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clinvar-annotation

Map ClinVar variants to ENCODE regulatory regions for disease association.

26|5|Updated Mar 8, 2026
Search Tags:#genomics#disease#regulatory#clinical#variant#clinvar#ENCODE
One-click install
npx skills add https://github.com/ammawla/encode-toolkit --skill clinvar-annotation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clinvar-annotation
Source: https://github.com/ammawla/encode-toolkit/tree/main/plugin/skills/clinvar-annotation
Command: npx skills add https://github.com/ammawla/encode-toolkit --skill clinvar-annotation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables users to identify and analyze clinically significant variants within ENCODE-regulatory regions, facilitating understanding of non-coding disease mechanisms and variants' clinical relevance.

Core Features & Use Cases

  • Variant Overlap Analysis: Cross-references ClinVar pathogenic, likely pathogenic, and VUS variants with ENCODE experimental genomic elements such as enhancers, promoters, and insulators.
  • Clinical Impact Assessment: Assists in prioritizing non-coding variants for further functional validation or clinical interpretation, especially in tissue-specific contexts.
  • Use Case: For example, identifying pathogenic variants in pancreatic enhancer regions that overlap with ENCODE H3K27ac peaks, to support diagnosis or research in neonatal diabetes.

Quick Start

Query ClinVar for pathogenic variants in the gene BRCA1 and cross-reference with ENCODE H3K27ac peaks in breast tissue to find potential regulatory disease variants.

Frequently Asked Questions about clinvar-annotation

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

FAQPage Schema
How do I link ClinVar disease variants to ENCODE regulatory regions?▼

To link ClinVar disease variants to ENCODE regulatory regions, cross-reference ClinVar pathogenic variants with ENCODE experimental elements like enhancers and promoters to identify non-coding variants associated with diseases.

What is the best way to analyze non-coding variants for clinical impact?▼

Analyzing non-coding variants for clinical impact involves mapping ClinVar pathogenic or VUS variants against ENCODE peak datasets across tissues to prioritize variants for functional validation or clinical interpretation.

Can I identify pathogenic variants in specific tissue regulatory elements?▼

Yes, you can identify pathogenic variants in specific tissue regulatory elements by querying ClinVar for disease variants and cross-referencing them with ENCODE H3K27ac peaks or other functional genomic elements in target tissues.

How do I find clinically significant variants overlapping ENCODE enhancers?▼

Finding clinically significant variants overlapping ENCODE enhancers uses the ClinVar API to fetch pathogenic and likely pathogenic variants, then checks their overlap with ENCODE experimental genomic elements to reveal regulatory disease mechanisms.

Does this approach work for prioritizing non-coding variants in neonatal diabetes research?▼

Yes, this approach works for prioritizing non-coding variants in neonatal diabetes research by identifying pathogenic variants in pancreatic enhancer regions overlapping with ENCODE H3K27ac peaks to support clinical diagnosis.

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