkN_L_ zB<18}Z=qvhs%!)Ll^5g}=HeGZ+@h?gt#Xu^PX>Ipx3RMTzZ5LY?4XESWUOIO2T&r< z%PY*qgZK*ywM;BcU^d&DK)i#y1WF*=K2R01^{^JMCRSUe_R3Z^0uB!RFfR)M zB}XM^GZ#(!tvarrP8M5rte{XUd(a^tGrt@&j}&Ma@sD2yIcVU*(F8ou=3uIWap2_L zYQY9Mcn-%soSp6AR!T>tt>v_(6+QXjI$ySiYSRI(05fs2R)LyZfal;bha(?eSXgkY zQFG6&5?)>&@QR4Hw1S~JLiUR&(6aGDJ`pc?+RbWiHs%&C$eXu{T%k~VR~x6#3(cU8 zjuvLfsYJGD0)s(4KCfm8wMV`lvW^pY^UqpG6lj^5fRWoAnQhf{Y|LG)KfVU?`4H6= zEo`i;kzGRskzbganAusupl*)H{v4r>o09=()CAQGvZ{-{?w9CG&EP3+x}BfK@KF0P)a zAqUS6W*2-b?O|=>YN6$1Vuq;d0VoWVS-U#egDV7Unz%S^O}V8F9KrI^F0L@Bods&1 z0O3mm0I`>W+CyQRqswn@Vga!zM(gx>_Jf{TsuyS@ipJ^=ZZwEC4#V!aTvOAzS1W=0`S);vI;fAQuFQ1s

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z3Z7GBILQHf&nx@EKzt_Y+Nxz%iEXHN_JOLa2w=&b=vXv6wnNmmcQd|EA0G$z3=B}I zn~gC!^-9LbTpwRP5IE5(y~Mxx?Q|nwx&d5gZC;10#IZ%X+SXq^sZuHtnKh0u^uoGmRZNL?`l_<%!Yf4+<<(sZdt zr}SP3m-KGivJvu!{iIuSm(&(;$dtc%C*88H6SIvlFb6EaHky$g{o%L7zQb=8xn6T@ zz4k>1YYW*8fo`MIGOKjqyB%yq-!bB^+2hIDqZTs<29F~f08iHBN({;o?;fjCoqAXM z%Eo2l;^5#2;1GU0C(3;q%;PTL&app6J{f*+-hk{w>)Q#+--gOuaN(?;eY%6 e^5+p}SY_3BE}R$^fLk;MhL)P1YL&8G`_. -In order to use this feature, you must first install Pathway Tools which requires a license. -Pathway Tools is freely available for research purposes to academic, non-profit, and government institutions, -and is available for a fee to commercial institutions. For academic use, a license and the download can be -found here: `Download `_. - -.. note:: - - Although MetaPathways is installed in a conda/mamba environment, Pathway Tools is installed in the - $HOME directory by default and is globally available in the commandline. MetaPathways expects that - the Pathway Tools software has been installed using defaults and may not work as expected if installed - in a custom way. - -Minimal Usage: -~~~~~~~~~~~~~~ - -.. code-block:: bash - - metapathways ptools \ - -o ${path/to/output}/{metagenome_id} - -`ptools` parameters: -~~~~~~~~~~~~~~~~~~~~~~~ - -.. code-block:: bash - - usage: Metapathways ptools [options] - - Minimum REQUIRED Command: - Metapathways ptools -o output_dir - - options: - -h, --help show this help message and exit - -o OUTPUT_DIR, --output_dir OUTPUT_DIR - path where MP output was saved [REQUIRED] - --tag TAG Custom name for ePGDB [optional] - --container Flag only used in containerized env [special flag] - --taxprune Set taxonomic pruning in pathway tools to True - -.. note:: - The container option only functions if both MetaPathways and Pathway Tools are installed - in the same container. But due to licensing constraints this cannot be distributed and therefore - is only experimental at this point. - - *There will be more work on this in the near future* - - diff --git a/docs/workflow.md b/docs/workflow.md new file mode 100644 index 0000000..cecfdd6 --- /dev/null +++ b/docs/workflow.md @@ -0,0 +1,206 @@ +# Workflow and output guide + +[Start with the README](../README.md) · [Complete CLI flags](cli-reference.md) + +For guided usage, start with the [command cookbook](commands.md) or [Pathway Tools chapter](pathway-tools.md). This page describes the stage and output contracts. + +## Command boundaries + +| Command | Work performed | Requires | +| --- | --- | --- | +| `analysis_wf` | One DAG for multiple assemblies, per-sample reads/MAG maps, PGDBs and combined reports | [Layout or manifest](../README.md#analysis-wf-input-layout), MPDB, registered SIF | +| `build_db` | Download references, build FAST/BLAST indexes and supporting maps through Nextflow | Network, writable database directory, indexing tools | +| `run` | Assembly QC, prediction, search, annotation, optional mapping, Pathway Tools input preparation | Assembly and compatible MPDB; reads optional | +| `mag_split` | Reuse existing annotations to create MAG Pathway Tools inputs; preserve the original contig map | Completed community outputs, MAGSplitter, headerless two-column contig map | +| `build_pt` | Build, validate and register a private Pathway Tools SIF | Licensed installer, Apptainer, Nextflow, build prerequisites | +| `ptools` | Build/extract community and optional MAG PGDBs | Pathway Tools inputs, SIF/native installation, Camelot extraction dependency | +| `report` | Index existing outputs; optionally open a local search/export portal | Existing MP output; no biological tools needed for indexing | + +Nextflow schedules tasks; existing MP scripts still perform the biological calculations and write the established sample paths. Public database construction uses the new Nextflow planner. The historical Snakefiles and old `bin/metapathways-data-install.sh` helper remain legacy artifacts; use `metapathways build_db` for supported construction. `--snakemake` on that command accepts only explicitly supported compatibility options (`cores`, `jobs`, `dryrun`, `dry-run`, `forceall`, `keep-going`, `rerun-incomplete`, `printshellcmds`, `latency-wait`); unsupported options fail rather than being interpreted as arbitrary Nextflow settings. Prefer the named resource flags. + +## Annotation stages + +The pipeline follows sample dependencies while permitting independent database searches/parses to run concurrently. Each sample maintains its own context and final output paths. + +| Stage | Purpose | Representative output | +| --- | --- | --- | +| `PREPROCESS_INPUT` | Filter sequences; establish MP/original contig identifiers | `preprocessed/` | +| `ORF_PREDICTION` / `ORF_TO_AMINO` | Predict ORFs and derive sequences | `orf_prediction/` | +| `FILTER_AMINOS` | Apply amino-acid sequence filters | QCed protein sequences | +| `FUNC_SEARCH` | Search each selected functional database | `blast_results/` | +| `COMPUTE_REFSCORES` | Compute reference scores used by parsing | Refscore file | +| `PARSE_FUNC_SEARCH` | Apply search thresholds and parse database results | Parsed search tables | +| `SCAN_rRNA` | Barrnap prediction followed by reference search/summary | `results/rRNA/` | +| `SCAN_tRNA` | Predict tRNAs | `results/tRNA/` | +| `ANNOTATE_ORFS` | Assign functional annotations | Annotated GFF and annotation products | +| `CREATE_ANNOT_REPORTS` | Write primary functional/taxonomic and reference tables | `results/annotation_table/` | +| `GENBANK_FILE` | Export annotated sequence record | `genbank/*.gbk` | +| `PATHOLOGIC_INPUT` | Prepare selected Pathway Tools inputs and EC/reaction mappings | `ptools/`, `*.EC_RXN_map.tsv`, `*.ptinput.tsv` | +| `COMPUTE_TPM` | Map supplied reads and derive abundance/count tables | `results/rpkm/` | + +FASTA-amino inputs take the compatible protein-input path. Stage choices and thresholds are in [CLI reference](cli-reference.md); internal derived stages do not necessarily have independent public flags. MP preserves the existing `yes`, `skip`, `redo` controls. Skipping a producer does not manufacture the inputs needed by its consumers. + +QC defaults, ORF prediction parameters, alignment algorithm/mode, functional score/e-value/identity thresholds and rRNA database thresholds remain configurable through the CLI. Search flags must match the configured database indexes. The portal reports existing assignments; it does not change thresholding or infer taxonomic ranks from free-text lineage strings. + +## Output layout + +```text +OUTPUT/ +├── SAMPLE/ +│ ├── preprocessed/ # Contigs and original-name map +│ ├── orf_prediction/ # Predicted and filtered sequences +│ ├── blast_results/ # Search and parsed hits +│ ├── genbank/ # GFF/GenBank annotation +│ ├── ptools/ # Community Pathway Tools inputs +│ ├── magsplitter/ +│ │ ├── contig_to_mag.tsv # Preserved original two-column map +│ │ └── results/MAG_ID/ # MAG-specific Pathway Tools inputs +│ ├── results/ +│ │ ├── annotation_table/ +│ │ ├── rpkm/ +│ │ ├── rRNA/ +│ │ ├── tRNA/ +│ │ └── pgdb/ +│ │ ├── community/ +│ │ └── MAGs/MAG_ID/ +│ ├── run_statistics/ +│ ├── metapathways_steps_log.txt +│ └── errors_warnings_log.txt +├── reports/ # Run report, EDA portal and SQLite +├── logs/ # Durable CLI/Nextflow records +└── .metapathways/ # Receipts, locks and temporary work +``` + +Commands operating on one existing sample (`mag_split`, `ptools`) also store their logs below that sample directory. A report over the parent includes these execution summaries. Running the report directly on a sample creates `SAMPLE/reports/`; running it on the parent creates `OUTPUT/reports/`. + +## Dependency and cache behavior + +Resource requests belong to each task. pProdigal, barrnap, ptRNAscan, FAST/BLAST, and read mapping/counting use the requested thread count capped by the total CPU budget. Serial stages, including Pathway Tools and Python parsers, reserve one CPU. Nextflow can mix threaded and serial tasks within the CPU and memory budgets. Independent database contexts share a preceding-stage dependency, and later stages wait for all contexts in that group. A failing required task stops dependent work. Optional MAG PGDB failures remain recorded while other entities proceed. + +MP retains durable task receipts outside Nextflow work directories. Reuse compares command signatures and tracked file state (size and modification time, including tracked reference/index files). These are not full content hashes of all biological inputs. The report source manifest independently records SHA-256 for files it parses. Use external input/reference checksums for stronger provenance, and `redo` when changing tool implementations or environments that are not represented by command/file fingerprints. + +Some legacy stages rewrite earlier outputs, such as the final GenBank record. The final producer owns that file's cached fingerprint. Old abundance output is not adopted without rerunning the corrected read mapping. Database index receipts track all index shards, so a missing shard invalidates reuse. + +Temporary cleanup archives diagnostic files before removal. Explicit work/cache paths and interruptions are retained. Final results and logs are never considered disposable caches. Multiple controllers targeting the same command/output are blocked by a file lock; per-invocation resource budgets do not govern unrelated MP commands. + +## Report limitations and error recovery + +Report generation runs after successful workflow completion. It is disk-backed, single-controller postprocessing rather than a scheduled biological stage. Large multi-sample report builds still use headnode I/O/CPU; run standalone `report` where site policy permits metadata indexing. It does not alter biological outputs. For a failed workflow, generate a report explicitly over the partial output to inspect what exists. + +A report requires recognized sample directories. Headers and identifiers matter: the importer rejects ambiguous duplicate source tables and malformed records. Do not merge different samples by concatenating tables containing unscoped `C1-G1` identifiers. Report schema versioning and source records make supported mappings explicit. + +Missing source tables, unannotated placeholders and expected optional MAG failures are visible instead of silently becoming zeros. See [results schema](results-schema.md) for exact semantics and [reproducibility](reproducibility.md) for benchmark limitations. + +For complete multi-sample execution, see [automatic input matching](../README.md#analysis-wf-input-layout) and the [custom manifest](../README.md#custom-analysis-manifest). `analysis_wf` assigns independent per-sample dependencies, saves the resolved input manifest, and builds the combined report after Nextflow completes so final statuses are included. + +### RNA identifiers and abundance integrity + +RNA annotations are emitted once per locus, including contigs with no CDS predictions. rRNA IDs include contig, subtype, coordinates and strand; distinct copies of the same rRNA must not share a gene ID. GFF-to-GTF conversion rejects duplicate IDs before mapping. ORF abundance uses featureCounts' `Length` column, requires a one-to-one gene-ID join with the GTF, and reports zero RPKM/TPM when all counts are zero. Tool output and errors are streamed into the task log, and failed sorting/conversion/counting/calculation commands stop the task immediately. + +Earlier versions could repeat RNA annotations at CDS parser buffer boundaries, omit RNA-only contigs and collapse separate rRNA loci into one ID. Existing derived annotations must be regenerated; updating MP alone does not repair saved results. After reinstalling this source revision, repeat the original `metapathways run` command with `--ANNOTATE_ORFS redo`, keeping the same input, database and resource settings. Changed annotation products invalidate dependent receipts; avoid `--force_redo` if you intend to retain successful ORF predictions and reference searches. Counting and RNA-derived results must be reviewed again. This does not rebuild previously generated PGDBs automatically under the standalone `run` command. + +### Concurrent FAST searches + +MP supplies FAST's `-X` option with a unique temporary directory for each search and reference-score invocation. FAST's default temporary names use a time-based seed and can collide when independent searches start in the same second. Older wrappers could therefore mix hits from different databases even when both processes returned success. A parser error showing Swiss-Prot `sp|...` targets in a MetaCyc result is one symptom; the databases themselves may be intact. + +The corrected planner invalidates previous functional-search and reference-score receipts and does not adopt untracked outputs for these stages. Repeat the original run command to regenerate the searches and affected downstream results; unrelated unchanged preprocessing can be reused. Search volumes stop on the first tool error, and merged results are published only after all volumes succeed. This change does not require rebuilding MPDB or the Pathway Tools SIF. + +### Pathway Tools failure diagnostics + +Before each community or MAG PGDB invocation, MP expands its compact `0.pf` annotations into per-contig PathoLogic inputs in private staging. Each genetic element has an annotation file and a `SEQ-FILE` containing its real preprocessed contig sequence. Feature IDs are preserved. The sample's `ptinput.tsv` supplies each feature's original contig, coordinates and strand; these restore MAG member coordinates that the splitter copied from a representative annotation. Missing sequences, unmapped/duplicate features or invalid source coordinates stop preparation before Pathway Tools starts. Unannotated contigs without PGDB features are omitted. The sequence counts and coordinate-restoration counts are retained in `diagnostics//input/sequence-input.json`. This enables Pathway Tools to derive protein sequences for its PGDB BLAST databases. The source annotation files and MAG split outputs are not modified. + +Older compact inputs described one sequence-less element named `0`, which caused `Chromosome 0: The chromosome has no sequence` and protein BLAST database creation warnings even with BLAST installed. Update MP, including its installed `pgdb_build_wf.py` script (`python -m pip install -e /path/to/MetaPathways`), then repeat `metapathways ptools -o /path/to/sample-output` to rebuild PGDBs with sequence-backed inputs. No annotation, read-mapping or SIF rebuild is needed. The planner invalidates previous PGDB receipts for this change and tracks the sequence inputs. + +Each container PGDB attempt saves its internal `pathologic.log`, other available logs, reports and `execution.json` under the entity output's `diagnostics/ATTEMPT/` directory. The execution record identifies the image, exit code and phase (`build`, `export`, or `archive`). On failure MP also prints the last 80 lines of the internal Pathologic log. These diagnostics survive temporary container-state cleanup. An optional MAG task failing does not by itself establish that the failure is biological or expected; inspect its diagnostics. Community PGDB failures remain fatal. + +Older container wrappers deleted the private Pathologic log along with temporary state, so the root cause of a historical exit 255 may be unavailable. Updating MP and repeating the same `ptools` invocation retains successful task receipts and retries unsuccessful entities, saving the internal error if it recurs. This logging fix works with an existing SIF. Newly built images also include NCBI BLAST+; the image recipe hash changes, so `build_pt` creates a separate image when rebuilt. + +`build_pt` also snapshots official SRI patches for the selected release and validates a synthetic BLAST database/search before registration. Analysis tasks keep patch downloads disabled. Rebuilding creates a distinct image; changing the selected image can invalidate prior PGDB receipts. A patched image is not evidence that a particular vendor inference bug is resolved. Add `-d /path/to/MPDB -a fast` to prepare matching MetaCyc sequences, indexes and tables after the image build; see [MetaCyc from Pathway Tools](../README.md#metacyc-from-pathway-tools). This optional preparation operates on the reference, not on sample annotations or sample PGDBs. + +Pathway Tools EC inputs are written as one `EC` line per identifier, including +when source annotations contain comma-, semicolon-, or pipe-separated lists. +PGDB staging applies the same normalization to existing PF inputs without +modifying the originals or rerunning annotation searches. The staging diagnostic +`sequence-input.json` records how many features had their EC entries normalized. +Provisional identifiers (for example `3.6.5.n1`) are preserved; Pathway Tools may +reject these, and its warnings remain in the saved logs. A successful Nextflow +wrapper for an optional MAG is not proof of a successful PGDB: consult MP's task +receipts and the per-entity `execution.json` status. + +PGDB staging separates the amino-acid label and anticodon in recognized MP tRNA +names (for example, `C1094.tRNA2-GluTTC` becomes `C1094.tRNA2-Glu-TTC` in the +`NAME` field). This prevents the label's last letter from merging with the +three-base anticodon during name parsing. Feature `ID` fields, sequences, +coordinates and source files remain unchanged, so annotation and abundance +joins retain their original identifiers. The original and staged names are +recorded in `sequence-input.json` under `normalized_trna_names`. Unknown +anticodons such as `NNN` and unrecognized name formats are left unchanged; +MP does not guess their biological assignments. Updating this preparation +invalidates existing PGDB receipts, but does not require rebuilding the SIF +or rerunning annotations. + +When the original `orf_prediction/.cds.gff` is available, PGDB staging +also preserves Prodigal's per-contig translation table through PathoLogic's +`CODON-TABLE` field. This avoids treating table-4 TGA codons as premature stops. +Older outputs without that metadata retain Pathway Tools' default genetic code; +no alternative code is guessed. The chosen codes are recorded in +`sequence-input.json`. This uses the input format documented in Pathway Tools' +installed `sample-genetic-elements.dat`; it does not patch Pathway Tools. + +Concurrent SIF PGDB tasks use Xvfb with a private filesystem display socket. +Apptainer's `--containall` isolates `/tmp` but does not isolate Linux abstract +X sockets. MP disables Xvfb's abstract listener (`-nolisten local`) and creates +the private `/tmp/.X11-unix` directory. This avoids exhausting `xvfb-run`'s ten +display attempts when many containers start together, which can otherwise +return exit 1 during cleanup even after Pathway Tools saves its PGDB and prints +`Done`. Build and export X-server logs are retained as `build-xvfb.log` and +`export-xvfb.log` in the invocation diagnostics. This wrapper change requires +no SIF rebuild or vendor patch; nonzero build/export exits still fail the task. + +For a controlled transport-inference comparison with an installed SIF, use +`metapathways ptools -o OUTPUT/SAMPLE --entity community --no_transport_inference`. +Omit `--entity` to process the community and MAGs. `analysis_wf` also accepts +`--no_transport_inference`. TIP remains enabled by default; changing the setting +invalidates the corresponding PGDB task cache. Failed SIF builds retain their +on-disk databases under `diagnostics//failed-pgdbs/`, together with the +staged inputs and original failure status. This preserves recovery material; it +does not automatically export or label partial databases as successful. + +For an explicit PGDB taxon override, `ptools` and `analysis_wf` accept +`--taxon_id NCBI_ID`. This changes only private staged `organism-params.dat` +inputs, which are retained in diagnostics. It applies to every selected entity; +use `--entity community` with `ptools` for a community-only experiment. +`--taxprune --taxon_id 131567` uses cellular organisms with taxonomic pruning +enabled, avoiding the separate unpruned rescoring pass documented for +`-no-taxonomic-pruning` in the Pathway Tools User Guide (printed pp. 16–17). +This broad taxon includes multicellular eukaryotes too and is not a microbial-only +filter. It is an experimental workaround, not demonstrated equivalence to +unpruned inference. Neither flag changes MP's gene taxonomic annotations. + +`--taxonomic_scope all|bacteria|archaea|eukaryotes` provides readable aliases +for taxon IDs 131567, 2, 2157, and 2759, respectively; `euks` is