ngs-dna-variant-calling — Codex skill: what it does, how to install

---
name: ngs-dna-variant-calling
description: Dispatch WGS, WES, or targeted DNA variant requests to germline, somatic, or UMI-panel skills, then plan public nf-core/sarek, GATK4, DeepVariant, samtools, or bcftools workflows.
---

# DNA Variant Calling

Use this skill as the DNA variant-calling dispatcher for WGS, WES, or targeted DNA panel analysis from FASTQ, BAM, or CRAM. Once the sample model is clear, hand off to the narrow subtype skill.

## Essential Inputs

Confirm:

- data type: WGS, WES, or panel
- sample model: germline single sample, cohort, trio, tumor-only, or tumor-normal
- input type: FASTQ, BAM, or CRAM
- organism and reference genome
- known-sites resources for BQSR, if required
- target BED for WES or panels
- UMI or duplex handling
- desired callers and annotation outputs

## Dispatch

Route by biological/sample model:

- Germline singleton, cohort, family, trio, WGS, WES, or ordinary inherited panel: `ngs-dna-germline-variants`
- Tumor-normal, tumor-only, relapse-baseline, or other cancer somatic calling: `ngs-dna-somatic-variants`
- UMI, duplex, molecular-barcode, or low-frequency targeted panel calling: `ngs-dna-umi-panel-variants`

If the request is ambiguous, ask only for the missing sample model and assay design needed to choose among these three. Do not run one generic variant workflow when the request needs subtype-specific assumptions.

## Public Default

Prefer `nf-core/sarek` for an end-to-end public workflow. Use direct GATK4, DeepVariant, samtools, or bcftools commands only for smaller, focused tasks or when the user explicitly wants a custom pipeline.

## Preflight

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

## Local Execution Package

For a compact BAM/CRAM-to-VCF run with a matching reference FASTA, use the plugin-owned samtools/bcftools runner:

```bash
python plugins/ngs-analysis/scripts/run_dna_variant_calling.py \
  --sample-sheet dna_samples.tsv \
  --reference-fasta reference.fa \
  --region chr20:1-100000 \
  --filter-min-qual 30 \
  --filter-min-site-dp 10 \
  --execute
```

The sample sheet should include `sample` and `bam` or `cram` columns. When `--region` is provided the runner also emits per-base depth plus a callable-loci summary for that interval, and when filter thresholds are provided it emits a soft-filtered VCF alongside the raw calls. This package is suitable for focused local checks and run-envelope generation; subtype skills still own germline, somatic, UMI, reference-resource, cohort, annotation, and workflow assumptions.

This compact runner now writes advisory `resources/resource_plan.json`, `resource_manifest.tsv`, `resource_env.sh`, and `resource_readiness.md` artifacts for the selected genome bundle. Use `--require-resource-plan` when missing registered reference resources should block readiness; otherwise the explicit `--reference-fasta` remains enough for focused local checks.

## Kickoff Pattern

Preflight-first nf-core pattern:

```bash
nextflow run nf-core/sarek \
  -profile test,docker \
  --outdir results/sarek_test
```

Real run skeleton:

```bash
nextflow run nf-core/sarek \
  -profile docker \
  --input samplesheet.csv \
  --outdir results/sarek \
  --genome GRCh38 \
  --tools haplotypecaller,vep
```

For WES/panel data, include the target BED. For tumor-normal data, verify pair metadata before execution. For UMI panels, preserve barcode handling and molecule-level QC.

## Guardrails

- Do not mix genome builds across FASTA, GTF/BED, known sites, and VEP cache.
- Do not download large references without confirming disk space and target path.
- Treat clinical interpretation as out of scope unless the user has a validated clinical workflow.