Individual skill
genomics-pro
Genome-scale analysis — variant calling, annotation, GWAS, and structural variation for research and clinical genomics.
skills/genomics-pro/SKILL.md
Source commit faf37c0859ebf627bfcb5225e8057d088691e0ae
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 8, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 56
- Repository last updated
- Oct 10, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agents Repository topic
- ai-agents-automation Repository topic
- ai-skills Repository topic
- awesome Repository topic
- awesome-list Repository topic
- chatgpt Repository topic
- claude-skills Repository topic
- meta-ai Repository topic
- muse-ai Repository topic
- research Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Read excerpt
## Overview
genomics-pro covers analysis at genome scale: whole-genome and whole-exome sequencing, variant
discovery and interpretation, population-scale association studies, and structural variation. Where
bioinformatics-pro handles the general NGS mechanics, this skill goes deep on genomic questions —
what variants exist, what they do, and how they associate with traits or disease.
It spans germline and somatic analysis, single-sample and cohort workflows, and the annotation
resources (ClinVar, gnomAD, COSMIC, dbSNP) that turn a VCF of millions of variants into a shortlist
worth investigating.
## When to use
- Designing a WGS/WES study: coverage targets (30x germline WGS, 100x+ tumor), capture kits,