Operator toolkit for nf-core/pacsomatic matched tumor-normal workflows from BAM inputs. Use this skill when the user needs to validate run inputs, generate pacsomatic-compliant samplesheets, prepare reproducible Nextflow launch artifacts, run locally or submit to schedulers (LSF/Slurm/PBS/SGE), and triage execution failures. Triggers on requests to run pacsomatic, prepare launch commands/scripts, perform dry-run checks, or troubleshoot pipeline startup and scheduler submission errors.
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.pyThe helper script:
patient,sample,status,bam,pbi)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.
Invoke this skill when the user asks to:
Do not use this skill for:
Typical trigger phrases:
scripts/run_pacsomatic.py for validation and artifact generation.--dry-run when the user asks for checks/validation only.--run only when the user asks to execute/submit..nextflow.log, pipeline_info, failing task logs).Required:
--fasta or --genomeOptional:
-r)--dry-run and/or --run--dry-run and not --run, stop after artifact generation.--run, execute locally or submit to scheduler.Every response after invocation should include:
dry-run vs run)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
Use config.yaml as the baseline for profile/executor/runtime defaults. Override at invocation time when user requirements differ.
Run unit tests from skill root:
python -m unittest discover -s tests/pacsomatic -v
references/agent-playbook.mdreferences/config-and-output.mdreferences/pacsomatic_guide.mdscripts/run_pacsomatic.pyCopy a source-pinned command for your client. You run it yourself.
Destination: .claude/skills/pacsomatic · pinned to the source commit
git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
cd scientific-agent-skills
git checkout 36d8f13a1e754618794bf42f417884940077b4ae
mkdir -p ".claude/skills/pacsomatic"
cp -r "skills/pacsomatic" ".claude/skills/pacsomatic"Review the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.
sudo apt update && sudo apt install -y gitnpm install -g @anthropic-ai/claude-codegit clone https://github.com/K-Dense-AI/scientific-agent-skills.git
cd scientific-agent-skills
git checkout 36d8f13a1e754618794bf42f417884940077b4ae
mkdir -p ".claude/skills/pacsomatic"
cp -r "skills/pacsomatic" ".claude/skills/pacsomatic"Destination: .claude/skills/pacsomatic
Scanner static-checks@0.1.0 · commit 36d8f13a1e75. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.
No static rules matched. This is not a safety guarantee.