gwas-catalog

Intersect GWAS variants with ENCODE regulatory elements using BED files.

26|5|Updated Mar 8, 2026

Search Tags:#genetics #regulatory #gwas #variant #encode #functional annotation

Ready to run

npx skills add https://github.com/ammawla/encode-toolkit --skill gwas-catalog

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: gwas-catalog
Source: https://github.com/ammawla/encode-toolkit/tree/main/plugin/skills/gwas-catalog
Command: npx skills add https://github.com/ammawla/encode-toolkit --skill gwas-catalog

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps researchers link genome-wide association study (GWAS) results to functional genomic annotations from ENCODE by identifying overlaps and potential causal regulatory variants.

Core Features & Use Cases

GWAS Data Retrieval: Fetches GWAS associations, variants, and study information via the GWAS Catalog REST API.
ENCODE Data Integration: Provides access to ENCODE experimental data such as peaks for histone modifications, open chromatin, and transcription factor binding in relevant tissues.
Genomic Intersection: Enables intersection of GWAS variants and LD proxies with ENCODE regulatory elements to prioritize causal variants.
Use Case: A researcher analyzing type 2 diabetes can identify GWAS variants overlapping pancreatic islet enhancers, thus pinpointing regulatory mechanisms.

Quick Start

Input GWAS-associated variants into this Skill to locate corresponding regulatory elements and understand their functional context within ENCODE datasets.

Frequently Asked Questions about gwas-catalog

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

FAQPage Schema

How do I overlap GWAS variants with ENCODE regulatory elements to find causal variants?▼

To overlap GWAS variants with ENCODE regulatory elements, you input GWAS-associated variants and the Skill intersects them with ENCODE peak files in BED format. This identifies overlapping regulatory elements to help pinpoint potential causal variants for disease research.

Can I fetch GWAS associations and study metadata directly from the GWAS Catalog REST API?▼

Yes, you can fetch GWAS associations, variants, and study information directly from the GWAS Catalog REST API. The Skill retrieves this data automatically to support subsequent genomic intersection and functional annotation analysis.

What ENCODE functional annotations are available for intersecting with GWAS variants?▼

Available ENCODE functional annotations include experimental peak data for histone modifications, open chromatin regions, and transcription factor binding sites. These are provided in BED format for intersection with GWAS variants to prioritize disease-relevant regulatory elements.

Do I need BED files and bedtools to perform genomic intersection of GWAS and ENCODE data?▼

Yes, you need ENCODE peak files in BED format and the bedtools dependency to perform genomic intersection. The Skill uses bedtools to intersect input GWAS variants and LD proxies with ENCODE regulatory elements for variant prioritization.

What's the best way to prioritize disease-relevant regulatory variants from GWAS results?▼

The best way to prioritize disease-relevant regulatory variants is integrating GWAS results with ENCODE functional genomic annotations. By identifying overlaps between GWAS variants and tissue-specific regulatory elements, you can pinpoint causal regulatory mechanisms.

How does integrating GWAS and ENCODE data help interpret type 2 diabetes variants?▼

Integrating GWAS and ENCODE data helps interpret type 2 diabetes variants by identifying GWAS variants that overlap pancreatic islet enhancers. This intersection highlights specific regulatory mechanisms and functional contexts relevant to the disease.