accepted as an +alias for `eukaryotes`. It is mutually exclusive with `--taxon_id`. For example, +`--taxprune --taxonomic_scope all` is equivalent to +`--taxprune --taxon_id 131567`. No new default is imposed: omitting both retains +the input taxon and the existing pruning setting. A `prokaryotes` scope is not +yet supported because it needs a union of Bacteria and Archaea; MP rejects it +explicitly rather than silently substituting cellular life (which includes +eukaryotes). Scope changes guide PGDB inference and do not filter input contigs. + +### If only `--threads 4` is specified + +For the default local executor, capable tools receive up to four CPUs each (capped by the available CPU budget). MP detects available CPUs and memory for the total scheduling budget; four threads is not a four-CPU limit for the whole workflow. General tasks reserve the default 16 GB each. In `analysis_wf`, PGDB tasks instead default to 4 GB each and one CPU. Nextflow schedules ready tasks together while their reservations fit. For example, a detected budget of 32 CPUs and 64 GB permits at most four simultaneous tasks that each request four CPUs and 16 GB, even though CPUs remain free. Dependencies can reduce concurrency further. + +Detection is a startup snapshot, not exclusive ownership of the server. Set `--max_cpus` and `--max_memory` on shared machines. Local memory reservations govern scheduling, not hard memory enforcement. If the available memory budget is smaller than a task's reservation, planning fails; choose a suitable explicit `--memory` for a tiny test or provide more capacity. Slurm uses its separate conservative defaults described above. + +### Abundance checkpoints + +`COMPUTE_TPM` checks the assembly, annotation GFF, supplied read files (including R2 for paired inputs), commands, and final abundance outputs when deciding whether to reuse results. Its `bwa/` directory contains generated intermediate files and is not an input dependency. Changes to those intermediates alone do not require recomputing valid abundance tables. + +Checkpoints written before this correction included `bwa/` as an input. Their first invocation with the corrected code recomputes abundance once to replace that old checkpoint; subsequent unchanged runs reuse it. Other tasks retain their existing checkpoint rules. + +### Large multi-sample workflows + +MP writes `main.nf` plus small files under `modules/` in each invocation log directory. This keeps thousands of sample/bin tasks below the JVM compiled-method size limit. Modules expose individual task completion channels: they do not introduce a wait for the whole module, a separate resource budget, or serial sample execution. The shared executor limits and durable MP task checkpoints still apply. Keep the module files with `main.nf` when archiving a generated workflow. + +If an older version failed at startup with `Method too large: Main.runScript`, update MP and repeat the same command with the same output directory. Compilation fails before any tasks are submitted; deleting the output is unnecessary. The next invocation generates a new modular workflow. diff --git a/metapathways/MetaPathways_annotate_fast.py b/metapathways/MetaPathways_annotate_fast.py index ee3bc0a..5a699e9 100644 --- a/metapathways/MetaPathways_annotate_fast.py +++ b/metapathways/MetaPathways_annotate_fast.py @@ -362,7 +362,7 @@ def insert_orf_into_dict(line, contig_dict, shortenorfid=False): seqname = attributes["orf_id"] attributes["seqname"] = seqname if feature_type == "rRNA": - seqname = seqname + "." + attributes["name"] + "_" + str(fields[3]) + seqname = seqname + "." + attributes["name"] + "_" + "_".join((fields[3], fields[4], fields[6])) attributes["seqname"] = seqname if not seqname in contig_dict: contig_dict[seqname] = [] @@ -566,8 +566,13 @@ def write_16S_tRNA_gene_info(contig_id, f_rec, outputgff_file, tag): output_line += "\t" + str(f_rec["score"]) output_line += "\t" + str(f_rec["strand"]) output_line += "\t" + str(f_rec["frame"]) - attributes = "ID=" + str(f_rec["seqname"]).rsplit('-', 1)[1].rsplit('_')[0] - attributes += ";" + "locus_tag=" + str(f_rec["name"]) + # Distinct copies of the same rRNA on a contig are distinct loci. + short_contig = contig_id.rsplit('-', 1)[-1] + subtype = str(f_rec['name']).removesuffix('_rRNA') + strand = 'plus' if f_rec['strand'] == '+' else 'minus' + identifier = f"{short_contig}.{subtype}_{f_rec['start']}_{f_rec['end']}_{strand}" + attributes = "ID=" + identifier + attributes += ";locus_tag=" + identifier attributes += ";" + "product=" + f_rec["product"] output_line += "\t" + attributes @@ -1013,15 +1018,14 @@ def create_annotation( compact_output=compact_output, ) count += 1 # move to the next orf - # Add rRNA and tRNA records to output gff - if rRNA_yes == True: - if contig in rRNA_dictionary: - for rec in rRNA_dictionary[contig]: - write_16S_tRNA_gene_info(contig, rec, outputgff_file, "_rRNA") - if tRNA_yes == True: - if contig in tRNA_dictionary: - for rec in tRNA_dictionary[contig]: - write_16S_tRNA_gene_info(contig, rec, outputgff_file, "_tRNA") + # RNA features belong to contigs, not CDS parser buffers. Emit them once, + # including contigs with RNA genes but no protein-coding predictions. + for contig, records in rRNA_dictionary.items(): + for rec in records: + write_16S_tRNA_gene_info(contig, rec, outputgff_file, "_rRNA") + for contig, records in tRNA_dictionary.items(): + for rec in records: + write_16S_tRNA_gene_info(contig, rec, outputgff_file, "_tRNA") output_comp_annot_file1.close() output_comp_annot_file2.close() diff --git a/metapathways/MetaPathways_create_genbank_ptinput.py b/metapathways/MetaPathways_create_genbank_ptinput.py index 8cbf502..2ea3693 100644 --- a/metapathways/MetaPathways_create_genbank_ptinput.py +++ b/metapathways/MetaPathways_create_genbank_ptinput.py @@ -22,6 +22,7 @@ from os import makedirs, path, listdir, remove, rename + from metapathways.pt_ec import normalize_ecs from metapathways import errorcodes as errormod from metapathways import general_utils as gutils from metapathways import metapathways_utils as mputils @@ -427,6 +428,7 @@ def write_ptinput_files(outfiles, contig_dict, sample_name, nucleotide_seq_dict, else: attrib['ec'] = [attrib['ec']] + attrib['ec'] = normalize_ecs(attrib['ec']) # keep all ORFs used for Ptools pt_attrib_dict[shortid] = attrib @@ -556,11 +558,7 @@ def write_to_pf_file(output_dir_name, shortid, attrib, pfFile, compact_output): gutils.fprintf(pfFile, "METACYC\t%s\n", rxn_val) if 'ec' in attrib: - ec_val = attrib['ec'] - #if ec_val: - # gutils.fprintf(pfFile, "EC\t%s\n", ec_val) - ec_list = list(set(attrib['ec'])) - for ec_val in ec_list: + for ec_val in normalize_ecs(attrib['ec']): gutils.fprintf(pfFile, "EC\t%s\n", ec_val) if 'taxon' in attrib: diff --git a/metapathways/MetaPathways_func_search.py b/metapathways/MetaPathways_func_search.py index c1c805c..41b6804 100644 --- a/metapathways/MetaPathways_func_search.py +++ b/metapathways/MetaPathways_func_search.py @@ -13,6 +13,8 @@ import glob import os import pandas as pd + import tempfile + import shlex from os import path, _exit, rename from optparse import OptionParser, OptionGroup @@ -209,72 +211,50 @@ def main(argv, errorlogger=None, runcommand=None, runstatslogger=None): def _execute_FAST(options, logger=None): - - volumes = 0 - if options.run_mode == 'pervol': - # open *.prj file to check if there are multiple volumes - # if there are then use the per-volume function - with open(options.last_db + '.prj', 'r') as prj_in: - dat_rl = prj_in.readlines() - for line in dat_rl: - if 'volumes=' in line: - volumes = int(line.split('=')[1].strip('\n')) - - # create argument list(s), depending on the number of volumes - args_list = [] - if volumes > 0: - for v in list(range(volumes)): - args = [] - args.append(options.last_executable) - args += ["-f", options.last_f] - args += ["-o", options.last_o + str(v) + ".tmp"] - args += ["-P", options.num_threads] - args += [" -K", options.num_hits] - args += [options.last_db + str(v)] - args += [options.last_query] - args_list.append(args) - else: # if only one volume OR running in default mode - args = [] - args.append(options.last_executable) - args += ["-f", options.last_f] - args += ["-o", options.last_o + ".tmp"] - args += ["-P", options.num_threads] - args += [" -K", options.num_hits] - args += [options.last_db] - args += [options.last_query] - args_list.append(args) - - result = None + """FAST's time-seeded sort filenames must live in an invocation-private root.""" + output = os.path.abspath(options.last_o) try: - if len(args_list) == 1: - a = args_list[0] - result = sysutils.getstatusoutput(" ".join(a)) - rename(a[4], a[4].rsplit('.', 1)[0]) - else: - for a in args_list: - result = sysutils.getstatusoutput(" ".join(a)) - rename(a[4], a[4].rsplit('.', 1)[0]) - out_list = glob.glob(options.last_o + '*') - with open(options.last_o, 'w') as outfile: - for fname in out_list: - with open(fname) as infile: - for line in infile: - outfile.write(line) - os.remove(fname) - # sort the final table on ORF and Bitscore - last_df = pd.read_csv(options.last_o, sep='\t', header=None) - last_df.sort_values(by = [0, 11], ascending = [True, False], inplace=True) - last_df.to_csv(options.last_o, sep='\t', header=False, index=False) - except: - message = "Could not run FAST correctly" - if result and len(result) > 1: - message = result[1] + volumes = 0 + if options.run_mode == 'pervol': + with open(options.last_db + '.prj') as stream: + for line in stream: + if line.startswith('volumes='): + volumes = int(line.split('=', 1)[1]) + with tempfile.TemporaryDirectory(prefix='.fast-', dir=os.path.dirname(output)) as work: + parts = [] + for v in range(volumes or 1): + part = os.path.join(work, f'hits-{v}.tsv') + db = options.last_db + str(v) if volumes else options.last_db + args = [options.last_executable, '-f', str(options.last_f), '-o', part, + '-P', str(options.num_threads), '-K', str(options.num_hits), + '-X', work, db, options.last_query] + result = sysutils.getstatusoutput(shlex.join(args)) + if result[0]: + return result + if not os.path.isfile(part): + raise RuntimeError('FAST returned success without producing its output') + parts.append(part) + if len(parts) == 1: + rename(parts[0], output) + else: + merged = os.path.join(work, 'merged.tsv') + with open(merged, 'w') as destination: + for part in parts: + with open(part) as source: + for line in source: + destination.write(line) + if os.path.getsize(merged): + table = pd.read_csv(merged, sep='\t', header=None) + table.sort_values(by=[0, 11], ascending=[True, False], inplace=True) + table.to_csv(merged, sep='\t', header=False, index=False) + rename(merged, output) + return (0, '') + except Exception as exc: + message = 'Could not run FAST correctly: ' + str(exc) if logger: - logger.printf("ERROR\t%s\n", message) + logger.printf('ERROR\t%s\n', message) return (1, message) - return (result[0], result[1]) - def _execute_BLAST(options, logger=None): args = [] diff --git a/metapathways/MetaPathways_refscore.py b/metapathways/MetaPathways_refscore.py index 30bed7d..499b088 100644 --- a/metapathways/MetaPathways_refscore.py +++ b/metapathways/MetaPathways_refscore.py @@ -9,6 +9,8 @@ import traceback import os import re + import tempfile + import shlex from os import makedirs, sys, remove, rename from sys import path @@ -169,13 +171,12 @@ def blast_against_itself(blast_executable, seq_subset_file, blast_table_out): def last_against_itself(last_executable, seq_subset_file, last_table_out): dirname = os.path.dirname(seq_subset_file.name) - cmd = "%s -o %s -f 0 %s %s" % ( - last_executable, - last_table_out, - dirname + PATHDELIM + "subset_db", - seq_subset_file.name, - ) - result = sysutils.getstatusoutput(cmd) + with tempfile.TemporaryDirectory(prefix='.fast-', dir=os.path.abspath(dirname)) as work: + cmd = shlex.join([last_executable, '-o', last_table_out, '-f', '0', '-X', work, + dirname + PATHDELIM + 'subset_db', seq_subset_file.name]) + result = sysutils.getstatusoutput(cmd) + if result[0]: + raise RuntimeError('FAST reference-score search failed: ' + result[1]) def add_last_refscore_to_file(blast_table_out, refscore_file, allNames): diff --git a/metapathways/MetaPathways_tpm.py b/metapathways/MetaPathways_tpm.py index 9e5f1db..59464fd 100644 --- a/metapathways/MetaPathways_tpm.py +++ b/metapathways/MetaPathways_tpm.py @@ -15,6 +15,7 @@ import multiprocessing import shutil import subprocess + import shlex from os import path, _exit, rename, system @@ -180,7 +181,8 @@ def runUsingBWA(bwaExec, sample_name, indexFile, readgroup, readFiles, bwaFolder readFiles[0], ) - st_cmd = "samtools sort -O bam -o %s -T %s %s" % ( + st_cmd = "samtools sort -@ %d -O bam -o %s -T %s %s" % ( + max(0, int(num_threads) - 1), stOutputTmp, stInterTmp, bwaOutput, @@ -244,10 +246,32 @@ def getReadFiles(readdir, sample_name): return fastqgroups +def coverm_read_arguments(forward, reverse=None, interleaved=False): + """Validate read layout, including the legacy serialized ``None`` value.""" + forward = None if forward in (None, '', 'None') else forward + reverse = None if reverse in (None, '', 'None') else reverse + if not forward: + raise ValueError('A forward, single-end, or interleaved FASTQ is required.') + if interleaved: + if reverse: + raise ValueError('Interleaved input cannot also specify a reverse FASTQ.') + return ['--interleaved', forward] + if reverse: + if path.realpath(forward) == path.realpath(reverse) or ( + path.exists(forward) and path.exists(reverse) and path.samefile(forward, reverse)): + raise ValueError('Paired FASTQs must be different files; use --interleaved for one interleaved file.') + return ['-1', forward, '-2', reverse] + return ['--single', forward] + + def main(argv, errorlogger=None, runcommand=None, runstatslogger=None): parser = createParser() options, args = parser.parse_args(argv) + try: + read_arguments = coverm_read_arguments(options.fwd_fastq, options.rev_fastq, options.interleaved) + except ValueError as error: + parser.error(str(error)) if not (options.contigs != None and path.exists(options.contigs)): parser.error("ERROR\tThe contigs file is missing") errormod.insert_error(10) @@ -304,34 +328,25 @@ def main(argv, errorlogger=None, runcommand=None, runstatslogger=None): command.append('-m trimmed_mean') command.append('-m rpkm') command.append('-m tpm') - # set up fastqs - if options.fwd_fastq and options.rev_fastq: - command.append('-1') - command.append(options.fwd_fastq) - command.append('-2') - command.append(options.fwd_fastq) - elif options.fwd_fastq and options.interleaved: - command.append('--interleaved') - command.append(options.fwd_fastq) - elif options.fwd_fastq and not options.interleaved: - command.append('--single') - command.append(options.fwd_fastq) - else: - parser.error("ERROR\tFASTQs not specified correctly.") - errormod.insert_error(10) - return 1 + command.extend(shlex.quote(str(arg)) for arg in read_arguments) command.append('-r') command.append(options.contigs) command.append('--output-file') command.append(options.output) command.append('-t') - command.append(options.num_threads) + command.append(str(options.num_threads)) command.append('--bam-file-cache-directory') command.append(options.bwaFolder) command.append('--min-read-percent-identity 97') command.append('--min-read-aligned-percent 97') command.append('--exclude-supplementary') + gff_in = options.orfgff + gtf_out = path.join(path.dirname(gff_in), path.basename(gff_in).rsplit('.', 1)[0] + '.gtf') + # Reject malformed/duplicate annotation IDs before expensive mapping. + with open(options.stats, 'w') as stat_out: + run_logged(['gff2gtf.py', '--feature', 'CDS,rRNA,tRNA,pseudogene', gff_in, gtf_out], stat_out) + rpkmstatus = 0 rpkmtext = '' try: @@ -340,57 +355,39 @@ def main(argv, errorlogger=None, runcommand=None, runstatslogger=None): rpkmstatus = 1 pass - with open(options.stats, 'w') as stat_out: + with open(options.stats, 'a') as stat_out: stat_out.write(' '.join(command)) stat_out.write('\n\n') stat_out.write(rpkmtext) stat_out.write('\n\n') + # A failed mapping must not trigger abundance calculations on cached BAMs. + if rpkmstatus != 0: + gutils.eprintf("ERROR\tRPKM calculation was unsuccessful\n") + errormod.insert_error(10) + return 1 + #Start custom abundance analysis - bam_in = glob.glob(options.bwaFolder + PATHDELIM + '*.bam')[0] + bam_in = path.join(options.bwaFolder, path.basename(options.contigs) + '.' + path.basename(options.fwd_fastq) + '.bam') + if not path.isfile(bam_in): + raise RuntimeError(f'CoverM did not create the expected BAM: {bam_in}') sort_out = options.bwaFolder + PATHDELIM + options.sample_name + '.sorted.bam' tmp_bam = options.bwaFolder + PATHDELIM + options.sample_name + '.tmp' - gff_in = options.orfgff - gtf_out = path.join(path.dirname(options.orfgff), path.basename(options.orfgff).rsplit('.', 1)[0] + '.annot.gtf') feat = options.bwaFolder + PATHDELIM + options.sample_name + '.annot.featurecounts.txt' - gen_lens = options.bwaFolder + PATHDELIM + options.sample_name + '.annot.genelengths.txt' abund_calc = path.join(path.dirname(options.output), path.basename(options.output).rsplit('.', 2)[0] + '.orf_counts.tsv') - samcmd = ['samtools', 'sort', '-n', '-T', f'{tmp_bam}', '-o', f'{sort_out}', f'{bam_in}'] - stat_out.write(' '.join(samcmd)) - stat_out.write('\n\n') - sam_result = subprocess.Popen(' '.join(samcmd), stdout=stat_out, stderr=subprocess.PIPE, shell=True) - stat_out.write('\n') - sam_result.wait() - - gtfcmd = ['gff2gtf.py', '--feature', 'CDS,rRNA,tRNA,pseudogene', f'{gff_in}', f'{gtf_out}'] - stat_out.write(' '.join(gtfcmd)) - stat_out.write('\n') - gtf_result = subprocess.Popen(' '.join(gtfcmd), stdout=stat_out, stderr=subprocess.PIPE, shell=True) - stat_out.write('\n') - gtf_result.wait() - - featcmd = ['featureCounts', '-t', 'CDS,rRNA,tRNA,pseudogene', '-p', '-O', '-T', f'{options.num_threads}', '-a', f'{gtf_out}', '-o', f'{feat}', f'{sort_out}'] - stat_out.write(' '.join(featcmd)) - stat_out.write('\n') - feat_result = subprocess.Popen(' '.join(featcmd), stdout=stat_out, stderr=subprocess.PIPE, shell=True) - stat_out.write('\n') - feat_result.wait() - - cutcmd = f'cut -f4,5,9 {gtf_out} | sed \'s/gene_id //g\' | gawk \'{{print $3,$2-$1+1}}\' | tr \' \' \'\t\' > {gen_lens}' - stat_out.write(cutcmd) - stat_out.write('\n') - cut_result = subprocess.Popen(cutcmd, stdout=stat_out, stderr=subprocess.PIPE, shell=True) - stat_out.write('\n') - cut_result.wait() - - abuncmd = ['abund_calc.py', '--counts-file', f'{feat}', '--gene-lengths-file', f'{gen_lens}', '--gtf-file', f'{gtf_out}', '--output', f'{abund_calc}'] - stat_out.write('\n') - stat_out.write(' '.join(abuncmd)) - stat_out.write('\n') - abund_result = subprocess.Popen(' '.join(abuncmd), stdout=stat_out, stderr=subprocess.PIPE, shell=True) - stat_out.write('\n') - abund_result.wait() + # samtools -@ counts additional threads, beyond the main thread. + samcmd = ['samtools', 'sort', '-@', str(max(0, int(options.num_threads) - 1)), '-n', '-T', f'{tmp_bam}', '-o', f'{sort_out}', f'{bam_in}'] + run_logged(samcmd, stat_out) + + featcmd = ['featureCounts', '-t', 'CDS,rRNA,tRNA,pseudogene', '-O', '-T', str(options.num_threads), + '-a', gtf_out, '-o', feat, sort_out] + if read_arguments[0] != '--single': + featcmd.insert(1, '-p') + run_logged(featcmd, stat_out) + + abuncmd = ['abund_calc.py', '--counts-file', feat, '--gtf-file', gtf_out, '--output', abund_calc] + run_logged(abuncmd, stat_out) if rpkmstatus != 0: gutils.eprintf("ERROR\tRPKM calculation was unsuccessful\n") @@ -401,6 +398,23 @@ def main(argv, errorlogger=None, runcommand=None, runstatslogger=None): return rpkmstatus +def run_logged(command, log): + """Stream both output channels and stop immediately on a failed subcommand.""" + display = shlex.join(command) + print('Command: ' + display, flush=True) + log.write(display + '\n') + log.flush() + with subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, + text=True, errors='replace') as process: + for line in process.stdout: + print(line, end='', flush=True) + log.write(line) + log.flush() + code = process.wait() + if code: + raise subprocess.CalledProcessError(code, command) + + def runRPKMCommand(runcommand=None): if runcommand == None: return False @@ -505,7 +519,7 @@ def MetaPathways_tpm(argv, extra_command=None, errorlogger=None, runstatslogger= if errorlogger != None: errorlogger.write("#STEP\tRPKM_CALCULATION\n") try: - main( + status = main( argv, errorlogger=errorlogger, runcommand=extra_command, @@ -515,7 +529,7 @@ def MetaPathways_tpm(argv, extra_command=None, errorlogger=None, runstatslogger= errormod.insert_error(10) return (1, traceback.print_exc(10)) - return (0, "") + return (status, "") if __name__ == "__main__": diff --git a/metapathways/_version.py b/metapathways/_version.py index c2ed4d8..73ac97f 100644 --- a/metapathways/_version.py +++ b/metapathways/_version.py @@ -1,5 +1,5 @@ __author__ = "Ryan J. McLaughlin, Tony X. Liu, Tomer Altman, Aditi N. Nallan, Aria S. Hahn, Julia Anstett, Connor Morgan-Lang, Kishori M. Konwar, Steven J. Hallam" -__version__ = "3.5.1" +__version__ = "3.5.2" __maintainer__ = "Ryan J. McLaughlin" __contact__ = "mcglock@student.ubc.ca" __status__ = "Release" diff --git a/metapathways/analysis_workflow.py b/metapathways/analysis_workflow.py new file mode 100644 index 0000000..e37cbea --- /dev/null +++ b/metapathways/analysis_workflow.py @@ -0,0 +1,374 @@ +"""Strict input discovery and one shared DAG for complete multi-sample analyses.""" +import argparse +import copy +import csv +import fcntl +import gzip +import io +import json +import os +from pathlib import Path +import re +import shlex +import shutil +import sys + +from metapathways import nextflow + +FIELDS = ('sample_id', 'assembly', 'read_layout', 'reads_1', 'reads_2', 'mag_map') +GUIDE = ('README.md#analysis-wf-input-layout and README.md#custom-analysis-manifest ' + '(https://github.com/hallamlab/MetaPathways#analysis-wf-input-layout)') +FASTA = re.compile(r'(.