pacsomatic
About
This Claude Skill assists developers in running the nf-core/pacsomatic workflow for matched tumor-normal analysis from BAM files. It validates inputs, generates compliant samplesheets, and prepares reproducible Nextflow launch artifacts for local execution or cluster submission. The toolkit also helps troubleshoot pipeline startup and scheduler errors.
Quick Install
Claude Code
Recommendednpx skills add K-Dense-AI/claude-scientific-skills -a claude-code/plugin add https://github.com/K-Dense-AI/claude-scientific-skillsgit clone https://github.com/K-Dense-AI/claude-scientific-skills.git ~/.claude/skills/pacsomaticCopy and paste this command in Claude Code to install this skill
Documentation
pacsomatic
Overview
This skill provides a reproducible execution workflow for nf-core/pacsomatic, centered on a single helper entrypoint that handles validation, artifact generation, and optional execution.
Primary entrypoint:
scripts/run_pacsomatic.py
The helper script:
- validates required identifiers, files, reference mode, and runtime prerequisites
- writes a pacsomatic-compatible samplesheet (
patient,sample,status,bam,pbi) - generates a params YAML and launch script for reproducible reruns
- supports dry-run validation and run/submit execution paths
Use this skill as the default path for pacsomatic operations. Do not bypass it with manually assembled nextflow run nf-core/pacsomatic commands unless the user explicitly asks for manual command construction.
When to Use This Skill
Invoke this skill when the user asks to:
- run matched tumor-normal analysis from BAM files
- generate or fix pacsomatic samplesheet and launch artifacts
- execute locally or submit to schedulers (LSF/Slurm/PBS/SGE)
- perform dry-run validation before execution
- troubleshoot launch failures or summarize run outputs
Do not use this skill for:
- deep biological interpretation beyond run-level sanity checks
- editing pipeline internals unless explicitly requested
Typical trigger phrases:
- "run nf-core/pacsomatic for this tumor-normal pair"
- "prepare pacsomatic samplesheet and launch script"
- "do a dry run first and tell me what is missing"
- "submit pacsomatic to slurm/lsf and return the job id"
- "why did pacsomatic submission fail"
Routing and Execution Rules
- Always collect required run inputs first.
- Always route through
scripts/run_pacsomatic.pyfor validation and artifact generation. - Default to
--dry-runwhen the user asks for checks/validation only. - Use
--runonly when the user asks to execute/submit. - For scheduler modes, include executor-specific resource arguments and return detected job ID when available.
- If execution fails, report first failure point and next triage target (
.nextflow.log,pipeline_info, failing task logs).
Inputs Required
Required:
- tumor BAM path
- normal BAM path
- patient ID
- tumor sample ID
- normal sample ID
- output directory
- exactly one reference mode:
--fastaor--genome
Optional:
- profile, resources, scheduler account/queue
- pipeline version (
-r) - params file, resume/report/dag flags
--dry-runand/or--run
Workflow
- Validate identity and input constraints.
- Validate required local paths (BAM, optional PBI, optional FASTA).
- Resolve runtime and dependency checks.
- Build samplesheet and generated params YAML.
- Generate launch script for selected executor.
- If
--dry-runand not--run, stop after artifact generation. - If
--run, execute locally or submit to scheduler. - Return command/script path, validation status, and job ID (if detected).
Agent Response Contract
Every response after invocation should include:
- exact command used or generated script path
- confirmation that validation checks ran
- run type (
dry-runvsrun) - scheduler job ID when available
- one concrete next step for validation/triage
Quick Start
Dry run:
python scripts/run_pacsomatic.py \
--tumor-bam /path/to/tumor.bam \
--normal-bam /path/to/normal.bam \
--patient-id P001 \
--tumor-sample-id P001_T \
--normal-sample-id P001_N \
--outdir /path/to/output \
--genome GRCh38 \
--profile singularity,sanger \
--dry-run
Scheduler execution example (Slurm):
python scripts/run_pacsomatic.py \
--tumor-bam /path/to/tumor.bam \
--normal-bam /path/to/normal.bam \
--patient-id P001 \
--tumor-sample-id P001_T \
--normal-sample-id P001_N \
--outdir /path/to/output \
--genome GRCh38 \
--profile singularity,sanger \
--executor slurm \
--queue compute \
--project my_account \
--cpus 16 \
--memory-gb 64 \
--walltime 48:00 \
--run
Configuration
Use config.yaml as the baseline for profile/executor/runtime defaults. Override at invocation time when user requirements differ.
Testing
Run unit tests from skill root:
python -m unittest discover -s tests -v
References
references/agent-playbook.mdreferences/config-and-output.mdreferences/pacsomatic_guide.mdscripts/run_pacsomatic.py
GitHub Repository
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