pacsomatic

When to use

Use scripts/run_pacsomatic.py to prepare one matched PacBio HiFi tumor/normal pair, generate a samplesheet and reproducible launch artifacts, and launch locally or submit the Nextflow driver to a scheduler. The pipeline realigns input BAMs; this helper targets unaligned HiFi BAMs and optional PacBio .pbi indexes. Do not substitute short reads or treat a BAM filename as evidence of platform, matched identity, or methylation information.

The reviewed upstream dev commit is 24c84cb371b0339c1d65a4de9451671945e19772. GitHub had no releases or tags on 2026-10-01, despite the internal manifest saying 1.0.0. The helper pins that commit by default for nf-core/pacsomatic; it does not invent a release tag. This is a source-reviewed development workflow, not a clinically validated assay. See references/pacsomatic_guide.md for sources and scientific checks.

Workflow

1. Obtain distinct tumor and normal BAM paths, patient ID, distinct sample IDs, output directory, and exactly one reference mode: --fasta or --genome. IDs and BAM/PBI/FASTA paths must have no whitespace. Local inputs must be nonempty regular files. Remote BAM/PBI/FASTA URIs are passed through without downloading or authenticating; use managed filesystem/cloud credentials, never embed secrets or signed URLs in generated files.
2. Confirm PacBio HiFi read groups and sample identity from acquisition metadata; confirm that MM/ML modification tags needed for methylation have been retained. Verify reference sequence/contig compatibility for every annotation resource.
3. Generate artifacts with --dry-run. This performs helper checks and writes files, but does not invoke the pipeline, validate BAM contents, check remote availability, resolve every pipeline parameter, or verify biological suitability. Missing runtime tools are warnings here. --dry-run cannot be combined with --run/--submit, cloning, or environment creation.
4. Review samplesheet, generated params YAML, script, pipeline revision, profiles, and branch-specific resources/skips. Existing artifacts require explicit --overwrite; input files can never be artifact targets. config.yaml is an operator reference, not an automatically loaded configuration file.
5. For execution, select the actual runtime with --use-current-path or an existing --conda-env. Load cluster modules before invoking the helper; --module-load only repeats those commands in the generated script. No Conda YAML is bundled; creating an environment needs --conda-env-file explicitly.
6. Use --run only for requested execution. For HPC, distinguish the outer launcher scheduler (--executor) from Nextflow's per-task process.executor, configured by a site profile or --nextflow-config. Driver CPU/memory requests do not constrain task resources. Read references/config-and-output.md.
7. Report artifact paths, revision, checks/warnings, run type, submission ID if present, and a concrete next QC or failure-triage step. Scheduler acceptance is not pipeline completion. Keep the output directory and work/cache state stable for --resume; scripts run with the output directory as their cwd.

Examples

Run these from the repository root. Paths and site settings are illustrative; local tests use synthetic placeholders only, not human genomic data.

python skills/pacsomatic/scripts/run_pacsomatic.py \
  --tumor-bam /data/P001_T.bam --normal-bam /data/P001_N.bam \
  --patient-id P001 --tumor-sample-id P001_T --normal-sample-id P001_N \
  --outdir /results/P001 --fasta /refs/GRCh38.fa \
  --profile apptainer --use-current-path --dry-run

After reviewing artifacts, a Slurm launch can use the same inputs plus the following options (replace --dry-run with --run):

--executor slurm --queue compute --project my_account
--cpus 2 --memory-gb 8 --walltime 48:00
--nextflow-config /configs/slurm.config --overwrite --run

Those resources are for the driver, assuming the reviewed infrastructure config sets process.executor = 'slurm' and suitable task queue/resources. The helper normalizes 48:00 to Slurm 48:00:00 (48 hours). Do not add a sanger profile unless actually using that institution's LSF infrastructure.

Custom pipeline parameters go in --params-file; infrastructure goes in

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