+)\.(?:fasta|fna|fa)(?:\.gz)?$') +READS = re.compile(r'(.+)_(R1|R2|interleaved|single)\.(?:fastq|fq)(?:\.gz)?$') +SAFE = re.compile(r'[A-Za-z][A-Za-z0-9_]*\Z') +RESERVED = {'logs', 'reports', 'inputs', 'assemblies', 'reads', 'mag_maps'} + + +def fail(message): + raise ValueError(f'{message}\nSee {GUIDE}') + + +def parser(): + from metapathways.pipeline import runParser + p = runParser('analysis_wf') + sub = next(a for a in p._actions if isinstance(a, argparse._SubParsersAction)).choices['analysis_wf'] + sub.description = 'Annotate multiple metagenomes, split MAGs, build PGDBs and generate a combined report.' + for action in sub._actions: + if action.dest in ('fwd_fastq', 'rev_fastq', 'interleaved', 'samples', 'test'): + action.help = argparse.SUPPRESS + elif action.dest == 'input_file': + action.help = 'dataset root, or assemblies directory with --reads_dir/--mag_maps_dir; alternative: --manifest' + + sub.add_argument('--manifest', help='TSV with sample_id, assembly, read_layout, reads_1, reads_2, mag_map') + sub.add_argument('--reads_dir', help='Flat reads directory; -i then names the assemblies directory') + sub.add_argument('--mag_maps_dir', help='Flat contig-to-MAG map directory; -i then names the assemblies directory') + sub.add_argument('--no_reads', action='store_true', help='Explicitly omit read mapping during automatic discovery') + sub.add_argument('--no_mags', action='store_true', help='Explicitly omit MAG splitting during automatic discovery') + sub.add_argument('--skip_ptools', action='store_true', help='Omit community and MAG PGDB construction') + sub.add_argument('--image', help='Pathway Tools SIF [registered by build_pt]') + from metapathways.pt_taxonomy import add_taxonomy_options + add_taxonomy_options(sub) + sub.add_argument('--no_transport_inference', action='store_true', help='Disable TIP transport inference') + sub.add_argument('--taxprune', action='store_true', help='Enable Pathway Tools taxonomic pruning') + sub.add_argument('--ptools_memory', type=nextflow.memory, default='4 GB', help='Memory per single-CPU PGDB task [4 GB]') + return p + + +def files(directory): + directory = Path(directory).expanduser().resolve() + if not directory.is_dir(): + fail(f'Missing input directory: {directory}') + result = [] + for p in sorted(directory.iterdir()): + if p.name.startswith('.'): + continue + if not p.is_file(): + fail(f'Expected a flat input directory; unexpected entry: {p}') + result.append(p) + return result + + +def discover(args): + root = Path(args.input_file).expanduser().resolve() + separate = bool(args.reads_dir or args.mag_maps_dir) + assembly_dir = root if separate else root / 'assemblies' + if not separate: + if not root.is_dir(): + fail(f'Missing dataset directory: {root}') + for p in root.iterdir(): + if not p.name.startswith('.') and p.name not in ('assemblies', 'reads', 'mag_maps'): + fail(f'Unexpected dataset entry: {p}') + rows = {} + for p in files(assembly_dir): + match = FASTA.fullmatch(p.name) + if not match: + fail(f'Unrecognized assembly filename: {p}') + sample = match[1] + if sample in rows: + fail(f'Multiple assemblies match sample {sample}') + rows[sample] = dict(zip(FIELDS, (sample, str(p), 'none', '', '', ''))) + if args.no_reads and args.reads_dir or args.no_mags and args.mag_maps_dir: + fail('An input directory conflicts with its --no_reads/--no_mags flag') + if not args.no_reads: + groups = {} + for p in files(args.reads_dir or root / 'reads'): + match = READS.fullmatch(p.name) + if not match or match[1] not in rows: + fail(f'Unrecognized or unmatched reads: {p}') + group = groups.setdefault(match[1], {}) + if match[2] in group: + fail(f'Multiple read files match {match[1]} / {match[2]}') + group[match[2]] = str(p) + for sample, row in rows.items(): + group = groups.get(sample, {}) + if set(group) == {'R1', 'R2'}: + row.update(read_layout='paired', reads_1=group['R1'], reads_2=group['R2']) + elif set(group) in ({'single'}, {'interleaved'}): + mode = next(iter(group)) + row.update(read_layout=mode, reads_1=group[mode]) + else: + fail(f'Missing mates or ambiguous read layout for {sample}: {list(group)}') + if not args.no_mags: + for p in files(args.mag_maps_dir or root / 'mag_maps'): + if p.suffix != '.tsv' or p.stem not in rows: + fail(f'Unrecognized or unmatched MAG map: {p}') + rows[p.stem]['mag_map'] = str(p) + missing = [s for s, row in rows.items() if not row['mag_map']] + if missing: + fail(f'Missing MAG maps for: {", ".join(missing)}') + return list(rows.values()) + + +def read_manifest(filename): + source = Path(filename).expanduser().resolve() + with source.open(newline='') as handle: + reader = csv.DictReader(handle, delimiter='\t') + if reader.fieldnames != list(FIELDS): + fail(f'Manifest header must be exactly: {", ".join(FIELDS)}') + rows = [] + for line, row in enumerate(reader, 2): + if None in row or any(v is None for v in row.values()): + fail(f'Manifest line {line} must contain exactly six tab-separated fields') + for key in ('assembly', 'reads_1', 'reads_2', 'mag_map'): + if row[key]: + p = Path(row[key]).expanduser() + row[key] = str((source.parent / p).resolve()) + rows.append(row) + return rows + + +def map_entities(filename): + entities, contigs = {}, set() + with open(filename) as handle: + for line, text in enumerate(handle, 1): + fields = text.rstrip('\r\n').split('\t') + if len(fields) != 2 or not all(fields) or any(x != x.strip() for x in fields): + fail(f'{filename}:{line}: expected headerless contig_idmag_id') + contig, original = fields + normalized = original.replace('.', '_') + if not SAFE.fullmatch(normalized) or normalized == 'community' or 'non_binned' in normalized: + fail(f'{filename}:{line}: unsupported/reserved MAG ID {original!r}') + if normalized in entities and entities[normalized] != original: + fail(f'{filename}: MAG IDs collide after replacing periods with underscores: {original}') + if contig in contigs: + fail(f'{filename}:{line}: repeated contig assignment {contig}') + contigs.add(contig) + entities[normalized] = original + if not entities: + fail(f'MAG map is empty: {filename}') + return sorted(entities), contigs + + +def validate(rows): + if not rows: + fail('No samples were found') + ids, used = set(), {} + for row in rows: + sample = row['sample_id'] + if not SAFE.fullmatch(sample) or sample.lower() in RESERVED or sample in ids: + fail(f'Invalid, reserved, or duplicate sample ID: {sample!r}; use letters, digits and underscores, starting with a letter') + ids.add(sample) + mode, r1, r2 = row['read_layout'], row['reads_1'], row['reads_2'] + if mode not in ('paired', 'single', 'interleaved', 'none') or \ + (mode == 'paired' and not (r1 and r2)) or \ + (mode in ('single', 'interleaved') and (not r1 or r2)) or \ + (mode == 'none' and (r1 or r2)): + fail(f'{sample}: read_layout and read paths disagree') + for key in ('assembly', 'reads_1', 'reads_2', 'mag_map'): + if not row[key]: + if key == 'assembly': + fail(f'{sample}: missing assembly') + continue + p = Path(row[key]).expanduser().resolve() + if not p.is_file() or p.stat().st_size == 0 or not os.access(p, os.R_OK): + fail(f'{sample}: missing, empty or unreadable {key}: {p}') + stat = p.stat() + identity = (stat.st_dev, stat.st_ino) + if identity in used: + fail(f'{sample}: {key} reuses the same file as {used[identity]}') + used[identity] = f'{sample}/{key}' + row[key] = str(p) + if not FASTA.fullmatch(Path(row['assembly']).name): + fail(f'{sample}: assembly must end in .fa, .fna or .fasta, optionally .gz') + row['entities'], mapped = map_entities(row['mag_map']) if row['mag_map'] else ([], set()) + # Check map membership before submitting any jobs. FASTQs are not fully scanned. + found = set() + opener = gzip.open if row['assembly'].endswith('.gz') else open + with opener(row['assembly'], 'rt') as handle: + first = handle.readline() + if not first.startswith('>'): + fail(f'{sample}: assembly is not FASTA') + def header(text): + tokens = text[1:].split() + if not tokens: + fail(f'{sample}: empty FASTA identifier') + if tokens[0] in found: + fail(f'{sample}: duplicate FASTA identifier {tokens[0]}') + found.add(tokens[0]) + header(first) + for text in handle: + if text.startswith('>'): + header(text) + unknown = mapped - found + if unknown: + fail(f'{sample}: MAG map contigs absent from assembly: {", ".join(sorted(unknown)[:5])}') + return sorted(rows, key=lambda row: row['sample_id']) + + +def save_inputs(rows, output): + text = io.StringIO() + writer = csv.DictWriter(text, FIELDS, delimiter='\t', lineterminator='\n', extrasaction='ignore') + writer.writeheader() + writer.writerows(rows) + manifest = output / 'inputs.resolved.tsv' + if manifest.exists() and manifest.read_text() != text.getvalue(): + fail(f'{manifest} describes different inputs; use a new output directory') + entities_file = output / 'inputs.entities.json' + entities = {row['sample_id']: row['entities'] for row in rows} + if entities_file.exists() and json.loads(entities_file.read_text()) != entities: + fail('The set of MAG IDs changed; use a new output directory') + if not manifest.exists(): + # Refuse to combine an unrelated existing analysis with a new dataset. + if any(p.is_dir() and not p.name.startswith('.') and p.name not in ('logs',) for p in output.iterdir()): + fail('Use a new output directory for the first analysis_wf invocation') + manifest.write_text(text.getvalue()) + if not entities_file.exists(): + entities_file.write_text(json.dumps(entities, indent=2) + '\n') + staging = output / '.metapathways/analysis_wf/inputs' + staging.mkdir(parents=True, exist_ok=True) + staged = [] + for row in rows: + item = dict(row) + for key in ('assembly', 'reads_1', 'reads_2', 'mag_map'): + if not row[key]: + continue + directory = staging / row['sample_id'] / key + directory.mkdir(parents=True, exist_ok=True) + suffix = ('.fasta' if key == 'assembly' else '.tsv' if key == 'mag_map' else '.fastq') + if row[key].endswith('.gz'): + suffix += '.gz' + alias = directory / (row['sample_id'] + suffix) + if alias.is_symlink(): + if alias.resolve() != Path(row[key]): + fail(f'Staged input changed unexpectedly: {alias}') + elif alias.exists(): + fail(f'Unexpected file at staged input path: {alias}') + else: + alias.symlink_to(row[key]) + item[key] = str(alias) + staged.append(item) + return staged + + +def downstream(row, output, annotations, args, image): + sample = row['sample_id'] + base = output / sample + # Pathologic inputs follow annotation reports in the annotation DAG. + parent = next(t['id'] for t in annotations if t.get('context', {}).get('name') == 'PATHOLOGIC_INPUT') + tasks = [] + if row['mag_map']: + ms = base / 'magsplitter' + pf, orfmap = base / 'ptools/0.pf', base / 'ptools/orf_map.txt' + table = base / f'results/annotation_table/{sample}.ORF_annotation_table.txt' + feature_table = base / f'results/annotation_table/{sample}.ptinput.tsv' + mapping = base / f'preprocessed/{sample}.mapping.txt' + saved = ms / 'contig_to_mag.tsv' + cmd = ['magsplitter', '-p', str(pf), '-r', str(orfmap), '-c', str(table), + '-m', row['mag_map'], '-i', str(mapping), '-o', str(ms)] + copy_cmd = [sys.executable, '-c', 'import shutil,sys; shutil.copyfile(*sys.argv[1:])', row['mag_map'], str(saved)] + tasks.append(nextflow.task(f'{sample}:mag_split', f'{sample}:mag_split', + [shlex.join(['mkdir', '-p', str(ms)]), shlex.join(cmd), shlex.join(copy_cmd)], + [str(pf), str(orfmap), str(table), str(mapping), row['mag_map'], str(feature_table)], + [str(ms / 'results'), str(saved)], [parent], memory=args.memory, sample=sample, adopt_existing=False, + cache_version='authoritative-mag-coordinates-v1')) + if args.skip_ptools: + return tasks + script = shutil.which('pgdb_build_wf.py') or str(Path(__file__).resolve().parents[1] / 'dev/pgdb_build_wf.py') + if not Path(script).is_file(): + fail('pgdb_build_wf.py is missing; reinstall MetaPathways') + for entity in ['community'] + row['entities']: + community = entity == 'community' + inputs = base / 'ptools' if community else base / 'magsplitter/results' / entity + results = base / 'results/pgdb/community' if community else base / 'results/pgdb/MAGs' / entity + tag = sample if community else entity + cmd = [sys.executable, script, '--mp_out', str(base), '--tag', sample, '--entity', entity, '--image', image] + if args.taxprune: + cmd.append('--taxprune') + if args.no_transport_inference: + cmd.append('--no_transport_inference') + from metapathways.pt_taxonomy import resolve_taxon + taxon_id = resolve_taxon(args) + if taxon_id is not None: + cmd += ['--taxon_id', str(taxon_id)] + tasks.append(nextflow.task(f'{sample}:pgdb:{entity}', f'{sample}:pgdb:{entity}', [shlex.join(cmd)], + [image, str(inputs), str(base / f'results/annotation_table/{sample}.EC_RXN_map.tsv'), + str(base / f'results/annotation_table/{sample}.ptinput.tsv'), str(base / f'preprocessed/{sample}.fasta')], + [str(results / (tag + suffix)) for suffix in ('cyc.tar.bz2', '_pwy.tsv', '_pwy2orf.tsv')], + [parent if community else f'{sample}:mag_split'], cpus=1, memory=args.ptools_memory, + sample=sample, entity=entity, allow_failure=not community, adopt_existing=False, + cache_version='sequence-backed-pgdb-trna-names-v3', + skip_if_missing=None if community else str(inputs / '0.pf'))) + tasks[-1]['fingerprint_inputs'] = tasks[-1]['inputs'] + [str(base / f'orf_prediction/{sample}.cds.gff')] + return tasks + + +def main(argv=None): + from metapathways.pipeline import prepare_annotation + from metapathways.pt_container import registered_image + p = parser() + args = p.parse_args(['analysis_wf'] + list(sys.argv[1:] if argv is None else argv)) + if not args.output_dir or not args.refdb_dir or not (args.input_file or args.manifest): + fail('Provide -o OUTPUT, -d MPDB and either -i INPUTS or --manifest FILE') + if args.manifest and any((args.input_file, args.reads_dir, args.mag_maps_dir, args.no_reads, args.no_mags)): + fail('--manifest cannot be combined with discovery flags') + if args.fwd_fastq or args.rev_fastq or args.interleaved or args.test or args.samples: + fail('Use per-sample reads and IDs from discovery/manifest, not -1/-2/--interleaved/--test/--samples') + if args.input_format != 'fasta': + fail('analysis_wf requires nucleotide FASTA assemblies') + if any(getattr(args, key) == 'skip' for key in ('PREPROCESS_INPUT', 'ORF_PREDICTION', 'FILTER_AMINOS', + 'FUNC_SEARCH', 'PARSE_FUNC_SEARCH', 'ANNOTATE_ORFS', 'CREATE_ANNOT_REPORTS', 'PATHOLOGIC_INPUT')): + fail('Required annotation stages cannot be skipped in analysis_wf; completed tasks are reused automatically') + output = Path(args.output_dir).expanduser().resolve() + refdb = Path(args.refdb_dir).expanduser().resolve() + if any(re.search(r'[^A-Za-z0-9_./-]', str(x)) for x in (output, refdb)): + fail('Output and MPDB paths must use letters, digits, underscores, hyphens, periods and slashes (legacy tool requirement)') + rows = validate(read_manifest(args.manifest) if args.manifest else discover(args)) + image = None + if not args.skip_ptools: + image = args.image or registered_image() + if not image or not Path(image).expanduser().is_file(): + fail('Build a Pathway Tools SIF with metapathways build_pt, pass --image, or explicitly --skip_ptools') + image = str(Path(image).expanduser().resolve()) + if not shutil.which('apptainer'): + fail('Apptainer is required for Pathway Tools') + if any(row['mag_map'] for row in rows) and not shutil.which('magsplitter'): + fail('MAGSplitter is required when MAG maps are supplied; see README installation instructions') + output.mkdir(parents=True, exist_ok=True) + control = output / '.metapathways/analysis_wf' + control.mkdir(parents=True, exist_ok=True) + with (control / 'planning.lock').open('a') as lock: + try: + fcntl.flock(lock, fcntl.LOCK_EX | fcntl.LOCK_NB) + except BlockingIOError: + fail(f'Another analysis_wf invocation is using {output}') + staged = save_inputs(rows, output) + tasks = [] + for row in staged: + sample_args = copy.copy(args) + sample_args.input_file = row['assembly'] + sample_args.output_dir, sample_args.refdb_dir = str(output), str(refdb) + sample_args.fwd_fastq = row['reads_1'] or None + sample_args.rev_fastq = row['reads_2'] or None + sample_args.interleaved = row['read_layout'] == 'interleaved' + annotation, _ = prepare_annotation(sample_args, p) + # A combined analysis only reuses outputs whose receipts prove provenance. + for task in annotation: + task['adopt_existing'] = False + tasks.extend(annotation) + tasks.extend(downstream(row, output, annotation, args, image)) + if args.force_redo: + for task in tasks: + if task['status'] != 'skip': + task['status'] = 'redo' + print(f'Validated {len(rows)} samples. Resolved inputs: {output / "inputs.resolved.tsv"}') + nextflow.launch(tasks, output, args, 'analysis_wf', dryrun=args.dryrun) diff --git a/metapathways/build_DBs/metacyc_build_ont.py b/metapathways/build_DBs/metacyc_build_ont.py index 7e90e9e..17ee3cc 100644 --- a/metapathways/build_DBs/metacyc_build_ont.py +++ b/metapathways/build_DBs/metacyc_build_ont.py @@ -56,8 +56,8 @@ print('Building MetaCyc Ontology...') ont_ids = {} ont_common = {} -stop_list = [] -for k in tqdm(class2types): +stop_list = set() +for k in tqdm(class2types, disable=not sys.stderr.isatty()): while k not in stop_list: if k in class2common: if k in ont_ids: @@ -80,11 +80,11 @@ else: new_maps.append(m) new_com_maps.append(com_m) - p_cnt =+ 1 + p_cnt += 1 ont_ids[k] = new_maps ont_common[k] = new_com_maps if ((map_cnt == p_cnt) | ('FRAMES' in parents)): - stop_list.append(k) + stop_list.add(k) else: parents = class2types[k] ont_ids[k] = [] @@ -96,9 +96,9 @@ class2common[k] ]) else: - stop_list.append(k) + stop_list.add(k) else: - stop_list.append(k) + stop_list.add(k) print('Saving MetaCyc Ontology...') path_ont_list = [] @@ -107,12 +107,13 @@ for path in path2types: for t in path2types[path]: for i,h in enumerate(ont_ids[t]): - c = ont_common[t][i] + h = list(h) + c = list(ont_common[t][i]) for p in h_prune_list: if p in h: h.remove(p) for p in c_prune_list: - if p in h: + if p in c: c.remove(p) common_name = path2common[path] path_ont_list.append([path, common_name, diff --git a/metapathways/build_DBs/metacyc_mapping_build.py b/metapathways/build_DBs/metacyc_mapping_build.py index 195ac84..71c344b 100755 --- a/metapathways/build_DBs/metacyc_mapping_build.py +++ b/metapathways/build_DBs/metacyc_mapping_build.py @@ -228,7 +228,7 @@ def build_rxnenz_dict(dat): c_enz_list = [] for c_tmp in com_flatlist_tmp: - e = prot2cat_dict[c][0] + e = prot2cat_dict[c_tmp][0] c_enz_list.extend(e) prot2enz_dict[m].extend(c_enz_list) @@ -245,6 +245,7 @@ def build_rxnenz_dict(dat): enzrxn_list.append([m, r]) enzrxns_df = pd.DataFrame(enzrxn_list, columns=['MC', 'RXN']) +enzrxns_df.drop_duplicates(inplace=True) enzrxns_df.to_csv(os.path.join(mc_dir, 'MetaCyc-monomer-rxn-pairs.tsv'), sep='\t', index=False ) @@ -263,8 +264,6 @@ def build_rxnenz_dict(dat): # Build Pathway to Compounds dictionary pwy_dict, pwy2cmp_dict = build_pwycmp_dict(pwy_dat, cmp_dict) -print(pwy_dict['METH-ACETATE-PWY']) -print(pwy2cmp_dict['METH-ACETATE-PWY']) # Create Pathway -> Reactions -> Compounds pwy_rxn_cmp_list = [] @@ -288,4 +287,3 @@ def build_rxnenz_dict(dat): pwy_rxn_cmp_df.to_csv(os.path.join(mc_dir, 'MetaCyc-PWY-RXN-CMP-map.tsv'), sep='\t', index=False ) - diff --git a/metapathways/cli_logging.py b/metapathways/cli_logging.py new file mode 100644 index 0000000..1fc76b0 --- /dev/null +++ b/metapathways/cli_logging.py @@ -0,0 +1,41 @@ +"""Keep the complete CLI transcript in the selected output directory.""" +from contextlib import contextmanager, redirect_stderr, redirect_stdout +from datetime import datetime, timezone +from pathlib import Path +import shlex +import sys +import uuid + + +class Tee: + def __init__(self, terminal, log): + self.terminal, self.log = terminal, log + + def write(self, value): + self.terminal.write(value) + self.log.write(value) + self.flush() + return len(value) + + def flush(self): + self.terminal.flush() + self.log.flush() + + def isatty(self): + return False + + def fileno(self): + return self.terminal.fileno() + + +@contextmanager +def transcript(directory, argv): + folder = Path(directory).expanduser().absolute() / 'logs' / 'cli' + folder.mkdir(parents=True, exist_ok=True) + stamp = datetime.now(timezone.utc).strftime('%Y%m%dT%H%M%SZ') + path = folder / (stamp + '-' + uuid.uuid4().hex[:8] + '.log') + with path.open('w') as log: + with redirect_stdout(Tee(sys.stdout, log)), redirect_stderr(Tee(sys.stderr, log)): + print('Command: ' + shlex.join(argv)) + print(f'CLI log: {path}') + yield diff --git a/metapathways/execution.py b/metapathways/execution.py index f5d49a8..fadcda7 100644 --- a/metapathways/execution.py +++ b/metapathways/execution.py @@ -13,6 +13,8 @@ import os import re import time + import importlib + import shlex from subprocess import Popen, PIPE, STDOUT from os import makedirs, listdir, _exit @@ -23,7 +25,6 @@ from metapathways import sysutil as sysutils from metapathways import general_utils as gutils - from metapathways import scripts as python_scripts except: print(""" Could not load some user defined module functions""") @@ -33,13 +34,13 @@ def execute_pipeline_stage(pipeline_command, \ extra_command=None, errorlogger=None, runstatslogger=None): - argv = [x.strip() for x in pipeline_command.split()] + argv = shlex.split(pipeline_command) funcname = re.sub(r".py$", "", argv[0]) funcname = re.sub(r"^.