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.
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill pacsomatic
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.pyIntegration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
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Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
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Take k-dense-ai/pacsomatic from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.