# ngs-dna-umi-panel-variants

Plan or run targeted DNA panel analysis with UMIs, consensus reads and low-frequency variant calling. Useful when molecular evidence and panel-specific QC matter.

- 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-umi-panel-variants/SKILL.md
- Updated: 2026-10-08
- HTML: https://affpapa.org/en/nevibecode/skills/ngs-dna-umi-panel-variants

## What it does

The skill lays out a workflow covering FASTQ checks, UMI extraction and consensus generation, alignment, target coverage review, and variant calling. For prepared consensus or aligned BAM/CRAM files, `run_dna_umi_panel_variants.py` can produce QC summaries and a checklist of evidence to review for low-allele-fraction calls.

Before starting, confirm the panel, target BED, UMI layout, reference build, and intended use. The local runner relies on an available fgbio/samtools/bcftools backend; without it, consensus-BAM VCF outputs are not produced. Low-frequency calls need review of molecular support, strand or duplex evidence, and target dropout. Ordinary germline analysis without molecular consensus belongs to a different skill.

## Install

### Codex (native platform)

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

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

### Claude Code

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

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

### Cursor

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

### GitHub Copilot

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

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

### Gemini CLI

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

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/ngs-dna-umi-panel-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-umi-panel-variants/SKILL.md

## When to use it
- plan a UMI-aware targeted DNA panel workflow
- review target coverage and family-size distribution
- separate raw, molecular, and consensus depth
- prepare an evidence checklist for low-frequency calls

## Example prompts
- Plan a UMI-based DNA panel workflow and list the inputs that need confirmation.
- Review prepared consensus BAM files for this panel and summarize target coverage.
- Draft a low-frequency variant review plan that includes duplex support and panel QC.

## Source text · SKILL.md · MIT

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BEGIN THIRD-PARTY FILE 04d6ed68bba65d77
````text
---
name: ngs-dna-umi-panel-variants
description: Run or plan targeted DNA panel variant workflows that use UMIs, duplex consensus reads, molecular barcodes, low-frequency calling, target coverage, and panel-specific QC.
---

# UMI Panel DNA Variants

Use this skill for targeted DNA panels where molecular barcodes, UMIs, duplex consensus, or low-frequency allele detection are central to the analysis. If the panel is ordinary germline calling without molecular consensus, use `ngs-dna-germline-variants`.

## Essential Inputs

Confirm:

- panel/capture kit name and target BED
- UMI layout: inline read, index read, single UMI, duplex UMI, or unknown
- whether consensus reads have already been generated
- FASTQ/BAM input and pairing convention
- reference build and panel-specific annotation requirements
- minimum allele fraction goal and intended use: screening, research, validation, or exploratory
- positive/negative controls and expected spike-ins when available

## Route

Use a lab-validated panel workflow when provided. For public-tool planning, combine FASTQ QC, UMI extraction/consensus generation, alignment, target coverage QC, and variant calling as separate audited stages.

Preflight command:

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

For compact local checks from prepared consensus or alignment BAM/CRAM files, use the dedicated UMI panel runner:

```bash
python plugins/ngs-analysis/scripts/run_dna_umi_panel_variants.py \
  --sample-sheet umi_panel_samples.tsv \
  --reference-fasta reference.fa \
  --target-bed panel_targets.bed \
  --umi-mode duplex \
  --umi-tag RX \
  --execute
```

This writes the consensus/variant command plan, molecular-consensus state, low-frequency calling settings, visualization index, `qc/umi_postrun_summary.{tsv,json}`, `qc/umi_molecular_evidence_contract.{tsv,json}`, and consensus-BAM VCF outputs when the local fgbio/samtools/bcftools backend is available. The post-run summary parses consensus flagstat, target coverage, bcftools stats, and family-size/duplex files when present; missing metrics stay explicit in the notes column. The molecular evidence contract keeps the low-AF review requirements visible per sample: consensus BAM, family-size or molecule-support metrics, variant stats, hotspot review, and duplex review.

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

- Do not trim or discard UMI bases until their layout and destination are known.
- Separate raw read depth from unique molecular depth and consensus depth.
- Track on-target rate, coverage uniformity, family size distribution, strand/duplex support, and per-target dropout.
- Low allele fraction calls require stronger artifact review than ordinary germline calls.
````
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