*/", "", funcname) args = argv[1:] - if hasattr(python_scripts, funcname): - methodtocall = getattr(getattr(python_scripts, funcname), funcname) + if funcname.startswith('MetaPathways_'): + methodtocall = getattr(importlib.import_module('metapathways.' + funcname), funcname) if extra_command == None: result = methodtocall( args, errorlogger=errorlogger, runstatslogger=runstatslogger) diff --git a/metapathways/jobscreator.py b/metapathways/jobscreator.py index 572a1d0..1ff7b7d 100644 --- a/metapathways/jobscreator.py +++ b/metapathways/jobscreator.py @@ -29,7 +29,6 @@ PATHDELIM = sysutils.pathDelim() -@gutils.Singleton class Params: params = {} def __init__(self, params): @@ -52,13 +51,11 @@ def print_key_values(self): print(self.params) -@gutils.Singleton class Configs: def __init__(self, configs): for key, value in configs.items(): setattr(self, key, value) -@gutils.Singleton class ContextCreator: params = None configs = None @@ -261,7 +258,7 @@ def create_orf_prediction_cmd(self, s) : mode = self.params.get('ORF Prediction Arguments', 'orf_mode') - num_threads = str(self.configs.NUM_CPUS) + num_threads = self.configs.NUM_CPUS pyScript = self.configs.ORF_PREDICTION executable = self.configs.PRODIGAL_EXECUTABLE @@ -594,7 +591,7 @@ def create_scan_rRNA_seqs_cmd(self, s): if bar_exe == None: eprintf("ERROR\tCannot find barrnap\n") barnap_cmd = "%s --quiet --threads %s --outseq %s %s > %s"\ - %(bar_exe, str(num_threads), + %(bar_exe, num_threads, context.outputs['rRNA_barout_seq'], context.inputs['input_fasta'], context.outputs['rRNA_barout_gff']) context.commands = [barnap_cmd] @@ -816,7 +813,7 @@ def create_genbank_file_cmd(self, s): genbank_file_status = self.params.get('Pipeline Step Arguments', 'GENBANK_FILE') if genbank_file_status in ['redo'] or\ - (genbank_file_status in ['yes'] and not s.hasGenbankFile() ): + genbank_file_status in ['yes']: cmd += ' --out-gbk ' + context.outputs['output_annot_gbk'] context.message = self._Message("GENBANK FILE" ) @@ -903,7 +900,7 @@ def create_ptinput_cmd(self, s): 'PATHOLOGIC_INPUT') - if context.status in ['redo'] or (context.status in ['yes'] and not s.hasPToolsInput() ): + if context.status in ['redo'] or context.status in ['yes']: cmd += ' --out-ptinput ' + s.output_fasta_pf_dir cmd += ' -n ' + context.inputs_optional['input_nucleotide_fasta'] cmd += ' --ncbi-tree ' + context.inputs1['ncbi_tree'] @@ -968,7 +965,7 @@ def create_report_files_cmd(self, s): #add the command now, remove to disable in a hackish way context.commands = [cmd] context.status = self.params.get('Pipeline Step Arguments', - 'ANNOTATE_ORFS') + 'CREATE_ANNOT_REPORTS') context.message = self._Message("CREATING REPORT FILE FOR ORF ANNOTATION") contexts.append(context) return contexts @@ -984,6 +981,10 @@ def create_rpkm_cmd(self, s): if rpkm_input: fwd_fq = rpkm_input[0][0] rev_fq = rpkm_input[0][1] + if fwd_fq in ('', 'None'): + fwd_fq = None + if rev_fq in ('', 'None'): + rev_fq = None inter = rpkm_input[1] else: fwd_fq = None @@ -1052,8 +1053,10 @@ def create_rpkm_cmd(self, s): def __init__(self, params, configs): - self.params = gutils.Singleton(Params)(params) - self.configs = gutils.Singleton(Configs)(configs) + self.factory = {} + self.stageList = {} + self.params = Params(params) + self.configs = Configs(configs) self.initFactoryList() def getContexts(self, s, stage): @@ -1179,4 +1182,3 @@ def addJobs(self, s, block_mode = False): s.addContexts(contextBlock) - diff --git a/metapathways/metacyc_db.py b/metapathways/metacyc_db.py new file mode 100644 index 0000000..250febc --- /dev/null +++ b/metapathways/metacyc_db.py @@ -0,0 +1,181 @@ +"""Prepare MP references from a user's licensed MetaCyc export or Pathway Tools SIF.""" +import argparse +import csv +from datetime import datetime, timezone +import json +from pathlib import Path +import re +import shutil +import subprocess +import tempfile +import sys + +from metapathways.pt_container import digest, exec_command, save_json + + +REQUIRED = ('protseq.fsa', 'proteins.dat', 'enzrxns.dat', 'reactions.dat', + 'pathways.dat', 'compounds.dat', 'classes.dat') +TABLES = ('MetaCyc-monomer-rxn-pairs.tsv', 'MetaCyc-PWY-RXN-CMP-map.tsv', + 'MetaCyc_PWY_Ontology.tsv') + + +def source_path(source): + p = Path(source).expanduser().resolve() + if p.name == 'protseq.fsa': + p = p.parent + if p.is_file() and p.suffix.lower() == '.sif': + return p + if p.is_dir(): + missing = [name for name in REQUIRED if not (p/name).is_file()] + if not missing: + return p + raise ValueError('Incomplete MetaCyc data directory; missing ' + ', '.join(missing) + + '. Use the Pathway Tools SIF to export the matching flat files; protseq.fsa alone is insufficient. See README.md: MetaCyc from Pathway Tools.') + raise ValueError(f'MetaCyc source must be a local SIF or complete data directory: {p}; copy remote SFTP data locally first') + + +def make_tables(source, output): + """Use the repository's MetaCyc builders on a private, same-release copy.""" + source, output = Path(source), Path(output) + output.mkdir(parents=True, exist_ok=True) + fasta_ids = [] + with (source/'protseq.fsa').open() as stream: + for line in stream: + if line.startswith('>'): + match = re.match(r'>gnl\|META\|([^\s]+)', line) + if not match: + raise ValueError('Unexpected MetaCyc FASTA identifier: ' + line.strip()) + fasta_ids.append(match.group(1)) + fasta_set = set(fasta_ids) + if not fasta_ids or len(fasta_ids) != len(fasta_set): + raise ValueError('MetaCyc FASTA has no sequences or contains duplicate identifiers') + versions = set() + identifiers = {} + for filename in REQUIRED[1:]: + with (source/filename).open(errors='replace') as stream: + ids = set() + for line in stream: + if line.startswith('# Version:'): + versions.add(line.partition(':')[2].strip()) + elif line.startswith('UNIQUE-ID - '): + ids.add(line.removeprefix('UNIQUE-ID - ').strip()) + if not ids: + raise ValueError('Empty MetaCyc flat file: ' + filename) + identifiers[filename] = ids + if len(versions) > 1: + raise ValueError('Mixed MetaCyc releases in input flat files: ' + ', '.join(sorted(versions))) + missing = fasta_set - identifiers['proteins.dat'] + if missing: + raise ValueError('FASTA proteins missing from proteins.dat: ' + ', '.join(sorted(missing)[:10])) + scripts = Path(__file__).parent / 'build_DBs' + subprocess.run([sys.executable, str(scripts/'metacyc_mapping_build.py'), str(source)], check=True) + subprocess.run([sys.executable, str(scripts/'metacyc_build_ont.py'), str(source), str(output)], check=True) + for name in TABLES[:2]: + shutil.copy2(source/name, output/name) + counts = {} + for name in TABLES: + with (output/name).open() as stream: + reader = csv.DictReader(stream, delimiter='\t') + counts[name] = sum(1 for row in reader) + if not counts[name]: + raise ValueError('MetaCyc builder produced an empty table: ' + name) + with (output/TABLES[0]).open() as stream: + pairs = list(csv.DictReader(stream, delimiter='\t')) + if any(r['MC'] not in fasta_set or r['RXN'] not in identifiers['reactions.dat'] for r in pairs): + raise ValueError('MetaCyc mapping table references proteins or reactions absent from its source') + counts['proteins'] = len(fasta_ids) + counts['proteins_with_reaction'] = len({r['MC'] for r in pairs}) + counts['proteins_without_reaction'] = len(fasta_ids) - counts['proteins_with_reaction'] + return counts + + +def export_image(image, state): + state = Path(state) + (state/'export').mkdir(parents=True) + script = r'''set -eu +cp -a /opt/ptools-local-template /data/ptools-local +if test -f /opt/mp-ncbirc; then cp /opt/mp-ncbirc /data/.ncbirc; fi +meta_root=/opt/pathway-tools/aic-export/pgdbs/biocyc/metacyc +version=$(cat "$meta_root/default-version") +test -n "$version" +cp "$meta_root/$version/data/protseq.fsa" /data/export/protseq.fsa +printf '%s\n' "$version" > /data/export/version.txt +xvfb-run -a /opt/pathway-tools/pathway-tools -no-patch-download -no-cel-overview -disable-metadata-saving -nologfile -lisp -eval '(progn (with-organism (:org-id '\''META) (dump-frames-to-attribute-value-files "/data/export/")) (format t "~%MP-METACYC-EXPORTED~%") (exit))' +''' + # This exports the bundled reference; it does not create a sample PGDB. + log = state/'export.log' + with log.open('w') as out: + result = subprocess.run(exec_command(image, state, ['sh', '-ec', script]), + stdout=out, stderr=subprocess.STDOUT, timeout=1800) + text = log.read_text(errors='replace') + print(text, flush=True) + if result.returncode or 'MP-METACYC-EXPORTED' not in text.splitlines(): + raise RuntimeError('MetaCyc reference export failed; see ' + str(log)) + return source_path(state/'export') + + +def prepare(source, root, aligner): + source, root = source_path(source), Path(root).resolve() + if aligner not in ('fast', 'blast'): + raise ValueError('MetaCyc aligner must be fast or blast') + root.mkdir(parents=True, exist_ok=True) + with tempfile.TemporaryDirectory(prefix='.metacyc-build-', dir=root) as scratch: + work = Path(scratch) + if source.is_file(): + raw = export_image(source, work/'state') + else: + # Existing scripts write tables beside the FASTA; never modify the source. + raw = work/'source' + raw.mkdir() + for name in REQUIRED: + shutil.copy2(source/name, raw/name) + (raw/'version.txt').write_text((source/'version.txt').read_text() if (source/'version.txt').is_file() else source.parent.name) + + staged = work/'reference' + functional, categories = staged/'functional', staged/'functional_categories' + formatted = functional/'formatted' + formatted.mkdir(parents=True) + categories.mkdir() + counts = make_tables(raw, categories) + fasta = functional/'metacyc' + shutil.copy2(raw/'protseq.fsa', fasta) + prefix = formatted/'metacyc' + with Path(str(prefix)+'-names.txt').open('w') as out, fasta.open() as stream: + for line in stream: + if line.startswith('>'): + out.write(line) + command = (['fastdb', '-p', str(prefix), str(fasta)] if aligner == 'fast' else + ['makeblastdb', '-in', str(fasta), '-dbtype', 'prot', '-parse_seqids', '-out', str(prefix)]) + subprocess.run(command, check=True) + sentinel = Path(str(prefix) + ('.prj' if aligner == 'fast' else '.pdb')) + if not sentinel.is_file(): + raise RuntimeError('MetaCyc indexer did not produce ' + sentinel.name) + version_file = raw/'version.txt' + version = version_file.read_text().strip() if version_file.is_file() else raw.parent.name + manifest = dict(source=str(source), release=version, aligner=aligner, counts=counts, + created_at=datetime.now(timezone.utc).isoformat(), + source_sha256={name: digest(raw/name) for name in REQUIRED}) + if source.is_file(): + manifest['image_sha256'] = digest(source) + (categories/'MetaCyc_reldate.txt').write_text('Release: ' + version + '\n') + save_json(categories/'MetaCyc_provenance.json', manifest) + # All export, mapping and indexing checks finish before publication. + new_indexes = {file.name for file in formatted.glob('metacyc.*')} + for old in (root/'functional/formatted').glob('metacyc.*'): + if old.name not in new_indexes: + old.unlink() + for file in sorted(staged.rglob('*')): + if file.is_file(): + destination = root/file.relative_to(staged) + destination.parent.mkdir(parents=True, exist_ok=True) + file.replace(destination) + print('Prepared MetaCyc ' + version + ': ' + json.dumps(counts), flush=True) + + +if __name__ == '__main__': + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument('--source', required=True) + parser.add_argument('--output', required=True) + parser.add_argument('--aligner', choices=('fast', 'blast'), required=True) + args = parser.parse_args() + prepare(args.source, args.output, args.aligner) diff --git a/metapathways/metapathways_utils.py b/metapathways/metapathways_utils.py index 0f7e7f1..90c50ca 100644 --- a/metapathways/metapathways_utils.py +++ b/metapathways/metapathways_utils.py @@ -62,7 +62,7 @@ def exit_process(message=None, logger=None): if logger: logger.printf("ERROR\tExiting the Python code\n") logger.printf("ERROR\t" + message + "\n") - _exit(0) + raise SystemExit(1) def exit_step(message=None): diff --git a/metapathways/nextflow.py b/metapathways/nextflow.py new file mode 100644 index 0000000..156eeae --- /dev/null +++ b/metapathways/nextflow.py @@ -0,0 +1,459 @@ +"""Nextflow scheduling behind the existing MetaPathways CLI. + +Stage tools continue writing their established output paths. Each Nextflow task +validates a durable receipt against those files instead of trusting a cached +sentinel when a user has removed or changed published outputs. +""" +import argparse +import fcntl +import hashlib +import json +import os +from pathlib import Path +import re +import shlex +import shutil +import subprocess +import sys +import uuid +import queue +import signal +import threading +import time + + +def positive(value): + n = int(value) + if n < 1: + raise argparse.ArgumentTypeError('must be a positive integer') + return n + + +def memory(value): + if not re.fullmatch(r'\d+(?:\.\d+)?\s*(?:KB|MB|GB|TB)', value, re.I): + raise argparse.ArgumentTypeError('use a size such as "16 GB"') + if float(re.match(r'[0-9.]+', value).group()) <= 0: + raise argparse.ArgumentTypeError('memory must be positive') + return value.upper() + + +def add_resources(parser, task_memory='16 GB'): + group = parser.add_argument_group('Execution Resources') + group.add_argument('--max_cpus', type=positive, default=None, + help='total CPUs available to this command [available CPUs]') + group.add_argument('--memory', type=memory, default=task_memory, + help=f'memory reservation per task [{task_memory}]') + group.add_argument('--max_memory', type=memory, default=None, + help='total memory available to this command [available host memory; Slurm: 64 GB]') + group.add_argument('--max_tasks', type=positive, default=None, + help='maximum simultaneously running tasks [limited by CPU/memory]') + + + group.add_argument('--executor', choices=['local', 'slurm'], default='local', + help='execution backend [local]; Slurm uses your logged-in cluster identity') + group.add_argument('--account', type=slurm_token, help='Slurm allocation/account') + group.add_argument('--partition', type=slurm_token, help='Slurm partition') + group.add_argument('--qos', type=slurm_token, help='Slurm quality of service') + group.add_argument('--reservation', type=slurm_token, help='Slurm reservation') + group.add_argument('--time_limit', type=duration, default='24h', help='Slurm walltime per task [24h]') + group.add_argument('--submit_rate', type=positive, default=6, help='maximum Slurm submissions per minute [6]') + group.add_argument('--work_dir', help='custom Nextflow work directory; retained after the run') + group.add_argument('--conda_cache', help='custom Conda cache directory; retained after the run') + group.add_argument('--keep_work', action='store_true', help='retain automatically allocated work/cache directories') + + +def slurm_token(value): + if not re.fullmatch(r'[A-Za-z0-9][A-Za-z0-9_.-]*', value): + raise argparse.ArgumentTypeError('use letters, digits, underscore, period or hyphen') + return value + + +def duration(value): + if not re.fullmatch(r'[1-9][0-9]*(?:s|m|h|d)', value): + raise argparse.ArgumentTypeError('use a positive duration such as 30m, 12h or 2d') + return value + + +def memory_bytes(value): + number, unit = re.fullmatch(r'([0-9.]+)\s*(KB|MB|GB|TB)', memory(value)).groups() + return int(float(number) * 1024 ** {'KB': 1, 'MB': 2, 'GB': 3, 'TB': 4}[unit]) + + +def ordered(tasks): + by_id = {t['id']: t for t in tasks} + if len(by_id) != len(tasks): + raise ValueError('Duplicate task identifiers') + result, visiting, seen = [], set(), set() + def visit(identifier): + if identifier not in by_id: + raise ValueError(f'Unknown dependency: {identifier}') + if identifier in visiting: + raise ValueError(f'Cyclic task dependency: {identifier}') + if identifier in seen: + return + visiting.add(identifier) + for dep in by_id[identifier]['dependencies']: + visit(dep) + visiting.remove(identifier) + seen.add(identifier) + result.append(by_id[identifier]) + for t in tasks: + visit(t['id']) + return result + + +def task(identifier, label, commands, inputs=(), outputs=(), dependencies=(), cpus=1, + memory='16 GB', **kwargs): + return dict(id=identifier, label=label, commands=commands, inputs=list(inputs), + outputs=list(outputs), dependencies=list(dependencies), cpus=cpus, + memory=memory, status='yes', **kwargs) + + +def groovy(value): + return "'" + str(value).replace('\\', '\\\\').replace("'", "\\'").replace('\n', '\\n') + "'" + + +def process_definition(t, name, manifest): + package_root = str(Path(__file__).resolve().parent.parent) + command = shlex.join([sys.executable, '-m', 'metapathways.nf_worker', str(manifest), t['id']]) + body = f'export PYTHONPATH={shlex.quote(package_root)}${{PYTHONPATH:+:$PYTHONPATH}}\n{command}\n' + inputs = '\n'.join(f' val dependency_{i}' for i in range(max(1, len(t['dependencies'])))) + return f'''process {name} {{ + tag {groovy(t['label'])} + cpus {t['cpus']} + memory {groovy(t['memory'])} + cache false + input: +{inputs} + output: + path 'receipt.json' + script: + {groovy(body)} +}}''' + + +def render_modules(tasks, manifest, batch_size=64): + """Bound compiled script size without adding scheduling barriers. + + Each module exposes individual task completion channels. A consumer waits + only for its own dependencies, even when their producers share a module + with other tasks. All processes still use the same Nextflow executor. + """ + if batch_size < 1 or batch_size > 64: + raise ValueError('Workflow module size must be between 1 and 64') + tasks = ordered(tasks) + names = {t['id']: f'TASK_{i:04d}' for i, t in enumerate(tasks)} + batches = [tasks[i:i + batch_size] for i in range(0, len(tasks), batch_size)] + owner = {t['id']: i for i, batch in enumerate(batches) for t in batch} + exports = {dep for t in tasks for dep in t['dependencies'] if owner[dep] != owner[t['id']]} + files, includes, calls = {}, [], [] + for i, batch in enumerate(batches): + workflow = f'BATCH_{i:04d}' + external = list(dict.fromkeys(dep for t in batch for dep in t['dependencies'] if owner[dep] != i)) + ports = {dep: f'upstream_{j}' for j, dep in enumerate(external)} + blocks = [process_definition(t, names[t['id']], manifest) for t in batch] + lines = [f'workflow {workflow} {{'] + if external: + lines += [' take:'] + [f' {ports[dep]}' for dep in external] + lines.append(' main:') + for t in batch: + args = ', '.join(ports[dep] if owner[dep] != i else names[dep] + '.out' for dep in t['dependencies']) + lines.append(f" {names[t['id']]}({args or 'Channel.value(true)'})") + emitted = [t['id'] for t in batch if t['id'] in exports] + if emitted: + lines += [' emit:'] + [f' done_{names[dep]} = {names[dep]}.out' for dep in emitted] + lines.append('}') + files[f'modules/{workflow}.nf'] = '\n\n'.join(blocks) + '\n\n' + '\n'.join(lines) + '\n' + includes.append(f"include {{ {workflow} }} from './modules/{workflow}'") + args = ', '.join(f'BATCH_{owner[dep]:04d}.out.done_{names[dep]}' for dep in external) + calls.append(f' {workflow}({args})') + files['main.nf'] = 'nextflow.enable.dsl=2\n\n' + '\n'.join(includes) + '\n\nworkflow {\n' + '\n'.join(calls) + '\n}\n' + return files + + +def local_capacity(): + cpus = len(os.sched_getaffinity(0)) + available = None + try: + for line in Path('/proc/meminfo').read_text().splitlines(): + if line.startswith('MemAvailable:'): + available = int(line.split()[1]) * 1024 + quota, period = Path('/sys/fs/cgroup/cpu.max').read_text().split() + if quota != 'max': + cpus = min(cpus, max(1, int(quota) // int(period))) + except (OSError, ValueError): + pass + try: + limit = Path('/sys/fs/cgroup/memory.max').read_text().strip() + if limit != 'max': + remaining = max(1, int(limit) - int(Path('/sys/fs/cgroup/memory.current').read_text())) + available = min(available, remaining) if available is not None else remaining + except (OSError, ValueError): + pass + return cpus, (f'{max(1, available // (1024 * 1024))} MB' if available is not None else None) + + +def configuration(tasks, args, conda_cache): + backend = getattr(args, 'executor', 'local') + local_cpus, local_memory = local_capacity() if backend == 'local' else (None, None) + cpus = getattr(args, 'max_cpus', None) or (32 if backend == 'slurm' else local_cpus) + limit_memory = getattr(args, 'max_memory', None) or ('64 GB' if backend == 'slurm' else local_memory) + if any(t['cpus'] < 1 or t['cpus'] > cpus for t in tasks): + raise ValueError('Task threads must be positive and no greater than --max_cpus') + largest_memory = max(memory_bytes(t['memory']) for t in tasks) + if limit_memory and largest_memory > memory_bytes(limit_memory): + raise ValueError('A task requests more memory than --max_memory') + config = [f'process.executor = {groovy(backend)}', "process.errorStrategy = 'finish'", + 'process.maxRetries = 0', f'conda.cacheDir = {groovy(str(conda_cache / "envs"))}'] + if backend == 'local': + if any(getattr(args, key, None) for key in ('account', 'partition', 'qos', 'reservation')): + raise ValueError('Slurm flags require --executor slurm') + config.append(f'executor.cpus = {cpus}') + if limit_memory: + config.append(f'executor.memory = {groovy(limit_memory)}') + # Default Nextflow queueSize (100) can otherwise underutilize large hosts. + jobs = getattr(args, 'max_tasks', None) or cpus + else: + if not getattr(args, 'account', None) or not getattr(args, 'partition', None): + raise ValueError('Slurm requires --account and --partition') + # Slurm does not use executor.cpus/memory as aggregate limits. Bound + # submitted jobs conservatively using the largest task request instead. + jobs = min(getattr(args, 'max_tasks', None) or 4, + cpus // max(t['cpus'] for t in tasks), + memory_bytes(limit_memory) // largest_memory) + options = [] + for key in ('account', 'qos', 'reservation'): + if getattr(args, key, None): + options.append('--' + key + '=' + slurm_token(getattr(args, key))) + config += [f'process.queue = {groovy(slurm_token(args.partition))}', + f'process.clusterOptions = {groovy(" ".join(options))}', + f'process.time = {groovy(duration(getattr(args, "time_limit", "24h")))}', + f'executor.submitRateLimit = {groovy(str(getattr(args, "submit_rate", 6)) + "/1min")}', + "executor.queueStatInterval = '1min'", "executor.pollInterval = '10sec'"] + config.append(f'executor.queueSize = {jobs}') + return '\n'.join(config) + '\n', dict(executor=backend, max_cpus=cpus, max_memory=limit_memory, max_tasks=jobs) + + +def stream_run(command, cwd, env, tasks, console): + """Mirror controller and worker output to the terminal and a durable log.""" + lines = queue.Queue() + process = subprocess.Popen(command, cwd=cwd, env=env, stdout=subprocess.PIPE, + stderr=subprocess.STDOUT, text=True, errors='replace', bufsize=1) + def read_controller(): + for line in process.stdout: + lines.put(line) + reader = threading.Thread(target=read_controller, daemon=True) + reader.start() + offsets = {t['id']: 0 for t in tasks} + def emit(line): + print(line, end='', flush=True) + console.write(line) + console.flush() + def drain(): + while True: + try: + emit(lines.get_nowait()) + except queue.Empty: + break + for t in tasks: + path = Path(t['log']) + if path.exists(): + with path.open(errors='replace') as f: + f.seek(offsets[t['id']]) + for line in f: + emit(f"[{t['label']}] {line}") + offsets[t['id']] = f.tell() + try: + while process.poll() is None: + drain() + time.sleep(0.2) + reader.join() + drain() + except BaseException: + process.send_signal(signal.SIGINT) + try: + process.wait(timeout=30) + except subprocess.TimeoutExpired: + process.terminate() + raise + finally: + process.stdout.close() + if process.returncode: + raise subprocess.CalledProcessError(process.returncode, command) + + +def launch(tasks, output_dir, args, name, dryrun=False): + if not tasks: + raise ValueError('No tasks were selected') + tasks = ordered(tasks) + output_dir = Path(output_dir).resolve() + state = output_dir / '.metapathways' / name + state.mkdir(parents=True, exist_ok=True) + with (state / 'controller.lock').open('w') as lock: + try: + fcntl.flock(lock, fcntl.LOCK_EX | fcntl.LOCK_NB) + except BlockingIOError: + raise RuntimeError(f'Another {name} command is already using {output_dir}') + run_id = uuid.uuid4().hex + run_dir = output_dir / 'logs' / name / run_id + run_dir.mkdir(parents=True) + scratch = state / 'tmp' / run_id + work_override = getattr(args, 'work_dir', None) + cache_override = getattr(args, 'conda_cache', None) + work = (Path(work_override).expanduser().resolve() / (name + '-' + run_id) if work_override else scratch / 'work') + cache = Path(cache_override).expanduser().resolve() if cache_override else scratch / 'conda' + config_text, resources = configuration(tasks, args, cache) + for t in tasks: + key = hashlib.sha256(t['id'].encode()).hexdigest() + t['receipt'] = str(state / 'receipts' / (key + '.json')) + t['log'] = str(run_dir / 'tasks' / (key + '.log')) + t['invocation_receipt'] = str(run_dir / 'tasks' / (key + '.json')) + manifest = run_dir / 'tasks.json' + manifest.write_text(json.dumps(tasks, indent=2) + '\n') + nf = run_dir / 'main.nf' + for relative, content in render_modules(tasks, manifest).items(): + target = run_dir / relative + target.parent.mkdir(parents=True, exist_ok=True) + target.write_text(content) + config = run_dir / 'nextflow.config' + config.write_text(config_text) + summary = dict(resources=resources, work_dir=str(work), conda_cache=str(cache), status='PLANNED') + summary_path = run_dir / 'summary.json' + summary_path.write_text(json.dumps(summary, indent=2) + '\n') + if dryrun: + for t in tasks: + print(f"{t['label']}: cpus={t['cpus']} memory={t['memory']} after={','.join(t['dependencies']) or '-'}") + for cmd in t['commands']: + print(' ' + cmd) + print(f'Execution plan: {manifest}') + return run_dir + executable = shutil.which('nextflow') + if not executable: + raise RuntimeError('Nextflow is required; activate the MetaPathways environment.') + if resources['executor'] == 'slurm': + missing = [c for c in ('sbatch', 'squeue', 'scancel') if not shutil.which(c)] + if missing: + raise RuntimeError('Run from your Slurm login node; missing commands: ' + ', '.join(missing)) + session = scratch / 'session' + session.mkdir(parents=True) + work.mkdir(parents=True, exist_ok=True) + cache.mkdir(parents=True, exist_ok=True) + env = os.environ.copy() + env.update(NXF_ANSI_LOG='false', PYTHONUNBUFFERED='1', + NXF_CONDA_CACHEDIR=str(cache / 'envs'), CONDA_PKGS_DIRS=str(cache / 'packages')) + # Isolate resource limits from ambient ~/.nextflow/config overrides. + command = [executable, '-C', str(config), '-log', str(run_dir / 'nextflow.log'), + 'run', str(nf), '-work-dir', str(work), + '-with-trace', str(run_dir / 'trace.tsv'), '-with-report', str(run_dir / 'report.html'), + '-with-timeline', str(run_dir / 'timeline.html')] + print(f"MetaPathways: {name}; executor={resources['executor']}; CPU budget={resources['max_cpus']}; task limit={resources['max_tasks']}", flush=True) + print(f'Logs and resource reports: {run_dir}', flush=True) + interrupted = False + try: + with (run_dir / 'console.log').open('w') as console: + stream_run(command, session, env, tasks, console) + summary['status'] = 'SUCCESS' + except BaseException as exc: + interrupted = isinstance(exc, (KeyboardInterrupt, SystemExit)) + summary['status'] = 'INTERRUPTED' if interrupted else 'FAILED' + summary['error'] = str(exc) + raise + finally: + records = [] + for t in tasks: + receipt = Path(t['invocation_receipt']) + if receipt.exists(): + record = json.loads(receipt.read_text()) + record['label'] = t['label'] + records.append(record) + else: + records.append(dict(task=t['id'], label=t['label'], status='NOT_STARTED')) + for t, record in zip(tasks, records): + for key in ('sample', 'entity'): + if key in t: + record[key] = t[key] + summary['tasks'] = records + # Preserve wrapper diagnostics even for scheduler/bootstrap failures + # before a worker could open its own log. + for path in work.rglob('.command.*'): + if path.is_file(): + target = run_dir / 'nextflow_tasks' / path.relative_to(work) + target.parent.mkdir(parents=True, exist_ok=True) + shutil.copy2(path, target) + summary_path.write_text(json.dumps(summary, indent=2) + '\n') + if not getattr(args, 'keep_work', False) and not interrupted: + shutil.rmtree(scratch) + else: + print(f'Work/cache retained: {scratch}', flush=True) + failed = [r['label'] for r in records if r.get('status') == 'FAILED'] + if failed: + print(f'Completed with {len(failed)} optional PGDB failures: ' + ', '.join(failed)) + print(f'Finished {name}. Logs: {run_dir}', flush=True) + return run_dir + + +def annotation_tasks(samples, params, configs, memory_value): + from metapathways import jobscreator + creator = jobscreator.JobCreator(params, configs) + threaded = {'ORF_PREDICTION', 'FUNC_SEARCH', 'SCAN_rRNA', 'SCAN_tRNA', 'COMPUTE_TPM'} + tasks = [] + for key in sorted(samples): + s = samples[key] + creator.addJobs(s, block_mode=True) + s.writeParamsToRunLogs(type('Parameters', (), {'params': params})()) + previous, group_ids, last_group = [], [], None + for block, contexts in enumerate(s.getContextBlocks()): + for i, c in enumerate(contexts): + group = c.name if c.name == 'SCAN_rRNA:barrnap' else c.name.split(':')[0] + if group != last_group: + previous, group_ids, last_group = group_ids, [], group + identifier = f'{s.sample_name}:{block}:{i}:{c.name}' + t = task(identifier, f'{s.sample_name}:{c.name}', c.commands, + c.inputs.values(), c.outputs.values(), previous, + int(configs['NUM_CPUS']) if c.name.split(':')[0] in threaded else 1, + memory_value, kind='annotation', context=vars(c), + sample_output=s.output_dir, sample=s.sample_name, block=block) + t['status'] = c.status + t['adopt_existing'] = c.name != 'COMPUTE_TPM' + if c.name.startswith('FUNC_SEARCH:') or c.name == 'COMPUTE_REFSCORES': + t['cache_version'] = 'private-fast-scratch-v1' + t['adopt_existing'] = False + if c.name == 'PATHOLOGIC_INPUT': + t['cache_version'] = 'normalized-ec-input-v1' + t['adopt_existing'] = False + if c.name == 'COMPUTE_TPM': + # bwaFolder is a destination for this task's intermediate + # BAM/count files, not a biological input. Fingerprinting + # it makes a successful run invalidate its own receipt. + t['inputs'] = [value for name, value in c.inputs.items() + if name != 'bwaFolder'] + if c.temps.get('rev_fq'): + t['inputs'].append(c.temps['rev_fq']) + # Auxiliary inputs affect resumability but may be optional references. + t['fingerprint_inputs'] = t['inputs'] + list(getattr(c, 'inputs1', {}).values()) + list(getattr(c, 'inputs_optional', {}).values()) + if c.name.startswith('FUNC_SEARCH:'): + db = c.name.split(':', 1)[1] + t['fingerprint_inputs'].append(str(Path(configs['REFDBS']) / 'functional/formatted' / db) + '.*') + if c.name.startswith('SCAN_rRNA:') and c.name != 'SCAN_rRNA:barrnap': + t['fingerprint_inputs'].append(c.inputs1['dbpath'] + '.*') + if c.name == 'PATHOLOGIC_INPUT': + t['outputs'] += [str(Path(s.output_dir) / 'ptools/0.pf'), str(Path(s.output_dir) / 'ptools/orf_map.txt'), + str(Path(s.output_dir) / 'results/annotation_table' / f'{s.sample_name}.EC_RXN_map.tsv')] + if c.name == 'CREATE_ANNOT_REPORTS': + t['outputs'].append(str(Path(s.output_dir) / 'results/annotation_table' / f'{s.sample_name}.ORF_annotation_table.txt')) + t['outputs'] = [p for p in t['outputs'] if not Path(p).is_dir()] + + # Read abundance is optional, not a missing-input failure. + if c.name == 'COMPUTE_TPM' and not c.inputs.get('fwd_fq'): + t['status'] = 'skip' + if c.name == 'COMPUTE_TPM': + t['outputs'] += [str(Path(s.output_dir) / 'results/rpkm' / f'{s.sample_name}.contig_counts.tsv'), + str(Path(s.output_dir) / 'results/rpkm' / f'{s.sample_name}.orf_counts.tsv')] + tasks.append(t) + group_ids.append(identifier) + # Some legacy stages intentionally update an earlier stage's output (GBK). + # The final producer owns its fingerprint; earlier stages still require it. + owner = {p: t['id'] for t in tasks for p in t['outputs']} + for t in tasks: + t['cache_outputs'] = [p for p in t['outputs'] if owner[p] == t['id']] + return tasks diff --git a/metapathways/nf_databases.py b/metapathways/nf_databases.py new file mode 100644 index 0000000..f189a02 --- /dev/null +++ b/metapathways/nf_databases.py @@ -0,0 +1,132 @@ +"""Database preparation DAG for the public build_db command (no Snakemake).""" +from pathlib import Path +import shlex +import sys +from metapathways.nextflow import task + + +def metacyc_task(root, source, aligner, memory='16 GB', dependencies=()): + """Shared by explicit build_db selection and the build_pt dependent export.""" + from metapathways.metacyc_db import TABLES + root, source = Path(root).expanduser().resolve(), Path(source).expanduser().resolve() + ext = '.prj' if aligner == 'fast' else '.pdb' + outputs = [root/'functional/metacyc', root/('functional/formatted/metacyc'+ext), + root/'functional/formatted/metacyc-names.txt', + root/'functional_categories/MetaCyc_provenance.json', root/'functional_categories/MetaCyc_reldate.txt'] + outputs.extend(root/'functional_categories'/name for name in TABLES) + command = shlex.join([sys.executable, '-m', 'metapathways.metacyc_db', '--source', str(source), + '--output', str(root), '--aligner', aligner]) + return task('prepare_metacyc', 'Prepare licensed MetaCyc reference', [command], [str(source)], + list(map(str, outputs)), dependencies, memory=memory, adopt_existing=False, + cache_outputs=[str(root/'functional/formatted/metacyc.*')]) + + +def plan(root, databases, aligner, test=False, memory='16 GB', metacyc_source=None): + root = Path(root).resolve() + scripts = Path(__file__).parent / 'build_DBs' + q = lambda p: shlex.quote(str(p)) + python = q(sys.executable) + tasks = [] + dirs = ['functional/formatted', 'functional_categories', 'ncbi_tree', 'taxonomic/formatted', '.metapathways'] + ready = root / '.metapathways/database-directories.ready' + tasks.append(task('directories', 'Prepare database directories', + ['mkdir -p ' + ' '.join(q(root/d) for d in dirs) + f'; test -e {q(ready)} || touch {q(ready)}'], outputs=[str(ready)], memory=memory)) + # Recreate missing directories without changing the download dependency timestamp. + tasks[-1]['status'] = 'redo' + + def add(identifier, commands, inputs, outputs, deps): + tasks.append(task(identifier, identifier, commands, map(str, inputs), map(str, outputs), deps, memory=memory)) + if identifier.startswith('index_'): + # Track every index shard so removal of a non-sentinel file invalidates reuse. + prefix = str(tasks[-1]['outputs'][0]).rsplit('.', 1)[0] + tasks[-1]['cache_outputs'] = [prefix + '.*'] + tasks[-1]['adopt_existing'] = False + return identifier + + def fetch(identifier, url, dest, compressed=False): + dest = Path(dest) + download = str(dest) + '.download' + command = f'wget -O {q(download)} {q(url)}\n' + if compressed: + command += f'gzip -dc {q(download)} > {q(str(dest)+".tmp")}\nmv {q(str(dest)+".tmp")} {q(dest)}\nrm {q(download)}' + else: + command += f'mv {q(download)} {q(dest)}' + return add(identifier, [command], [ready], [dest], ['directories']) + + if 'metacyc' in databases: + from metapathways.metacyc_db import source_path + from metapathways.pt_container import registered_image + source = metacyc_source or registered_image() + if not source: + raise ValueError('MetaCyc requires a licensed source: run build_pt first, or provide --metacyc_source with a complete data directory or SIF. See README.md: MetaCyc from Pathway Tools.') + source = source_path(source) + tasks.append(metacyc_task(root, source, aligner, memory, ['directories'])) + databases = [db for db in databases if db != 'metacyc'] + if not databases: + # Adding MetaCyc to an existing MPDB must not refresh unrelated references. + return tasks + + silvas = ['SILVA_LSU_test', 'SILVA_SSU_test'] if test else [ + 'SILVA_138.1_LSURef_NR99_tax_silva_trunc', 'SILVA_138.1_SSURef_NR99_tax_silva_trunc'] + for db in silvas: + fasta, prefix = root/'taxonomic'/db, root/'taxonomic/formatted'/db + deps = ['directories'] + if not test: + deps = [fetch('fetch_'+db, f'https://www.arb-silva.de/fileadmin/silva_databases/release_138_1/Exports/{db}.fasta.gz', fasta, True)] + add('index_'+db, [f'makeblastdb -in {q(fasta)} -dbtype nucl -parse_seqids -out {q(prefix)}'], + [fasta], [str(prefix)+'.ndb'], deps) + add('names_'+db, [f"grep '^>' {q(fasta)} > {q(str(prefix)+'-names.txt')}"], [fasta], [str(prefix)+'-names.txt'], deps) + + if not test: + note = root/'functional_categories/SILVA_reldate.txt' + add('release_silva', [f'date -u > {q(note)}\nprintf "Release: 138.1\\n" >> {q(note)}'], + [], [note], ['fetch_'+db for db in silvas]) + + ec = root/'functional_categories/enzyme.dat' + ec_dep = fetch('fetch_enzyme', 'https://ftp.expasy.org/databases/enzyme/enzyme.dat', ec) + ec_note = root/'functional_categories/Expasy_reldate.txt' + add('enzyme_release', [f'wget -O {q(str(ec_note)+".tmp")} https://ftp.expasy.org/databases/enzyme/enzclass.txt\n' + f'date -u > {q(ec_note)}\ngrep "^Release:" {q(str(ec_note)+".tmp")} >> {q(ec_note)}\nrm {q(str(ec_note)+".tmp")}'], + [ec], [ec_note], [ec_dep]) + tax_archive = root/'ncbi_tree/new_taxdump.tar.gz' + tax_dep = fetch('fetch_taxonomy', 'https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/new_taxdump/new_taxdump.tar.gz', tax_archive) + add('taxonomy_tree', [f'tar xzf {q(tax_archive)} -C {q(root/"ncbi_tree")}\n{python} {q(scripts/"taxmap_build.py")} {q(root/"ncbi_tree")}'], + [tax_archive], [root/'ncbi_tree/ncbi_taxonomy_tree.txt'], [tax_dep]) + unirefs = [db for db in databases if db in ('uniref50', 'uniref90')] + if unirefs: + idmap = root/'functional_categories/idmapping.dat.gz' + idmap_dep = fetch('fetch_idmapping', 'https://ftp.ebi.ac.uk/pub/databases/uniprot/current_release/knowledgebase/idmapping/idmapping.dat.gz', idmap) + for db in databases: + fasta, prefix = root/'functional'/db, root/'functional/formatted'/db + deps = ['directories'] + if not test: + if db == 'swissprot': + url = 'https://ftp.ebi.ac.uk/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot.fasta.gz' + deps = [fetch('fetch_'+db, url, fasta, True)] + fetch('release_'+db, 'https://ftp.ebi.ac.uk/pub/databases/uniprot/current_release/knowledgebase/complete/reldate.txt', root/'functional_categories/SwissProt_reldate.txt') + elif db in unirefs: + url = f'https://ftp.ebi.ac.uk/pub/databases/uniprot/uniref/{db}/{db}.fasta.gz' + deps = [fetch('fetch_'+db, url, fasta, True)] + fetch('release_'+db, f'https://ftp.ebi.ac.uk/pub/databases/uniprot/uniref/{db}/{db}.release_note', root/f'functional_categories/{db}_reldate.txt') + elif db == 'cazy': + deps = [fetch('fetch_cazy', 'https://bcb.unl.edu/dbCAN2/download/Databases/V12/CAZyDB.07262023.fa', fasta)] + note = root/'functional_categories/CAZyDB_reldate.txt' + add('release_cazy', [f'date -u > {q(note)}\nprintf "Release: V12_07262023\\n" >> {q(note)}'], + [fasta], [note], deps) + elif db == 'eggnog' and not fasta.is_file(): + raise ValueError(f'Provide the eggNOG protein FASTA at {fasta}; the previous database builder did not define an eggNOG download source.') + ext = '.pdb' if aligner == 'blast' else '.prj' + cmd = (f'makeblastdb -in {q(fasta)} -dbtype prot -parse_seqids -out {q(prefix)}' if aligner == 'blast' + else f'fastdb -p {q(prefix)} {q(fasta)}') + add('index_'+db, [cmd], [fasta], [str(prefix)+ext], deps) + add('names_'+db, [f"grep '^>' {q(fasta)} > {q(str(prefix)+'-names.txt')}"], [fasta], [str(prefix)+'-names.txt'], deps) + if db in ('swissprot', 'swissprot_test'): + add('ec_'+db, [f'{python} {q(scripts/(db+"_mapper.py"))} {q(ec)} {q(root/"functional_categories")}'], + [fasta, ec], [root/f'functional_categories/EC_map.{db}.tsv'], deps+[ec_dep]) + elif db in unirefs: + filtered = root/f'functional_categories/{db}_idmapping.dat' + # A shared download feeds independent maps; no concurrent overwrites. + add('ec_'+db, [f"gzip -dc {q(idmap)} | grep {q('UniRef'+db[6:]+'_')} > {q(filtered)}\n" + f'{python} {q(scripts/(db+"_mapper.py"))} {q(ec)} {q(root/"functional_categories")}'], + [fasta, ec, idmap], [root/f'functional_categories/EC_map.{db}.tsv'], deps+[ec_dep, idmap_dep]) + return tasks diff --git a/metapathways/nf_worker.py b/metapathways/nf_worker.py new file mode 100644 index 0000000..623cedc --- /dev/null +++ b/metapathways/nf_worker.py @@ -0,0 +1,165 @@ +"""Execute one planned task; preserve MP outputs and check resumability.""" +import glob +import fcntl +import hashlib +import json +import os +from pathlib import Path +import subprocess +import sys +import time +import traceback + + +def fingerprint(paths): + result = [] + for value in paths: + if not value: + result.append([value, None]) + continue + matches = sorted(glob.glob(str(value))) or [str(value)] + for name in matches: + p = Path(name) + if not p.exists() and Path(name + '.gz').exists(): + p = Path(name + '.gz') + if p.exists(): + st = p.stat() + result.append([str(p), st.st_size, st.st_mtime_ns]) + if p.is_dir(): + # A directory mtime alone does not detect edits to its files. + for child in sorted(p.rglob('*')): + if child.is_file(): + st = child.stat() + result.append([str(child), st.st_size, st.st_mtime_ns]) + else: + result.append([str(p), None]) + return result + + +def available(paths): + return bool(paths) and all(value and (Path(value).exists() or Path(str(value)+'.gz').exists()) for value in paths) + + +def atomic_json(p, obj): + p = Path(p) + p.parent.mkdir(parents=True, exist_ok=True) + temp = p.with_suffix('.tmp') + temp.write_text(json.dumps(obj, indent=2) + '\n') + temp.replace(p) + + +def execute(t): + print(f"Starting {t['label']} (cpus={t['cpus']}, memory={t['memory']})", flush=True) + start = time.monotonic() + receipt_path = Path(t['receipt']) + previous = json.loads(receipt_path.read_text()) if receipt_path.exists() else None + signature_data = {k: t.get(k) for k in ['commands', 'context', 'cpus', 'kind']} + if 'cache_version' in t: + signature_data['cache_version'] = t['cache_version'] + if signature_data['context']: + signature_data['context'] = {k: v for k, v in signature_data['context'].items() if k not in ('status', 'message')} + signature = hashlib.sha256(json.dumps(signature_data, sort_keys=True).encode()).hexdigest() + input_state = fingerprint(t.get('fingerprint_inputs', t['inputs'])) + output_state = fingerprint(t.get('cache_outputs', t['outputs'])) + status = 'FAILED' + error = '' + def log(status, duration): + if t.get('kind') == 'annotation': + p = Path(t['sample_output']) / 'metapathways_steps_log.txt' + with p.open('a') as f: + f.write(f"{t['context']['name']}\t{status} - Time elapsed: {duration:.2f} seconds\n") + try: + if t['status'] == 'skip' or (t.get('skip_if_missing') and not Path(t['skip_if_missing']).is_file()): + status = 'SKIPPED' + elif (t['status'] != 'redo' and available(t['outputs']) and + ((previous and previous['status'] == 'SUCCESS' and previous['signature'] == signature + and previous['inputs'] == input_state and previous['outputs'] == output_state) + or (previous is None and t.get('adopt_existing', True)))): + status = 'ALREADY_COMPUTED' + else: + if any(not value or (not glob.glob(str(value)) and not Path(str(value)+'.gz').exists()) for value in t['inputs']): + raise RuntimeError(f"Missing required input: {t['inputs']}") + # Invalidate the previous success before touching outputs, even if killed. + atomic_json(receipt_path, dict(status='RUNNING')) + for command in t['commands']: + print('Command: ' + command, flush=True) + if t.get('kind') == 'annotation': + from types import SimpleNamespace + from metapathways.context import Context + from metapathways.metapathways_utils import WorkflowLogger + from metapathways.execution import execute as run_stage + c = Context() + c.__dict__.update(t['context']) + c.removeOutput() + base = Path(t['sample_output']) + s = SimpleNamespace(errorlogger=WorkflowLogger(str(base/'errors_warnings_log.txt'), open_mode='a'), + runstatslogger=WorkflowLogger(str(base/'run_statistics'/f"{t['sample']}.run.stats.txt"), open_mode='a')) + result = run_stage(s, c) + if result is None or result[0] != 0: + raise RuntimeError(f'Stage failed: {result}') + else: + for cmd in t['commands']: + subprocess.run(['bash', '-euo', 'pipefail', '-c', cmd], check=True) + if not available(t['outputs']): + raise RuntimeError(f"Task did not produce expected outputs: {t['outputs']}") + status = 'SUCCESS' + except Exception as exc: + error = str(exc) + traceback.print_exc() + duration = time.monotonic() - start + log(status, duration) + record = dict(task=t['id'], status=status, elapsed_seconds=duration, signature=signature, + inputs=input_state, outputs=fingerprint(t.get('cache_outputs', t['outputs'])), error=error) + # Preserve the cache's SUCCESS on a cache hit; record this invocation separately. + if status != 'SKIPPED': + saved = dict(record, status='SUCCESS' if status == 'ALREADY_COMPUTED' else status) + atomic_json(receipt_path, saved) + atomic_json('receipt.json', record) + if t.get('invocation_receipt'): + atomic_json(t['invocation_receipt'], record) + print(f"{t['label']}: {status} ({duration:.2f}s)", flush=True) + if status == 'FAILED' and not t.get('allow_failure', False): + return 1 + if status == 'FAILED': + print(f"Optional-entity task failed; inspect its diagnostics: {t['label']}: {error}", file=sys.stderr) + return 0 + + +def main(argv=None): + argv = list(sys.argv[1:] if argv is None else argv) + direct = argv and argv[0] == '--execute' + if direct: + argv.pop(0) + manifest, identifier = argv + tasks = json.loads(Path(manifest).read_text()) + t = next(t for t in tasks if t['id'] == identifier) + if direct: + if t.get('host_serial'): + with open(f'/tmp/metapathways-ptools-{os.getuid()}.lock', 'a') as lock: + fcntl.flock(lock, fcntl.LOCK_EX) + return execute(t) + return execute(t) + logfile = Path(t['log']) + logfile.parent.mkdir(parents=True, exist_ok=True) + env = os.environ.copy() + env["METAPATHWAYS_STREAM_TOOLS"] = "1" + # Prevent hidden BLAS/OpenMP pools from exceeding the scheduled CPU request. + for key in ('OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS'): + env[key] = str(t['cpus']) + with logfile.open('w') as log: + process = subprocess.Popen([sys.executable, '-u', '-m', 'metapathways.nf_worker', + '--execute', manifest, identifier], env=env, + stdout=subprocess.PIPE, stderr=subprocess.STDOUT, + text=True, errors='replace', bufsize=1) + try: + for line in process.stdout: + log.write(line) + log.flush() + print(line, end='', flush=True) + return process.wait() + finally: + process.stdout.close() + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/metapathways/pipeline.py b/metapathways/pipeline.py index cc7d661..0fa1c39 100755 --- a/metapathways/pipeline.py +++ b/metapathways/pipeline.py @@ -27,6 +27,7 @@ from metapathways import sampledata as sampledata from metapathways import general_utils as gutils from metapathways import _version + from metapathways import nextflow except: print("""Could not load some user defined module functions""") print(traceback.print_exc(10)) @@ -58,14 +59,14 @@ -def runParser(): +def runParser(command='run'): parser = argparse.ArgumentParser(description='MetaPathways command-line tool for annotation of contigs.') subparsers = parser.add_subparsers(dest="command") run_parser = subparsers.add_parser( - 'run', + command, description='Minimum REQUIRED Command:\n' 'MetaPathways run -i INPUT_FILE -o OUTPUT_DIR -d REFDB_DIR\n\n', - usage='Metapathways run [options]', formatter_class=argparse.RawTextHelpFormatter) + usage=f'Metapathways {command} [options]', formatter_class=argparse.RawTextHelpFormatter) # Minimum required args req_args = run_parser.add_argument_group('Minimum Required Arguments') @@ -171,12 +172,15 @@ def runParser(): pipe_args.add_argument('--force_redo', action="store_true", default=False, help="Redo all steps [False]") + nextflow.add_resources(run_parser) + run_parser.add_argument('--dryrun', action='store_true', help='show the execution plan without running tasks') + # Other arguments misc_args = run_parser.add_argument_group('Miscellaneous Arguments') misc_args.add_argument("-s", "--samples", nargs='+', action="append", default=[], help="process only specific samples, space-separated list") - misc_args.add_argument("-t", "--threads", default=1, type=int, - help="max number of cores to use in multithreaded steps [1]") + misc_args.add_argument("-t", "--threads", default=8, type=nextflow.positive, + help="threads per capable tool [8], capped by --max_cpus; serial stages use one CPU") misc_args.add_argument("-v", "--verbose", action="store_true", default=False, help="print more information on the stdout") misc_args.add_argument("--test", action="store_true", help="use test values for all arguments") @@ -198,6 +202,7 @@ def msParser(): mag_parser.add_argument("-m", "--contig_mag_map", dest="mag_map", required=True, help="TSV file that contains contig-to-MAG mapping [REQUIRED]") + nextflow.add_resources(mag_parser) return parser @@ -218,6 +223,13 @@ def ptParser(): help="Flag only used in containerized env [special flag]") ptools_parser.add_argument('--taxprune', action="store_true", dest="taxprune", default=False, help='Set taxonomic pruning in pathway tools to True') + from metapathways.pt_taxonomy import add_taxonomy_options + add_taxonomy_options(ptools_parser) + ptools_parser.add_argument('--no_transport_inference', action='store_true', help='Disable TIP transport inference (SIF only)') + ptools_parser.add_argument('--entity', help='Build only community or the specified MAG ID') + ptools_parser.add_argument('--image', help='Pathway Tools SIF [registered by build_pt]') + from metapathways.nextflow import add_resources + add_resources(ptools_parser, task_memory='4 GB') return parser @@ -230,17 +242,19 @@ def blParser(DBS_FUNC, DBS_FUNC_DEFAULT, ALIGNERS): help=f"functional references, select any combination from {DBS_FUNC}, [DEFAULT {DBS_FUNC_DEFAULT}]") db.add_argument("-a", "--aligner", required=False, default="fast", help=f"local aligner to index for, select one of {ALIGNERS}, [DEFAULT fast]") + db.add_argument('--metacyc_source', help='licensed MetaCyc data directory or Pathway Tools SIF [registered SIF when --func includes metacyc]') # "options" group - parser.add_argument("-t", "--threads", metavar="INT", type=int, required=False, default=1, - help="max number of cores to use in multithreaded steps [1]") + parser.add_argument("-t", "--threads", metavar="INT", type=nextflow.positive, required=False, default=None, + help="total database-build CPU budget [available CPUs]") parser.add_argument("--dryrun", action="store_true", default=False, required=False, - help="dry run snakemake") + help="show the database execution plan without running tasks") parser.add_argument("--snakemake", nargs='*', required=False, default=[], - help="additional snakemake cli args in the form of KEY=\"VALUE\" or KEY (no leading dashes)") + help="legacy compatibility flags; use the resource flags for new runs") parser.add_argument("--test", action="store_true", help="use test values for all arguments") + nextflow.add_resources(parser) return parser @@ -284,7 +298,7 @@ def check_for_error_in_input_file_name(shortname, globalerrorlogger=None): gutils.eprintf("ERROR\t%s\n",errmessage) if globalerrorlogger: globalerrorlogger.printf("ERROR\t%s\n",errmessage) - mputils.exit_process() + raise ValueError(errmessage) return False @@ -399,10 +413,15 @@ def create_arg_dict(parser): def run(): argv = sys.argv - gutils.eprintf("%-10s:%s\n" % ('COMMAND', ' '.join(argv))) parser = runParser() args = parser.parse_args() - # Check for the --test flag and set test values if present + tasks, output_dir = prepare_annotation(args, parser) + nextflow.launch(tasks, output_dir, args, 'run', dryrun=args.dryrun) + print('MetaPathways processing complete.') + + +def prepare_annotation(args, parser): + # Shared planner: creates tasks without starting any tools. if args.test: args.refdb_dir = str(pathlib.Path(path.abspath(__file__)).parent.joinpath("regtests/test_db")) args.rRNA_refdbs = ["SILVA_SSU_test", "SILVA_LSU_test"] @@ -427,6 +446,12 @@ def run(): elif args.refdb_dir == None: parser.error(f"Reference DB is a required argument: \"-d\", \"--refdb_dir\"") + for key in ('input_file', 'output_dir', 'refdb_dir', 'fwd_fastq', 'rev_fastq'): + value = getattr(args, key, None) + if value and value != 'None': + setattr(args, key, str(pathlib.Path(value).expanduser().absolute())) + budget = args.max_cpus or (32 if args.executor == 'slurm' else nextflow.local_capacity()[0]) + args.threads = min(args.threads, budget) if args.force_redo: steps_list = ['PREPROCESS_INPUT', 'ORF_PREDICTION', 'FILTER_AMINOS', 'SCAN_rRNA', 'SCAN_tRNA', 'FUNC_SEARCH', 'PARSE_FUNC_SEARCH', 'ANNOTATE_ORFS', @@ -461,8 +486,8 @@ def run(): """ load the sample inputs it expects either a fasta file or a directory containing fasta and yaml file pairs """ - print("output dir", output_dir) - globalerrorlogger = mputils.WorkflowLogger(mputils.generate_log_fp(output_dir, basefile_name = 'global_errors_warnings'), open_mode='w') + print(f"Output directory: {output_dir}") + globalerrorlogger = mputils.WorkflowLogger(mputils.generate_log_fp(output_dir, basefile_name = 'global_errors_warnings'), open_mode='a') input_output_list = {} if path.isfile(input_fp): """ check if it is a file """ @@ -475,7 +500,7 @@ def run(): """ must be an error """ gutils.eprintf("ERROR\tNo valid input sample file or directory containing samples exists .!") gutils.eprintf("ERROR\tAs provided as arguments in the -in option.!\n") - mputils.exit_process("ERROR\tAs provided as arguments in the -in option.!\n") + parser.error(f'Input path does not exist: {input_fp}') """ these are the subset of sample to process if specified in case of an empty subset process all the sample """ @@ -489,7 +514,7 @@ def run(): #stop on invalid samples if not halt_on_invalid_input(input_output_list, filetypes, sample_subset): - globalerrorlogger.printf("ERROR\tInvalid inputs found. Check for file with bad format or characters!\n") + parser.error('Invalid input sequence format; see the error log.') # make sure the sample files are found report_missing_filenames(input_output_list, sample_subset, logger=globalerrorlogger) @@ -501,7 +526,7 @@ def run(): if not diagnoze.staticDiagnose(params, config, logger = globalerrorlogger): gutils.eprintf("ERROR\tFailed to pass the test for required scripts and inputs before run\n") globalerrorlogger.printf("ERROR\tFailed to pass the test for required scripts and inputs before run\n") - return + parser.exit(1, "Input or dependency checks failed; see the error log.\n") samplesData = {} # PART1 before the blast @@ -566,43 +591,24 @@ def run(): s.prepareToRun() samplesData[input_file] = s - # load the sample information - mpsteps.run_metapathways( - samplesData, - sample_output_dir, - output_dir, - globallogger = globalerrorlogger, - command_line_params = command_line_params, - params = params, - status_update_callback = status_update_callback, - config_settings = configs, - run_type = run_type, - block_mode = block_mode - ) + tasks = nextflow.annotation_tasks(samplesData, params, configs, args.memory) + return tasks, output_dir else: gutils.eprintf("ERROR\tNo valid input files/Or no files specified to process in folder %s!\n",gutils.sQuote(input_fp) ) - globalerrorlogger.printf("ERROR\tNo valid input files to process in folder %s!\n",gutils.sQuote(input_fp) ) - - except: - mputils.exit_process(str(traceback.format_exc(10)), logger= globalerrorlogger ) + raise ValueError(f'No valid inputs in {input_fp}') + except Exception as exc: + parser.exit(1, f"MetaPathways run failed: {exc}\n") - gutils.eprintf(" *********** \n") - gutils.eprintf("INFO : FINISHED PROCESSING THE SAMPLES \n") - gutils.eprintf(" THE END \n") - gutils.eprintf(" *********** \n") - def build_db(): argv = sys.argv - gutils.eprintf("%-10s:%s\n" % ('COMMAND', ' '.join(argv))) - DBS_FUNC = "swissprot cazy eggnog uniref50 uniref90".split(" ") + DBS_FUNC = "swissprot cazy eggnog uniref50 uniref90 metacyc".split(" ") DBS_FUNC_DEFAULT = "swissprot".split(" ") ALIGNERS = "fast blast".split(" ") parser = blParser(DBS_FUNC, DBS_FUNC_DEFAULT, ALIGNERS) args = parser.parse_args(argv[2:]) - build_dbs_src = pathlib.Path(path.abspath(__file__)).parent.joinpath("build_DBs") # Check for the --test flag and set test values if present if args.test: @@ -610,7 +616,7 @@ def build_db(): args.func = ["swissprot_test"] args.aligner = "fast" args.threads = 1 - snakefile = f"""{build_dbs_src}/Snakefile_test""" + # Set required arguments to False when --test is used for action in parser._actions: @@ -619,7 +625,7 @@ def build_db(): # Validate required arguments if --test is not used else: - snakefile = f"""{build_dbs_src}/Snakefile""" + missing_required = [] for action in parser._actions: if action.required and getattr(args, action.dest, None) is None: @@ -652,90 +658,36 @@ def _error(message: str): if input_error: sys.exit(1) - # --------------------------------------------------------------------------- - # setup folders, params, and wget passwords for snakemake - - ref_db_dir = pathlib.Path(args.refdb_dir).absolute() - if not ref_db_dir.exists(): makedirs(ref_db_dir) - smk_temp_dir = ref_db_dir.joinpath("temp_cache") - - smk_args = [ - "--latency-wait 0", - "--keep-going", - "--rerun-incomplete", - ] - if args.dryrun: smk_args.append("--dryrun") - for smk_arg in args.snakemake: - if "=" in smk_arg: - smk_arg_tokens = smk_arg.split("=") - parsed_smk_arg = f"--{smk_arg_tokens[0]} {'='.join(smk_arg_tokens[1:])}" - else: - parsed_smk_arg = f"--{smk_arg}" - smk_args.append(parsed_smk_arg) - - smk_config = dict( - ref_db_dir=ref_db_dir, - script_path=build_dbs_src, - aligner=alinger, - functional_db_names=','.join(selected_dbs_functional) - ) - - #if "metacyc" in selected_dbs_functional: - # gutils.eprintf("Your selected database type requires a MetaCyc download...\n") - # # Get the username and password securely - # metacyc_user = input("Enter your MetaCyc username: ") - # metacyc_pswd = getpass.getpass("Enter your MetaCyc password: ") - # add_netrc_entry("brg-files.ai.sri.com", f"{metacyc_user}", f"{metacyc_pswd}") - - # --------------------------------------------------------------------------- - # run snakemake - - # set $XDG_CACHE_HOME so that snakemake doesn't polute $HOME - cmd = f"""\ - mkdir -p {smk_temp_dir} - export XDG_CACHE_HOME={smk_temp_dir} - snakemake -p -s "{snakefile}" \ - -d {ref_db_dir} \ - --cores {args.threads} \ - --config {' '.join([f'{k}="{v}"' for k, v in smk_config.items()])} \ - {' '.join(smk_args)} \ - && rm -r {smk_temp_dir} - """ - cmd = " ".join(l for l in cmd.split(" ") if l != "").strip() # remove indetation - gutils.eprintf("-"*30+"\n") - gutils.eprintf(cmd) - gutils.eprintf("\n"+"-"*30+"\n") - system(cmd) - -def add_netrc_entry(machine, login, password): - # Get the user's home directory - home_directory = path.expanduser("~") - - # Define the path to the .netrc file - netrc_path = path.join(home_directory, ".netrc") - - # todo: overwrite previous, otherwise may be stuck with wrong password - # Check if the .netrc file already exists - if path.exists(netrc_path): - # Read the existing .netrc file - with open(netrc_path, 'r') as netrc_file: - existing_entries = netrc_file.read() - # Check if an entry for the specified machine already exists - if f"machine {machine}" in existing_entries: - print(f"An entry for '{machine}' already exists in .netrc. Not adding a duplicate entry.") - return - - # If it doesn't exist or the entry doesn't exist, open the .netrc file in append mode - with open(netrc_path, 'a') as netrc_file: - # Write the new entry to the file - netrc_file.write(f"machine {machine}\n") - netrc_file.write(f"login {login}\n") - netrc_file.write(f"password {password}\n") + from metapathways.nf_databases import plan + # Preserve the old build_db -t total-core limit, while run -t controls searches. + if args.max_cpus is None and args.threads is not None: + args.max_cpus = args.threads + force = False + for item in args.snakemake: + key, _, value = item.partition('=') + if key in ('cores', 'jobs') and value: + args.max_cpus = nextflow.positive(value) + elif key in ('dryrun', 'dry-run'): + args.dryrun = True + elif key == 'forceall': + force = True + elif key not in ('keep-going', 'rerun-incomplete', 'printshellcmds', 'latency-wait'): + parser.error(f'Legacy --snakemake option {key!r} has no supported Nextflow equivalent; use resource flags') + try: + if args.metacyc_source and 'metacyc' not in args.func: + parser.error('--metacyc_source requires --func metacyc (optionally alongside other databases)') + tasks = plan(args.refdb_dir, args.func, args.aligner, test=args.test, memory=args.memory, + metacyc_source=args.metacyc_source) + if force: + for t in tasks: + t['status'] = 'redo' + nextflow.launch(tasks, args.refdb_dir, args, 'build_db', dryrun=args.dryrun) + except (ValueError, RuntimeError, OSError, subprocess.CalledProcessError) as exc: + parser.exit(1, f'build_db: {exc}\n') def mag_split(): argv = sys.argv - gutils.eprintf("%-10s:%s\n" % ('COMMAND', ' '.join(argv))) parser = msParser() args = parser.parse_args() @@ -743,6 +695,7 @@ def mag_split(): pf_file = path.join(args.output_dir, 'ptools/0.pf') orf_map = path.join(args.output_dir, 'ptools/orf_map.txt') orf_contig_map = glob.glob(path.join(args.output_dir, 'results/annotation_table/*.ORF_annotation_table.txt'))[0] + feature_table = orf_contig_map.removesuffix('.ORF_annotation_table.txt') + '.ptinput.tsv' contig_map = glob.glob(path.join(args.output_dir, 'preprocessed/*.mapping.txt'))[0] mag_map = args.mag_map ms_outdir = path.join(args.output_dir, 'magsplitter') @@ -754,56 +707,89 @@ def mag_split(): cmd_str = f' magsplitter -p {pf_file} -r {orf_map} -c {orf_contig_map} -m {mag_map} -i {contig_map} -o {ms_outdir}' gutils.eprintf(cmd_str + '\n') - run_command_with_realtime_output(cmd) + import shlex + cmd = [str(pathlib.Path(v).resolve()) if i in (2, 4, 6, 8, 10, 12) else v for i, v in enumerate(cmd)] + saved_map = str(pathlib.Path(ms_outdir).resolve() / 'contig_to_mag.tsv') + copy_map = shlex.join([sys.executable, '-c', 'import shutil,sys; from pathlib import Path; a,b=map(Path,sys.argv[1:]); shutil.copyfile(a,b) if a.resolve()!=b.resolve() else None', str(pathlib.Path(mag_map).resolve()), saved_map]) + tasks = [nextflow.task('mag-split', 'Split annotations into MAGs', [shlex.join(cmd), copy_map], + [str(pathlib.Path(p).resolve()) for p in (pf_file, orf_map, orf_contig_map, mag_map, contig_map, feature_table)], + [str(pathlib.Path(ms_outdir).resolve() / 'results'), saved_map], + cpus=1, memory=args.memory, adopt_existing=False, + cache_version='authoritative-mag-coordinates-v1')] + try: + nextflow.launch(tasks, args.output_dir, args, 'mag_split') + except (ValueError, RuntimeError, OSError, subprocess.CalledProcessError) as exc: + parser.exit(1, f'mag_split: {exc}\n') + def ptools(): argv = sys.argv - gutils.eprintf("%-10s:%s\n" % ('COMMAND', ' '.join(argv))) parser = ptParser() args = parser.parse_args() - if args.tag: - tag = args.tag - else: - tag = path.basename(args.output_dir.rstrip('/')) - cmd = ['pgdb_build_wf.py', '--mp_out', args.output_dir, '--tag', tag] - if args.container: - container = args.container - cmd.append('--container') - if args.taxprune: - taxprune = args.taxprune - cmd.append('--taxprune') - - cmd_str = ' '.join(cmd) - gutils.eprintf("Building ePGDBs:") - gutils.eprintf(cmd_str + '\n') - - run_command_with_realtime_output(cmd) - - -def run_command_with_realtime_output(command): - """Runs a command and prints its output in real-time.""" - process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) - - # Read and print the output as it is produced - while True: - output_bytes = process.stdout.readline() - if output_bytes: - print(output_bytes.decode('utf-8', 'replace').strip()) - else: - break # Exit the loop if no more output - - # Wait for the subprocess to complete - process.wait() - - if process.returncode != 0: - print("\nThe command ended with an error.") - + from metapathways.pt_container import registered_image + from metapathways import nextflow + image = args.image or (None if args.container else registered_image()) + if args.executor == 'slurm' and not image: + parser.error('Slurm Pathway Tools tasks require a SIF; run build_pt or pass --image') + if image: + image = str(pathlib.Path(image).expanduser().resolve()) + if image and not pathlib.Path(image).is_file(): + parser.error(f'Pathway Tools image does not exist: {image}') + output = pathlib.Path(args.output_dir).resolve() + tag = args.tag or output.name + script = shutil.which('pgdb_build_wf.py') + if not script: + candidate = pathlib.Path(__file__).resolve().parent.parent / 'dev/pgdb_build_wf.py' + if not candidate.is_file(): + parser.error('pgdb_build_wf.py is missing; reinstall MetaPathways') + script = str(candidate) + import shlex + tasks = [] + entities = [('community', tag, output / 'ptools', output / 'results/pgdb/community')] + entities += [(p.name, p.name, p, output / 'results/pgdb/MAGs' / p.name) + for p in sorted((output / 'magsplitter/results').glob('*')) + if p.is_dir() and 'non_binned' not in p.name] + if args.no_transport_inference and not image: + parser.error('--no_transport_inference requires a Pathway Tools SIF') + if args.entity: + entities = [entry for entry in entities if entry[0] == args.entity] + if not entities: + parser.error('Unknown PGDB entity: ' + args.entity) + for entity, entity_tag, inputs, results in entities: + cmd = [sys.executable, script, '--mp_out', str(output), '--tag', tag, + '--entity', entity] + if image: + cmd += ['--image', image] + elif args.container: + cmd.append('--container') + if args.taxprune: + cmd.append('--taxprune') + if args.no_transport_inference: + cmd.append('--no_transport_inference') + from metapathways.pt_taxonomy import resolve_taxon + taxon_id = resolve_taxon(args) + if taxon_id is not None: + cmd += ['--taxon_id', str(taxon_id)] + tasks.append(nextflow.task('pgdb-' + entity, entity, [shlex.join(cmd)], + ([image] if image else []) + [str(inputs), str(output / 'results/annotation_table'), + str(output / 'preprocessed' / (output.name + '.fasta'))], + [str(results / (entity_tag + suffix)) for suffix in ('cyc.tar.bz2', '_pwy.tsv', '_pwy2orf.tsv')], + cpus=1, memory=args.memory, allow_failure=entity != 'community', adopt_existing=False, + cache_version='sequence-backed-pgdb-trna-names-v3', host_serial=not bool(image))) + tasks[-1]['fingerprint_inputs'] = tasks[-1]['inputs'] + [str(output / 'orf_prediction' / (output.name + '.cds.gff'))] + if not image: + args.max_tasks = 1 + print('Native Pathway Tools tasks are serialized; build_pt enables isolated parallel runs.') + try: + nextflow.launch(tasks, output, args, 'ptools') + except (ValueError, RuntimeError, OSError, subprocess.CalledProcessError) as exc: + parser.exit(1, f'ptools: {exc}\n') + return def help(): print(f"""\ MetaPathways: v{__version__} - https://metapathways.readthedocs.io https://github.com/hallamlab/MetaPathways Syntax: MetaPathways COMMAND [OPTIONS] @@ -812,9 +798,12 @@ def help(): help version build_db + build_pt run + analysis_wf mag_split ptools + report for addional help, use: MetaPathways COMMAND -h @@ -824,21 +813,73 @@ def version(): print(f"MetaPathways v{__version__}") +def build_pt(): + from metapathways.pt_container import main as build_image + try: + build_image(sys.argv[2:]) + except (ValueError, RuntimeError, OSError, subprocess.CalledProcessError) as exc: + print(f'build_pt: {exc}', file=sys.stderr) + sys.exit(1) + + +def report(): + from metapathways.report_server import main as report_main + report_main(sys.argv[2:]) + + +def analysis_wf(): + from metapathways.analysis_workflow import main as analysis_main + analysis_main(sys.argv[2:]) + + def main(): if len(sys.argv) <= 1: help() return - { - "help": help, - "version": version, - "build_db" : build_db, - "run": run, - "mag_split": mag_split, - "ptools": ptools - }.get( - sys.argv[1], - help # default - )() + command = sys.argv[1] + fn = {'help': help, 'version': version, 'build_db': build_db, 'build_pt': build_pt, + 'run': run, 'analysis_wf': analysis_wf, 'mag_split': mag_split, 'ptools': ptools, 'report': report}.get(command, help) + log_dir = None + if command in ('run', 'analysis_wf', 'mag_split', 'ptools', 'build_db', 'build_pt', 'report') and not any(x in sys.argv for x in ('-h', '--help')): + probe = argparse.ArgumentParser(add_help=False) + probe.add_argument('-o', '--output_dir') + probe.add_argument('-d', '--refdb_dir') + probe.add_argument('--test', action='store_true') + options, _ = probe.parse_known_args(sys.argv[2:]) + log_dir = options.refdb_dir or '.' if command == 'build_db' else options.output_dir + if options.test and command in ('run', 'build_db'): + log_dir = './test' if command == 'run' else pathlib.Path(__file__).parent / 'regtests/test_db' + if command == 'build_pt' and not log_dir: + from metapathways.pt_container import parser as pt_parser + log_dir = pt_parser().get_default('output_dir') + def invoke(): + try: + fn() + if command in ('run', 'analysis_wf', 'mag_split', 'ptools') and log_dir and '--dryrun' not in sys.argv: + from metapathways.reporting import build_report + report_root = pathlib.Path(log_dir).resolve() + parent_report = report_root.parent / 'reports/schema.json' + if parent_report.is_file(): + import json + if str(report_root) in json.loads(parent_report.read_text()).get('sample_paths', []): + report_root = report_root.parent + build_report(report_root) + except (ValueError, RuntimeError, OSError, subprocess.CalledProcessError) as exc: + print(f'MetaPathways: {exc}', file=sys.stderr) + sys.exit(1) + except KeyboardInterrupt: + print('MetaPathways interrupted; see the retained logs and work directory.', file=sys.stderr) + sys.exit(130) + except Exception: + traceback.print_exc() + sys.exit(1) + if log_dir: + from metapathways.cli_logging import transcript + with transcript(log_dir, sys.argv): + invoke() + else: + invoke() + # the main function of metapaths if __name__ == "__main__": diff --git a/metapathways/pt_container.py b/metapathways/pt_container.py new file mode 100644 index 0000000..15c1148 --- /dev/null +++ b/metapathways/pt_container.py @@ -0,0 +1,385 @@ +"""Build and register a private Pathway Tools image from a local installer.""" +import argparse +from datetime import datetime, timezone +import hashlib +from html.parser import HTMLParser +import json +import os +from pathlib import Path +import platform +import re +import shlex +import shutil +import subprocess +import sys +import tempfile +import uuid +from urllib.request import build_opener, HTTPRedirectHandler + +from metapathways import nextflow + + +# Changing the recipe produces a distinct image, even for the same installer. +RECIPE = r'''Bootstrap: docker +From: ubuntu:22.04 + +%files + installer /opt/pt-installer + official-patches /opt/mp-official-patches + +%post + set -eu + export DEBIAN_FRONTEND=noninteractive + apt-get update + apt-get install -y --no-install-recommends ca-certificates xterm openssl libxml2 xvfb xauth libxm4 libssl-dev procps bzip2 ncbi-blast+ + mkdir -p /data /opt/bin + chmod 700 /opt/pt-installer + unset DISPLAY + printf '/opt/pathway-tools\n/data\n\nn\nY\nn\n\n' | /opt/pt-installer + test -x /opt/pathway-tools/pathway-tools + rm /opt/pt-installer + # Install only the unmodified, release-specific vendor files (SRI FAQ 7.4). + pt_version=$(cat /opt/mp-official-patches/version) + patch_dir=/opt/pathway-tools/aic-export/pathway-tools/ptools/$pt_version/patches + test -d "$patch_dir" + set -- "$patch_dir"/bin-* + test "$#" -eq 1 && test -d "$1" + for patch in /opt/mp-official-patches/files/*; do + case "$patch" in + *.fasl) cp "$patch" "$1/" ;; + *) cp "$patch" "$patch_dir/" ;; + esac + done + # Load official patches while the filesystem is still writable. + xvfb-run -a /opt/pathway-tools/pathway-tools -no-patch-download -lisp -eval '(progn (format t "~%MP-PT-READY~%") (exit))' > /opt/mp-pt-patch-startup.log 2>&1 || { cat /opt/mp-pt-patch-startup.log; exit 1; } + cat /opt/mp-pt-patch-startup.log + grep -qx 'MP-PT-READY' /opt/mp-pt-patch-startup.log + printf '[ncbi]\nData=/usr/share/ncbi/data\n' > /opt/mp-ncbirc + test -d /usr/share/ncbi/data + blastp -version + makeblastdb -version + dpkg-query -W ncbi-blast+ > /opt/mp-blast-version.txt + # Keep a pristine template; each invocation mounts its own writable /data. + cp -a /data/ptools-local /opt/ptools-local-template + rm -rf /var/lib/apt/lists/* + +%environment + export PATH=/opt/pathway-tools:$PATH + +%runscript + exec /opt/pathway-tools/pathway-tools "$@" + +%labels + org.metapathways.purpose PathwayTools +''' + + +def digest(path): + h = hashlib.sha256() + with Path(path).open('rb') as f: + for block in iter(lambda: f.read(8 * 1024 * 1024), b''): + h.update(block) + return h.hexdigest() + + +class _NoRedirect(HTTPRedirectHandler): + def redirect_request(self, req, fp, code, msg, headers, newurl): + raise ValueError('Official patch URL redirected; refusing an unverified patch source: ' + newurl) + + +class _PatchLinks(HTMLParser): + def __init__(self): + super().__init__() + self.names = set() + + def handle_starttag(self, tag, attrs): + if tag == 'a': + href = dict(attrs).get('href', '') + # No arbitrary URLs, parent paths, nested directories or query strings. + if re.fullmatch(r'[A-Za-z0-9][A-Za-z0-9_.-]*\.(?:fasl|lisp|tar\.gz)', href): + self.names.add(href) + + +def installer_version(installer, explicit=None): + match = re.search(r'pathway-tools-(\d+\.\d+)', Path(installer).name) + version = explicit or (match.group(1) if match else None) + if not version or not re.fullmatch(r'\d+\.\d+', version): + raise ValueError('Cannot determine Pathway Tools release; use --ptools_version (for example 29.5) for a renamed installer') + if explicit and match and explicit != match.group(1): + raise ValueError('--ptools_version disagrees with the installer filename') + return version + + +def download_patches(version, destination): + """Snapshot SRI's official release feed; never silently use partial downloads.""" + if not re.fullmatch(r'\d+\.\d+', version): + raise ValueError('Invalid Pathway Tools release') + url = f'https://bioinformatics.ai.sri.com/ptools/{version}/Linux-64/patches/' + destination = Path(destination) + files = destination / 'files' + files.mkdir(parents=True) + opener = build_opener(_NoRedirect()) + try: + with opener.open(url, timeout=60) as response: + listing = response.read() + links = _PatchLinks() + links.feed(listing.decode('utf-8')) + if not links.names: + raise ValueError('Vendor listing contained no recognized patch files') + manifest = dict(source=url, version=version, fetched_at=datetime.now(timezone.utc).isoformat(), + listing_sha256=hashlib.sha256(listing).hexdigest(), files=[]) + for name in sorted(links.names): + print('Downloading official Pathway Tools patch: ' + name, flush=True) + target = files / name + with opener.open(url + name, timeout=60) as response, target.open('wb') as stream: + shutil.copyfileobj(response, stream) + if target.stat().st_size == 0: + raise ValueError('Empty patch: ' + name) + manifest['files'].append(dict(name=name, url=url + name, sha256=digest(target))) + manifest['snapshot_sha256'] = hashlib.sha256(json.dumps(manifest['files'], sort_keys=True).encode()).hexdigest() + (destination / 'version').write_text(version + '\n') + (destination / 'index.html').write_bytes(listing) + save_json(destination / 'manifest.json', manifest) + return manifest + except Exception as exc: + raise RuntimeError(f'Official Pathway Tools patches could not be obtained from {url}; build stopped: {exc}') from exc + + +def registry_path(): + return Path(os.environ.get('XDG_CONFIG_HOME', Path.home() / '.config')) / 'metapathways' / 'ptools.json' + + +def registered_image(): + override = os.environ.get('METAPATHWAYS_PTOOLS_IMAGE') + if override: + image = Path(override).expanduser().resolve() + elif registry_path().exists(): + image = Path(json.loads(registry_path().read_text())['image']) + else: + return None + if not image.is_file(): + raise ValueError(f'Registered Pathway Tools image is missing: {image}; run metapathways build_pt again') + return str(image) + + +def save_json(path, data): + path = Path(path) + path.parent.mkdir(parents=True, exist_ok=True) + with tempfile.NamedTemporaryFile(mode='w', dir=path.parent, delete=False) as f: + temp = Path(f.name) + json.dump(data, f, indent=2) + f.write('\n') + try: + temp.replace(path) + finally: + temp.unlink(missing_ok=True) + + +def exec_command(image, state, command): + """Use a task-private data directory, PID namespace, home and /tmp.""" + state = Path(state).resolve() + state.mkdir(parents=True, exist_ok=True) + if any(c in str(state) for c in ':,\n'): + raise ValueError('Apptainer state path cannot contain a colon, comma or newline') + executable = shutil.which('apptainer') + if not executable: + raise RuntimeError('Apptainer is required and must be on PATH') + return [executable, 'exec', '--containall', '--cleanenv', + '--home', f'{state}:/data', '--pwd', '/data', str(image), *command] + + +def validate(image, directory): + script = ('cp -a /opt/ptools-local-template /data/ptools-local; ' + 'cp /opt/mp-ncbirc /data/.ncbirc; ' + 'blastp -version; makeblastdb -version; ' + 'printf ">mp_validation\\nMKWVTFISLLFLFSSAYSRGVFRRDTHKSEIAHRFKDLGE\\n" > /data/check.faa; ' + 'makeblastdb -in /data/check.faa -dbtype prot -out /data/check-db; ' + 'blastp -query /data/check.faa -db /data/check-db -outfmt 6 -out /data/check.tsv; ' + 'test -s /data/check.tsv; ' + 'exec xvfb-run -a /opt/pathway-tools/pathway-tools ' + '-no-patch-download -lisp -eval \'(progn (format t "~%MP-PT-READY~%") (exit))\'') + result = subprocess.run(exec_command(image, directory, ['sh', '-ec', script]), + check=False, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, + text=True, timeout=300) + if result.returncode: + raise RuntimeError(f'Pathway Tools startup failed (exit {result.returncode}): ' + result.stdout[-4000:]) + if 'MP-PT-READY' not in [line.strip() for line in result.stdout.splitlines()]: + raise RuntimeError('Pathway Tools startup did not emit its validation marker: ' + result.stdout[-4000:]) + if re.search(r'Error determining path to BLAST|blastall or blastp could not be located', result.stdout, re.I): + raise RuntimeError('Pathway Tools could not locate the installed BLAST executables: ' + result.stdout[-4000:]) + return result.stdout + + +def run_pgdb(image, inputs, outputs, tag, taxprune=False, sample_output=None, transport_inference=True): + """Run one PGDB with no shared host Pathway Tools state.""" + if not re.fullmatch(r'[A-Za-z_][A-Za-z0-9_-]*', tag): + raise ValueError('PGDB tag must start with a letter or underscore and contain only letters, digits, underscores or hyphens') + output = Path(outputs).resolve() + output.mkdir(parents=True, exist_ok=True) + with tempfile.TemporaryDirectory(prefix='.pt-run-', dir=output.parent) as work: + state = Path(work) + shutil.copytree(inputs, state / 'input') + (state / 'output').mkdir() + script = '''set -eu +cp -a /opt/ptools-local-template /data/ptools-local +if test -f /opt/mp-ncbirc; then cp /opt/mp-ncbirc /data/.ncbirc; fi +mkdir -p /data/blastdb /tmp/.X11-unix +# --containall isolates /tmp, but not Linux abstract sockets. Use only the +# private filesystem X socket so concurrent containers cannot collide. +printf 'build\n' > /data/stage.txt +xvfb-run -a -e /data/build-xvfb.log -s '-screen 0 1280x1024x24 -nolisten local' /opt/pathway-tools/pathway-tools -patho /data/input "$@" -no-web-cel-overview -no-patch-download -no-cel-overview -disable-metadata-saving -nologfile +''' + lisp = f"(progn (with-organism (:org-id '{tag}) (dump-frames-to-attribute-value-files (org-data-dir)))(exit))" + script += "printf 'export\\n' > /data/stage.txt\n" + script += shlex.join(['xvfb-run', '-a', '-e', '/data/export-xvfb.log', + '-s', '-screen 0 1280x1024x24 -nolisten local', '/opt/pathway-tools/pathway-tools', + '-no-patch-download', '-no-cel-overview', '-nologfile', '-eval', lisp]) + '\n' + script += "printf 'archive\\n' > /data/stage.txt\n" + script += shlex.join(['tar', '-cjf', f'/data/output/{tag}cyc.tar.bz2', + '-C', f'/data/ptools-local/pgdbs/user/{tag.lower()}cyc', '.']) + '\n' + command = ['sh', '-ec', script, 'run-pgdb'] + if transport_inference: + command.append('-tip') + if not taxprune: + command.append('-no-taxonomic-pruning') + invocation = exec_command(image, state, command) + diagnostics = output / 'diagnostics' / uuid.uuid4().hex + status = dict(tag=tag, image=str(image), command=invocation, status='FAILED') + try: + if sample_output is not None: + from metapathways.pt_sequences import attach_sequences + (state / 'stage.txt').write_text('input preparation\n') + attach_sequences(state / 'input', sample_output) + subprocess.run(invocation, check=True) + archive = state / 'output' / f'{tag}cyc.tar.bz2' + if not archive.is_file() or not archive.stat().st_size: + raise RuntimeError(f'Pathway Tools produced no PGDB archive for {tag}') + archive.replace(output / archive.name) + status['status'] = 'SUCCESS' + except BaseException as exc: + status['error'] = str(exc) + status['exit_code'] = getattr(exc, 'returncode', None) + # Pathologic redirects its own errors away from the parent's stderr. + private_log = state / 'input/pathologic.log' + if private_log.is_file(): + from collections import deque + with private_log.open(errors='replace') as stream: + tail = ''.join(deque(stream, maxlen=80)) + print(f'Pathway Tools internal log tail ({tag}):\n{tail}', flush=True) + raise + finally: + # Preserve internal diagnostics before TemporaryDirectory removes state, + # on success, failure, or an interrupted subprocess. + diagnostics.mkdir(parents=True, exist_ok=True) + stage = state / 'stage.txt' + status['stage'] = stage.read_text().strip() if stage.is_file() else 'container startup' + for source in state.rglob('*'): + if source.is_file() and (source.suffix.lower() in ('.log', '.err', '.out') + or source.name in ('stage.txt', 'sequence-input.json', 'organism-params.dat') + or 'reports' in source.relative_to(state).parts): + destination = diagnostics / source.relative_to(state) + destination.parent.mkdir(parents=True, exist_ok=True) + shutil.copy2(source, destination) + if status['status'] != 'SUCCESS': + # Retain the last on-disk PGDB for separate recovery attempts. + # Moving avoids copying a potentially large database before cleanup. + user_pgdbs = state / 'ptools-local/pgdbs/user' + if user_pgdbs.is_dir(): + retained = diagnostics / 'failed-pgdbs' + shutil.move(str(user_pgdbs), str(retained)) + status['retained_pgdbs'] = str(retained) + shutil.copytree(state / 'input', diagnostics / 'input', dirs_exist_ok=True) + save_json(diagnostics / 'execution.json', status) + print(f'Pathway Tools {status["status"]} during {status["stage"]}; diagnostics: {diagnostics}', flush=True) + + +def build(installer, image, installer_sha256, threads, version=None): + """Worker entry point: never publish or register a failed build.""" + installer, image = Path(installer).resolve(), Path(image).resolve() + if digest(installer) != installer_sha256: + raise ValueError('Installer changed after the build was planned') + executable = shutil.which('apptainer') + if not executable: + raise RuntimeError('Apptainer is required and must be on PATH') + image.parent.mkdir(parents=True, exist_ok=True) + with tempfile.TemporaryDirectory(prefix='.pt-build-', dir=image.parent) as work: + work = Path(work) + # A fixed relative name avoids definition-file quoting of arbitrary paths. + (work / 'installer').symlink_to(installer) + patches = download_patches(installer_version(installer, version), work / 'official-patches') + definition = work / 'pathway-tools.def' + definition.write_text(RECIPE) + partial = work / 'pathway-tools.sif' + subprocess.run([executable, 'build', '--fakeroot', '--mksquashfs-args', + f'-processors {threads}', str(partial), str(definition)], + cwd=work, check=True) + validation_log = validate(partial, work / 'validation') + metadata = dict(installer_sha256=installer_sha256, image=str(image), + image_sha256=digest(partial), recipe_sha256=hashlib.sha256(RECIPE.encode()).hexdigest(), + official_patches=patches, validation_log=validation_log) + partial.replace(image) + save_json(str(image) + '.json', metadata) + image.with_suffix('.def').write_text(RECIPE) + + +def parser(): + p = argparse.ArgumentParser(prog='metapathways