Individual skill
variant-annotation
Annotating genetic variants — consequence prediction, population frequency, and clinical interpretation.
skills/variant-annotation/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)
- 54
- 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
- engineering 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
variant-annotation covers turning raw variant calls into interpretable information: predicting
molecular consequence, filtering by population frequency, scoring deleteriousness, and
connecting variants to phenotype and clinical significance. Annotation is where a VCF of
millions of variants becomes a shortlist — and where most interpretation errors originate.
## When to use
- Annotating VCFs: VEP, ANNOVAR, snpEff — choosing and configuring.
- Consequence prediction: coding, splice, regulatory effects.
- Population frequency filtering: gnomAD, 1000 Genomes, population-specific databases.
- Deleteriousness scores: CADD, REVEL, SIFT, PolyPhen, SpliceAI.
- Clinical interpretation: ClinVar, ACMG classification support.