Intersect GWAS variants with ENCODE regulatory elements using BED files.
npx skills add https://github.com/ammawla/encode-toolkit --skill gwas-catalog
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
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.
Input GWAS-associated variants into this Skill to locate corresponding regulatory elements and understand their functional context within ENCODE datasets.
High-intent search queries and answers about installing and using this skill.
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.
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.
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.
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.
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.
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.
nahisahoRetrieve GWAS Catalog associations, traits, and study metadata via the NHGRI-EBI REST API.
ammawlaAnalyze genetic variant overlaps with ENCODE regulatory elements and clinical data.
ammawlaIntegrate ENCODE regulatory elements and GWAS data to interpret non-coding disease variants.
ammawlaLink ENCODE genomic experiments to PubMed, ClinVar, GWAS Catalog, GTEx, and Ensembl.
