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MubasherMohammed
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variant-annotation

Annotate VCF variants with Ensembl VEP, ClinVar, and gnomAD data.

Updated May 10, 2026
Search Tags:#bioinformatics#genomics#vcf#clinvar#gnomad#variant annotation#ensembl vep
One-click install
npx skills add https://github.com/MubasherMohammed/opencode-BioInfo --skill variant-annotation-mubashermohammed
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: variant-annotation
Source: https://github.com/MubasherMohammed/opencode-BioInfo/tree/main/python/skills/variant-annotation
Command: npx skills add https://github.com/MubasherMohammed/opencode-BioInfo --skill variant-annotation-mubashermohammed

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pysam, requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill annotates VCF variants and provides prioritized findings by integrating Ensembl VEP, ClinVar, and gnomAD data, aiding in variant interpretation and prioritization.

Core Features & Use Cases

  • VEP Annotation: Utilizes Ensembl VEP to annotate variants with functional effects.
  • ClinVar Significance: Integrates ClinVar data to identify clinical significance of variants.
  • Population Frequency: Includes gnomAD data to assess population frequency of variants.
  • Prioritization: Assigns a numeric priority score and tier based on various criteria.
  • Use Case: When analyzing genetic variants, this Skill can be used to quickly identify variants of interest by prioritizing those with significant clinical impact and population frequency.

Quick Start

Annotate the VCF file 'variants.vcf' and generate a report.

Frequently Asked Questions about variant-annotation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I annotate VCF variants with ClinVar and gnomAD data?▼

Variant annotation assigns a numeric priority score and tier to genetic variants by evaluating their functional effects from VEP, clinical significance from ClinVar, and population frequency from gnomAD. This prioritization helps identify variants with significant clinical impact.

Can I prioritize genetic variants based on clinical significance and population frequency?▼

Yes, variant prioritization assigns a numeric priority score and tier based on clinical significance from ClinVar and population frequency from gnomAD. This allows you to quickly identify variants of interest with significant clinical impact during bioinformatics analysis.

Do I need pysam and requests to annotate variants with Ensembl VEP?▼

Yes, you need Python with the pysam and requests libraries installed to perform variant annotation. These dependencies are required for data retrieval from Ensembl VEP, ClinVar, and gnomAD databases during the annotation workflow.

What's the best way to interpret genetic variants for clinical impact?▼

The best way to interpret genetic variants is by integrating Ensembl VEP functional effects, ClinVar clinical significance, and gnomAD population frequency data. This combined approach provides prioritized findings that highlight variants with significant clinical impact.

Does variant annotation work with standard VCF files for bioinformatics analysis?▼

Yes, variant annotation works with standard VCF files as input to query Ensembl VEP, ClinVar, and gnomAD databases. It generates a report with annotated variants and prioritized findings suitable for bioinformatics analysis workflows.

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