build_pt', + description='Build a Pathway Tools SIF from a local Linux installer using Nextflow and Apptainer.') + p.add_argument('-i', '--installer', required=True, help='local Pathway Tools Linux x86-64 installer') + p.add_argument('--ptools_version', help='release number if the installer was renamed; otherwise inferred from its filename') + p.add_argument('-d', '--refdb_dir', help='also export and prepare the licensed MetaCyc reference in this MPDB after building the SIF') + p.add_argument('-a', '--aligner', choices=('fast', 'blast'), default='fast', help='MetaCyc reference index format with -d [fast]') + default = Path(os.environ.get('XDG_DATA_HOME', Path.home() / '.local/share')) / 'metapathways/containers' + p.add_argument('-o', '--output_dir', default=str(default), help='container directory [~/.local/share/metapathways/containers]') + p.add_argument('-t', '--threads', type=nextflow.positive, default=2, help='CPUs for image compression [2]; Pathway Tools uses one CPU') + p.add_argument('--dryrun', action='store_true', help='write and show the build plan without building or registering') + nextflow.add_resources(p, task_memory='4 GB') + return p + + +def main(argv=None): + p = parser() + args = p.parse_args(argv) + installer = Path(args.installer).expanduser().resolve() + if not installer.is_file(): + p.error(f'Installer does not exist: {installer}') + if platform.system() != 'Linux' or platform.machine() not in ('x86_64', 'AMD64'): + p.error('Building this Pathway Tools image requires Linux x86-64') + if not args.dryrun: + for executable in ('apptainer', 'nextflow'): + if not shutil.which(executable): + p.error(f'{executable} must be installed and on PATH') + checksum = digest(installer) + recipe_hash = hashlib.sha256(RECIPE.encode()).hexdigest() + try: + version = installer_version(installer, args.ptools_version) + except ValueError as exc: + p.error(str(exc)) + output = Path(args.output_dir).expanduser().resolve() + # Each explicit build refreshes the vendor feed and creates a separate SIF. + # Never overwrite an image that existing analysis receipts/running jobs use. + build_id = uuid.uuid4().hex + image = output / f'pathway-tools-{version}-{checksum[:12]}-{recipe_hash[:8]}-{build_id[:12]}.sif' + command = shlex.join([sys.executable, '-m', 'metapathways.pt_container', '--worker', + str(installer), str(image), checksum, str(args.threads), version]) + t = nextflow.task('build-pt-' + checksum + recipe_hash + build_id, 'Build Pathway Tools ' + version, + [command], [str(installer)], [str(image), str(image) + '.json'], + cpus=args.threads, memory=args.memory, adopt_existing=False) + tasks = [t] + if args.refdb_dir: + from metapathways.nf_databases import metacyc_task + tasks.append(metacyc_task(args.refdb_dir, image, args.aligner, args.memory, [t['id']])) + nextflow.launch(tasks, output, args, 'build_pt', dryrun=args.dryrun) + if not args.dryrun: + metadata = json.loads(Path(str(image) + '.json').read_text()) + if metadata['image_sha256'] != digest(image): + raise RuntimeError('Built image checksum does not match its metadata') + save_json(registry_path(), metadata) + print(f'Pathway Tools image: {image}\nRegistered in: {registry_path()}') + + +if __name__ == '__main__': + if len(sys.argv) > 1 and sys.argv[1] == '--worker': + build(*sys.argv[2:5], int(sys.argv[5]), sys.argv[6]) + else: + main() diff --git a/metapathways/pt_ec.py b/metapathways/pt_ec.py new file mode 100644 index 0000000..23deffa --- /dev/null +++ b/metapathways/pt_ec.py @@ -0,0 +1,19 @@ +"""Normalize multi-valued EC annotations without inventing EC assignments.""" +import re + + +def normalize_ecs(values): + """Return distinct EC tokens in input order; preserve provisional identifiers.""" + if values is None: + return [] + if isinstance(values, str): + values = [values] + result = [] + seen = set() + for value in values: + for token in re.split(r'[,;|]', str(value)): + token = token.strip() + if token and token not in seen: + seen.add(token) + result.append(token) + return result diff --git a/metapathways/pt_sequences.py b/metapathways/pt_sequences.py new file mode 100644 index 0000000..991f62c --- /dev/null +++ b/metapathways/pt_sequences.py @@ -0,0 +1,153 @@ +"""Attach real contig sequences to compact PathoLogic input in private staging.""" +import csv +import json +import re +from pathlib import Path +from metapathways.pt_ec import normalize_ecs + + +def normalize_trna_name(name): + """Separate MP's amino-acid label from a known anticodon; retain locus IDs.""" + return re.sub( + r'(\.tRNA\d+-(?:Ala|Arg|Asn|Asp|Cys|Gln|Glu|Gly|His|Ile|Leu|Lys|' + r'Met|Phe|Pro|Ser|Thr|Trp|Tyr|Val|fMet|SeC|Sec|Pyl))([ACGTU]{3})$', + r'\1-\2', name) + + +def set_organism_taxon(inputs, taxon_id): + """Apply an explicit NCBI taxon override to private PathoLogic input.""" + if not isinstance(taxon_id, int) or isinstance(taxon_id, bool) or taxon_id < 1: + raise ValueError('NCBI taxon ID must be a positive integer') + params = Path(inputs) / 'organism-params.dat' + lines = params.read_text().splitlines() + lines = [line for line in lines if line.split(None, 1)[:1] != ['NCBI-TAXON-ID']] + lines.append(f'NCBI-TAXON-ID\t{taxon_id}') + params.write_text('\n'.join(lines) + '\n') + print(f'Pathway Tools organism taxon override: {taxon_id}', flush=True) + + +def prodigal_codon_tables(gff): + """Read per-contig genetic codes from Prodigal's original model metadata.""" + tables, contig = {}, None + if not gff.is_file(): + return tables + for line in gff.read_text().splitlines(): + if line.startswith('# Sequence Data:'): + match = re.search(r'seqhdr="([^" ]+)', line) + contig = match.group(1) if match else None + elif line.startswith('# Model Data:'): + match = re.search(r'transl_table=(\d+)(?:;|$)', line) + if contig is None or match is None: + raise ValueError(f'Missing Prodigal contig/genetic-code metadata in {gff}') + code = int(match.group(1)) + if code not in (1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 13, 14, 15): + raise ValueError(f'Unsupported PathoLogic codon table {code} for {contig}') + if contig in tables and tables[contig] != code: + raise ValueError(f'Conflicting Prodigal codon tables for {contig}') + tables[contig] = code + return tables + + +def attach_sequences(inputs, sample_output): + inputs, base = Path(inputs), Path(sample_output) + sample = base.name + table = base/'results/annotation_table'/f'{sample}.ptinput.tsv' + fasta = base/'preprocessed'/f'{sample}.fasta' + for file in (table, fasta): + if not file.is_file(): + raise ValueError(f'Cannot prepare sequence-backed Pathway Tools input; missing {file}') + with table.open() as stream: + reader = csv.DictReader(stream, delimiter='\t') + if not {'orf_id', 'seqname', 'start', 'end', 'strand'} <= set(reader.fieldnames or []): + raise ValueError(f'Pathway Tools annotation table lacks feature coordinates/contig/strand: {table}') + features = {} + for row in reader: + if not row['orf_id'] or not row['seqname'] or row['orf_id'] in features: + raise ValueError('Missing or duplicate feature/contig in annotation table: ' + row['orf_id']) + start, end = int(row['start']), int(row['end']) + if start < 1 or end < start or row['strand'] not in ('+', '-'): + raise ValueError('Invalid source coordinates/strand for ' + row['orf_id']) + if row['strand'] == '-': + start, end = end, start + features[row['orf_id']] = (row['seqname'], start, end) + records, seen, corrected = {}, set(), 0 + normalized_ec_records = 0 + normalized_trna_names = {} + texts, lines = [], [] + for line in (inputs/'0.pf').read_text().splitlines(): + if line.strip() == '//': + texts.append('\n'.join(lines)) + lines = [] + else: + lines.append(line) + if any(line.strip() for line in lines): + raise ValueError('Unterminated Pathway Tools feature record') + for text in texts: + if not text.strip(): + continue + fields = dict(line.split('\t', 1) for line in text.strip().splitlines() if '\t' in line) + identifier = fields.get('ID') + if identifier in seen or identifier not in features: + raise ValueError('Duplicate or unmapped Pathway Tools feature: ' + str(identifier)) + seen.add(identifier) + contig, start, end = features[identifier] + # MAG splitter expands representative annotations to member IDs but retains + # the representative's coordinates. Restore each member's actual locus. + corrected += (fields.get('STARTBASE'), fields.get('ENDBASE')) != (str(start), str(end)) + fixed = [line for line in text.strip().splitlines() if not line.startswith(('STARTBASE\t', 'ENDBASE\t'))] + if fields.get('PRODUCT-TYPE', '').upper() == 'TRNA': + old_name = fields.get('NAME', '') + new_name = normalize_trna_name(old_name) + if new_name != old_name: + fixed = ['NAME\t' + new_name if line.startswith('NAME\t') else line for line in fixed] + normalized_trna_names[identifier] = dict(original=old_name, staged=new_name) + old_ecs = [line.split('\t', 1)[1] for line in fixed if line.startswith('EC\t')] + ecs = normalize_ecs(old_ecs) + normalized_ec_records += old_ecs != ecs + fixed = [line for line in fixed if not line.startswith('EC\t')] + fixed.extend('EC\t' + ec for ec in ecs) + fixed.extend([f'STARTBASE\t{start}', f'ENDBASE\t{end}']) + records.setdefault(contig, []).append(('\n'.join(fixed)+'\n//\n', start, end)) + if not records: + raise ValueError('Pathway Tools input contains no feature records') + sequences, name, parts = {}, None, [] + def save(): + if name in records: + if name in sequences: + raise ValueError('Duplicate contig sequence: ' + name) + sequences[name] = ''.join(parts) + with fasta.open() as stream: + for line in stream: + if line.startswith('>'): + save() + name, parts = line[1:].split()[0], [] + elif name in records: + parts.append(line.strip()) + save() + missing = set(records)-set(sequences) + if missing: + raise ValueError('Missing Pathway Tools contig sequences: ' + ', '.join(sorted(missing)[:10])) + # Validate everything before replacing the genetic-element manifest. + for contig, features in records.items(): + for _, start, end in features: + if min(start, end) < 1 or max(start, end) > len(sequences[contig]): + raise ValueError(f'Pathway Tools coordinates {start}..{end} outside {contig} (length {len(sequences[contig])})') + codon_tables = prodigal_codon_tables(base/'orf_prediction'/f'{sample}.cds.gff') + elements = [] + for number, contig in enumerate(sorted(records), 1): + identifier = f'contig_{number}' + (inputs/(identifier+'.pf')).write_text(''.join(record[0] for record in records[contig])) + seq = sequences[contig] + (inputs/(identifier+'.fasta')).write_text('>'+identifier+'\n' + '\n'.join(seq[i:i+80] for i in range(0, len(seq), 80))+'\n') + code = f'CODON-TABLE\t{codon_tables[contig]}\n' if contig in codon_tables else '' + elements.append(f'ID\t{identifier}\nNAME\t{contig}\nTYPE\t:CONTIG\n{code}ANNOT-FILE\t{identifier}.pf\nSEQ-FILE\t{identifier}.fasta\n//\n') + (inputs/'genetic-elements.dat').write_text(''.join(elements)) + (inputs/'sequence-input.json').write_text(json.dumps(dict(contigs=len(sequences), features=len(seen), + restored_coordinates=corrected, normalized_ec_records=normalized_ec_records, + normalized_trna_names=normalized_trna_names, + codon_tables={c: codon_tables[c] for c in records if c in codon_tables}, fasta=str(fasta), feature_table=str(table)), indent=2)+'\n') + if normalized_trna_names: + print(f'Separated anticodon triplets in {len(normalized_trna_names)} tRNA names; feature IDs and original inputs retained', flush=True) + if normalized_ec_records: + print(f'Normalized EC entries in {normalized_ec_records} features; original inputs retained', flush=True) + print(f'Attached {len(sequences)} contig sequences to {len(seen)} Pathway Tools features; restored {corrected} feature coordinates', flush=True) diff --git a/metapathways/pt_taxonomy.py b/metapathways/pt_taxonomy.py new file mode 100644 index 0000000..81459b8 --- /dev/null +++ b/metapathways/pt_taxonomy.py @@ -0,0 +1,41 @@ +"""Readable aliases for explicit Pathway Tools organism taxon overrides.""" +import argparse + +SCOPES = {'all': 131567, 'bacteria': 2, 'archaea': 2157, 'eukaryotes': 2759} +ALIASES = {'euks': 'eukaryotes'} + + +def positive_taxon(value): + try: + taxon = int(value) + except (TypeError, ValueError): + raise argparse.ArgumentTypeError('taxon ID must be a positive integer') + if taxon < 1: + raise argparse.ArgumentTypeError('taxon ID must be a positive integer') + return taxon + + +def scope_name(value): + if value == 'prokaryotes': + raise argparse.ArgumentTypeError( + 'prokaryotes combines Bacteria and Archaea and has no supported single ' + 'NCBI taxon here; choose bacteria, archaea, or all (includes eukaryotes)') + return ALIASES.get(value, value) + + +def add_taxonomy_options(parser): + group = parser.add_mutually_exclusive_group() + group.add_argument('--taxon_id', type=positive_taxon, + help='Override PGDB NCBI taxon in private inputs; applies to every selected entity') + group.add_argument('--taxonomic_scope', type=scope_name, choices=tuple(SCOPES), + help='Named PGDB taxon override; all means cellular life; euks aliases eukaryotes. ' + 'Use --taxprune to retain pruning and avoid unpruned rescoring. ' + 'Omitting both options preserves the input taxon.') + + +def resolve_taxon(args): + scope = getattr(args, 'taxonomic_scope', None) + taxon = getattr(args, 'taxon_id', None) + if scope and taxon is not None: + raise ValueError('--taxon_id and --taxonomic_scope are mutually exclusive') + return SCOPES[scope] if scope else taxon diff --git a/metapathways/regtests/cami_reviewer/Gastrointestinal_5.selection.log b/metapathways/regtests/cami_reviewer/Gastrointestinal_5.selection.log new file mode 100644 index 0000000..20566c6 --- /dev/null +++ b/metapathways/regtests/cami_reviewer/Gastrointestinal_5.selection.log @@ -0,0 +1,11 @@ +[M::mm_idx_gen::0.004*1.29] collected minimizers +[M::mm_idx_gen::0.012*1.60] sorted minimizers +[M::main::0.012*1.60] loaded/built the index for 3 target sequence(s) +[M::mm_mapopt_update::0.012*1.60] mid_occ = 1000 +[M::mm_idx_stat] kmer size: 21; skip: 11; is_hpc: 0; #seq: 3 +[M::mm_idx_stat::0.012*1.57] distinct minimizers: 24598 (99.13% are singletons); average occurrences: 1.009; average spacing: 6.045; total length: 150000 +[M::worker_pipeline::0.918*2.05] mapped 333334 sequences +[M::worker_pipeline::1.077*1.98] mapped 166666 sequences +[M::main] Version: 2.31-r1302 +[M::main] CMD: /data/home/ryan/repos/metapathways-setup/environment/bin/minimap2 -ax sr -t 2 /data/tmp/mp-cami-reviewer-0sinn_1_/assembly.fasta /data/tmp/mp-cami-reviewer-0sinn_1_/r1.fq /data/tmp/mp-cami-reviewer-0sinn_1_/r2.fq +[M::main] Real time: 1.109 sec; CPU: 2.170 sec; Peak RSS: 0.198 GB diff --git a/metapathways/regtests/cami_reviewer/README.md b/metapathways/regtests/cami_reviewer/README.md new file mode 100644 index 0000000..775b046 --- /dev/null +++ b/metapathways/regtests/cami_reviewer/README.md @@ -0,0 +1,32 @@ +# Tiny CAMI II reviewer inputs + +Use the [reviewer walkthrough](../../../docs/reviewer-test.md) for normal MP commands. + +This bundle contains three different samples from the CAMI II human-associated short-read dataset: Urogenital_22, Gastrointestinal_5 and Skin_28. Each has three 50,000-base assembly regions from three source genomes, intact paired simulated reads, and a headerless contig-to-genome map. Total input size is about 2.4 MiB compressed. No Pathway Tools installer, image, MetaCyc reference or licensed PGDB is included. + +- `single.tsv`: Urogenital_22. +- `pair.tsv`: Gastrointestinal_5 and Skin_28. +- `all.tsv`: all three. +- `inputs/`: strict automatic-discovery layout containing only assemblies, reads and genome maps. +- `provenance.json`: selection method, source files, original GSA mapping rows, retained coordinates, aligned-pair counts and SHA256 hashes. +- `validation.json`: input validation and predicted gene counts; the complete MP workflow has not been executed as part of preparing this bundle. +- `*.selection.log`: minimap2 selection diagnostics. + +Manifest paths are relative to the manifest file. Copy the whole bundle when moving it. Original contig and read identifiers are preserved; contigs are cropped to their first 50,000 bases. Source genome IDs are prefixed with `CAMI_` and punctuation becomes underscores for MP-compatible entity names. Coordinates in `provenance.json` explicitly distinguish original source mapping intervals from retained contig-relative intervals. + +For each sample, the preparation script ranks contigs at least 20 kb long by source read density, chooses one contig from each of three different genomes, and retains at most 50 kb per contig. It scans the first 250,000 original interleaved read pairs, aligns them to the retained regions with minimap2, and keeps at most 3,000 complete pairs with at least one primary alignment at MAPQ 20 or higher. Both original mates and qualities are retained even if only one mate maps. Every retained contig must have at least ten selected pairs aligning to it. The cap and selection deliberately bias coverage; this is interface-test data, not an accuracy or abundance benchmark. Three short genome fragments are not three complete MAGs. + +Maintainers can reproduce the data from an MP manifest pointing at the original local CAMI downloads: + +```bash +python scripts/prepare_cami_reviewer.py \ + --source-manifest /path/to/full-cami-manifest.tsv \ + --output /path/to/new-cami-reviewer \ + --minimap2 /path/to/minimap2 +``` + +Run from the source checkout. The output directory must not already exist. Source assemblies must have a sibling `gsa_mapping.tsv`, and the selected sample read inputs must be the original interleaved FASTQs. Python and minimap2 are required. Temporary read subsets and alignments are cleaned up after preparation. Reproduction requires the original large CAMI files; reviewers use the bundled small files directly. + +## Source attribution + +Derived from the CAMI II multi-sample human microbiome dataset, [DOI 10.4126/FRL01-006425518](https://doi.org/10.4126/FRL01-006425518). Cite the CAMI II study, Meyer et al., *Critical Assessment of Metagenome Interpretation: the second round of challenges*, Nature Methods (2022), [DOI 10.1038/s41592-022-01431-4](https://doi.org/10.1038/s41592-022-01431-4). Cropping, read selection, mate separation and MP-format maps are the modifications made here. The data retain their source terms; the MP software license does not relicense third-party data. diff --git a/metapathways/regtests/cami_reviewer/Skin_28.selection.log b/metapathways/regtests/cami_reviewer/Skin_28.selection.log new file mode 100644 index 0000000..466a20b --- /dev/null +++ b/metapathways/regtests/cami_reviewer/Skin_28.selection.log @@ -0,0 +1,11 @@ +[M::mm_idx_gen::0.006*1.23] collected minimizers +[M::mm_idx_gen::0.010*1.46] sorted minimizers +[M::main::0.010*1.46] loaded/built the index for 3 target sequence(s) +[M::mm_mapopt_update::0.010*1.46] mid_occ = 1000 +[M::mm_idx_stat] kmer size: 21; skip: 11; is_hpc: 0; #seq: 3 +[M::mm_idx_stat::0.011*1.43] distinct minimizers: 20161 (75.80% are singletons); average occurrences: 1.243; average spacing: 5.987; total length: 150000 +[M::worker_pipeline::0.985*1.90] mapped 333334 sequences +[M::worker_pipeline::1.201*1.87] mapped 166666 sequences +[M::main] Version: 2.31-r1302 +[M::main] CMD: /data/home/ryan/repos/metapathways-setup/environment/bin/minimap2 -ax sr -t 2 /data/tmp/mp-cami-reviewer-0sinn_1_/assembly.fasta /data/tmp/mp-cami-reviewer-0sinn_1_/r1.fq /data/tmp/mp-cami-reviewer-0sinn_1_/r2.fq +[M::main] Real time: 1.221 sec; CPU: 2.263 sec; Peak RSS: 0.199 GB diff --git a/metapathways/regtests/cami_reviewer/Urogenital_22.selection.log b/metapathways/regtests/cami_reviewer/Urogenital_22.selection.log new file mode 100644 index 0000000..1168cc5 --- /dev/null +++ b/metapathways/regtests/cami_reviewer/Urogenital_22.selection.log @@ -0,0 +1,11 @@ +[M::mm_idx_gen::0.004*1.25] collected minimizers +[M::mm_idx_gen::0.012*1.59] sorted minimizers +[M::main::0.012*1.60] loaded/built the index for 3 target sequence(s) +[M::mm_mapopt_update::0.012*1.60] mid_occ = 1000 +[M::mm_idx_stat] kmer size: 21; skip: 11; is_hpc: 0; #seq: 3 +[M::mm_idx_stat::0.012*1.57] distinct minimizers: 25092 (99.95% are singletons); average occurrences: 1.001; average spacing: 5.975; total length: 150000 +[M::worker_pipeline::0.917*2.03] mapped 333334 sequences +[M::worker_pipeline::1.119*1.97] mapped 166666 sequences +[M::main] Version: 2.31-r1302 +[M::main] CMD: /data/home/ryan/repos/metapathways-setup/environment/bin/minimap2 -ax sr -t 2 /data/tmp/mp-cami-reviewer-0sinn_1_/assembly.fasta /data/tmp/mp-cami-reviewer-0sinn_1_/r1.fq /data/tmp/mp-cami-reviewer-0sinn_1_/r2.fq +[M::main] Real time: 1.132 sec; CPU: 2.218 sec; Peak RSS: 0.198 GB diff --git a/metapathways/regtests/cami_reviewer/all.tsv b/metapathways/regtests/cami_reviewer/all.tsv new file mode 100644 index 0000000..9b11279 --- /dev/null +++ b/metapathways/regtests/cami_reviewer/all.tsv @@ -0,0 +1,4 @@ +sample_id assembly read_layout reads_1 reads_2 mag_map +Urogenital_22 inputs/assemblies/Urogenital_22.fasta.gz paired inputs/reads/Urogenital_22_R1.fastq.gz inputs/reads/Urogenital_22_R2.fastq.gz inputs/mag_maps/Urogenital_22.tsv +Gastrointestinal_5 inputs/assemblies/Gastrointestinal_5.fasta.gz paired 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