🧬 Biotech & Pharma · Bioinformatics

Standardize variant calling and annotation

Consistent callers, filters, and annotation sources so variant lists compare across runs.

advanced~50 minBioinformaticiansLab ScientistsRegulatory Affairs

Steps

1Fix caller versions and filter thresholds in writing before processing
2Normalize representations (left-align, split multiallelics) consistently
3Annotate against versioned databases recording exact release dates
4Apply depth/quality filters appropriate to assay type
5Validate a truth-set sample each run before trusting outputs
6Store VCFs with full provenance: sample, pipeline hash, references

Common Pitfalls

▲Annotation databases drifting between analyses
▲Filter tuning per-run destroying comparability

Commands

Install with skills CLI

$ npx skills add aniruddhaadak80/skills --skill bioinformatics-variant-calling-sop

Install globally

$ npx skills add aniruddhaadak80/skills --skill bioinformatics-variant-calling-sop -g

Tags

#variants#genomics#sop#biotech-pharma#bioinformatics

Install this skill

$ npx skills add aniruddhaadak80/skills --skill bioinformatics-variant-calling-sop -a opencode

SKILL.md

# Standardize variant calling and annotation

> Consistent callers, filters, and annotation sources so variant lists compare across runs.

## When to Use This Skill

Consistent callers, filters, and annotation sources so variant lists compare across runs.

## Steps

1. Fix caller versions and filter thresholds in writing before processing
2. Normalize representations (left-align, split multiallelics) consistently
3. Annotate against versioned databases recording exact release dates
4. Apply depth/quality filters appropriate to assay type
5. Validate a truth-set sample each run before trusting outputs
6. Store VCFs with full provenance: sample, pipeline hash, references

## Common Pitfalls

- Annotation databases drifting between analyses
- Filter tuning per-run destroying comparability

View source on GitHub ↗

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