VEP Variant Annotator Skill

SkillDatabases & data

Variant Effect Predictor skill for comprehensive variant annotation with clinical database integration

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the VEP Variant Annotator Skill skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/bioinformatics/skills/vep-variant-annotator/SKILL.md and read by ahel’s review.

Purpose

Provide comprehensive variant annotation using Variant Effect Predictor with clinical database integration.

Capabilities

Functional consequence prediction
Population frequency annotation (gnomAD)
Clinical database integration (ClinVar, COSMIC)
Custom annotation plugins
Pathogenicity score integration (CADD, REVEL)
Regulatory region annotation

Usage Guidelines

Configure VEP with relevant annotation sources
Include population frequency databases
Add clinical databases for interpretation
Use pathogenicity predictors for prioritization
Document annotation database versions
Update annotations regularly

Dependencies

Ensembl VEP
ANNOVAR
SnpEff

Process Integration

Whole Genome Sequencing Pipeline (wgs-analysis-pipeline)
Clinical Variant Interpretation (clinical-variant-interpretation)
Pharmacogenomics Analysis (pharmacogenomics-analysis)
Rare Disease Diagnostic Pipeline (rare-disease-diagnostics)

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: vep-variant-annotator
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter