# ngs-dna-somatic-variants

A skill that plans and runs somatic variant workflows for tumor-normal and tumor-only designs, WGS, WES and cancer panels. Useful for checking sample pairs before a pipeline starts.

- skill · `type=skill` · Codex, ChatGPT · 2 installs · ★ 7604
- Author: OpenAI · official OpenAI repository
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/openai/plugins/tree/HEAD/plugins/ngs-analysis/skills/ngs-dna-somatic-variants/SKILL.md
- Updated: 2026-10-08
- HTML: https://affpapa.org/en/nevibecode/skills/ngs-dna-somatic-variants

## What it does

The skill handles somatic SNV and indel calling from FASTQ, BAM or CRAM. Four designs are covered: tumor-normal, tumor-only, relapse-baseline and multi-tumor. Inherited germline calling and family analysis belong to a separate skill, `ngs-dna-germline-variants`.

Two scripts do the work. `ngs_preflight.py` inspects the environment and prints an install plan; `run_dna_somatic_variants.py` builds the pairing table, the Mutect2 command plan, contamination and filtering artifacts, and a QC summary. A full pipeline route exists through `run_nfcore_pipeline.py --pipeline sarek`. Outputs include a validated sample sheet, a resource manifest, `qc/somatic_pair_review.tsv` plus JSON, and filtered VCF files.

Resource checking is advisory by default, so custom or reduced references can still be planned. Adding `--genome-build`, `--bundle-root` and `--require-resource-plan` makes missing registered bundles block readiness instead. A swapped or absent normal changes what the calls mean biologically, so verify pair metadata first. Tumor-only runs need a germline resource and careful filtering, or false positives reach the report as somatic. Never reuse a panel-of-normals across incompatible capture kits or genome builds.

## Install

### Codex (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill ngs-dna-somatic-variants -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/ngs-dna-somatic-variants/SKILL.md` — For all projects use ~/.agents/skills/

### Claude Code

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill ngs-dna-somatic-variants -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/ngs-dna-somatic-variants/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/ngs-dna-somatic-variants/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/ngs-dna-somatic-variants/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install openai/plugins ngs-dna-somatic-variants
```

2. **Manually: put the files in place**
- File: `.github/skills/ngs-dna-somatic-variants/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/openai/plugins --path plugins/ngs-analysis/skills/ngs-dna-somatic-variants
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/ngs-dna-somatic-variants/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/openai/plugins/tree/HEAD/plugins/ngs-analysis/skills/ngs-dna-somatic-variants/SKILL.md

## When to use it
- verify tumor-normal pairs before a pipeline run
- plan Mutect2 calls from prepared BAM or CRAM files
- summarize QC on depth, contamination and duplication
- filter false positives out of tumor-only calls
- prepare a reference and germline resource manifest

## Example prompts
- Check the sample pairs in `somatic_pairs.tsv` and build a Mutect2 run plan
- Run `run_dna_somatic_variants.py` with `reference.fa` and the panel-of-normals `pon.vcf.gz`
- Plan the sarek pipeline for a WES panel with a target BED

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 8dc69d4378db929d.

BEGIN THIRD-PARTY FILE 8dc69d4378db929d
````text
---
name: ngs-dna-somatic-variants
description: Run or plan tumor-normal, tumor-only, WGS, WES, or cancer-panel somatic variant workflows with pairing, contamination, panel-of-normals, purity, QC, and annotation checks.
---

# Somatic DNA Variants

Use this skill for tumor-normal or tumor-only somatic SNV/indel calling from FASTQ, BAM, or CRAM. If the request is inherited germline calling or family analysis, use `ngs-dna-germline-variants`.

## Essential Inputs

Confirm:

- tumor-normal, tumor-only, relapse-baseline, or multi-tumor design
- WGS, WES, or panel assay and target BED when applicable
- input type and whether reads are already aligned
- tumor/normal pairing table and sample identifiers
- reference build, known-sites, germline resource, and annotation cache
- panel-of-normals availability and matched-normal availability
- tumor purity, contamination expectations, and minimum allele fraction goals
- desired outputs: raw calls, filtered calls, VEP/SnpEff annotation, MAF, CNV/SV handoff

## Route

Prefer `nf-core/sarek` for an end-to-end public workflow when its supported callers fit the request. Use direct GATK Mutect2 or bcftools/samtools utilities for focused validation or prepared BAMs.

Preflight command:

```bash
python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline dna_somatic_variants --emit-install-plan
```

For compact local checks from prepared tumor/normal BAM/CRAM files, use the dedicated Mutect2 runner:

```bash
python plugins/ngs-analysis/scripts/run_dna_somatic_variants.py \
  --sample-sheet somatic_pairs.tsv \
  --reference-fasta reference.fa \
  --germline-resource af-only-gnomad.vcf.gz \
  --panel-of-normals pon.vcf.gz \
  --execute
```

This produces a tumor-normal/tumor-only pairing table, Mutect2 command plan, contamination/filtering artifacts, somatic QC summary, `qc/somatic_pair_review.{tsv,json}`, visualization index, and filtered VCF outputs when the local GATK resources are available. For nf-core execution, use `plugins/ngs-analysis/scripts/run_nfcore_pipeline.py --pipeline sarek`.

The direct runner also emits `resources/resource_plan.json`, `resource_manifest.tsv`, `resource_env.sh`, and `resource_readiness.md`. The resource check is advisory by default so custom or reduced references can still be planned; add `--genome-build`, `--bundle-root <bundle>=<path>`, and `--require-resource-plan` when missing registered reference bundles should block readiness.

## Decision Points

- Verify tumor-normal pair metadata before execution. A swapped or missing normal changes the biological meaning of the calls.
````
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