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SKILL verified MIT-0 Self-run

Variant Calling

skill-awslabs-hcls-agent-skills-variant-calling · by awslabs

Germline and somatic short-variant calling pipeline for Illumina short-read data. Use when the user mentions BWA, BWA-MEM2, GATK, HaplotypeCaller, Mutect2, VCF, GVCF, VQSR, variant calling, germline, somatic, SNV, or indel calling from FASTQ/BAM.

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Install

$ agentstack add skill-awslabs-hcls-agent-skills-variant-calling

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Variant Calling (GATK4) — Pipeline Skill (Thin Scaffold)

Overview

Adds decision logic for VQSR vs hard filters, WES vs WGS parameter differences, and GATK4-specific gotchas that LLMs frequently get wrong (filter thresholds, GVCF requirements, reference consistency).

Usage

  • Activate when choosing between VQSR and hard filters for a given cohort size
  • Activate when setting up WES vs WGS pipeline parameters
  • Activate when running Mutect2 tumor/normal or tumor-only somatic calling

Core Concepts

Decision Logic

Germline calling strategy:
├── Single sample, no future joint calling → HaplotypeCaller direct VCF
└── Cohort (≥2 samples) → HaplotypeCaller -ERC GVCF → GenomicsDBImport → GenotypeGVCFs

Filtering strategy:
├── ≥30 WGS samples OR ≥30 WES exomes → VQSR
└──  60.0 | > 200.0 |
| MQ |  3.0 | > 10.0 |

**VQSR truth sensitivity levels:**
- SNPs: 99.7
- Indels: 99.0
- Indel `--max-gaussians 4` (fewer training variants than SNPs)

**VQSR annotations:** `-an QD -an FS -an MQ -an MQRankSum -an ReadPosRankSum -an SOR`

**Mutect2 essentials:**
- `--germline-resource af-only-gnomad.hg38.vcf.gz`
- `--panel-of-normals pon.vcf.gz` (essential for tumor-only)
- `--f1r2-tar-gz` → `LearnReadOrientationModel` (FFPE/OxoG artifacts)
- `GetPileupSummaries` + `CalculateContamination` before `FilterMutectCalls`

## Common Mistakes

- **Wrong:** Aligning without proper `@RG` headers (missing ID, SM, PL, LB)
  **Right:** Always specify at alignment: `-R '@RG\tID:x\tSM:x\tPL:ILLUMINA\tLB:x'`
  **Why:** GATK refuses to run or silently merges samples when SM tags are wrong

- **Wrong:** Running HaplotypeCaller without `-ERC GVCF` for cohort analysis
  **Right:** Always produce GVCFs when joint genotyping will be performed
  **Why:** Regular VCFs cannot be joint-genotyped; must re-call from BAM

- **Wrong:** Reusing SNP hard-filter thresholds for indels (e.g., `FS > 60` for indels)
  **Right:** Use `FS > 200` for indels, `FS > 60` for SNPs
  **Why:** Indels tolerate higher strand bias; SNP thresholds over-filter real indels

- **Wrong:** Applying VQSR to <30 samples
  **Right:** Use hard filters for small cohorts
  **Why:** VQSR needs many variants to train its Gaussian mixture model

- **Wrong:** Subsetting `--known-sites` VCFs to WES capture BED for BQSR
  **Right:** Use genome-wide known-sites; only restrict analysis intervals via `-L`
  **Why:** BQSR needs genome-wide known sites to model base quality errors

- **Wrong:** Skipping `samtools index` between GATK steps
  **Right:** Index after every BAM-producing step
  **Why:** GATK requires BAM indices; missing them causes immediate failure

- **Wrong:** Mixing reference files from different genome builds
  **Right:** Ensure ref.dict, ref.fa.fai, BWA index, and all VCFs match the same build
  **Why:** Mismatched dictionaries cause silent failures or cryptic errors

- **Wrong:** Running Mutect2 tumor-only without a panel of normals
  **Right:** Always provide `--panel-of-normals` for tumor-only calling
  **Why:** Without PoN, recurrent sequencing artifacts are called as somatic mutations

## Response Format

- Lead with the command or code the user needs — explain after
- Structure as: confirm inputs → working code → key parameters explained → gotchas
- One complete working example per task; do not show every alternative
- Keep code comments minimal and functional (what, not why-it-exists)
- Target: 50-100 lines of code with brief surrounding explanation

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [awslabs](https://github.com/awslabs)
- **Source:** [awslabs/hcls-agent-skills](https://github.com/awslabs/hcls-agent-skills)
- **License:** MIT-0

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.