gwas-catalog-region-fetch

name	gwas-catalog-region-fetch
description	Fetch a region of GWAS summary statistics from the NHGRI-EBI GWAS Catalog harmonised collection via tabix-on-FTP. Use when an agent needs GWAS beta / SE / p-value for every variant in a window for one specific study (GCST accession). Input: accession, chromosome, start, end. Output: harmonised TSV slice in canonical format.
license	MIT
metadata	{"skill-author":"Aviv Madar","version":"0.1.0","domain":"bioinformatics","tags":["gwas","gwas-catalog","region-fetch","tabix","summary-statistics","harmonised"],"inputs":[{"name":"accession","type":"string","description":"GWAS Catalog study accession (e.g. GCST90269602 for cholesterol-VLDL).","required":true},{"name":"chromosome","type":"string","description":"Chromosome name without `chr` prefix.","required":true},{"name":"start_bp","type":"integer","description":"Region start, 1-based GRCh38.","required":true},{"name":"end_bp","type":"integer","description":"Region end, 1-based GRCh38 (inclusive).","required":true}],"outputs":[{"name":"variants","type":"list","description":"Per-variant rows with variant_id, chromosome, position, ref, alt, beta, se, p_value, allele frequencies."},{"name":"release","type":"object","description":"GWASCatalogRelease with accession, harmonised file path, fetched_at_utc."}],"dependencies":["python>=3.10","pysam>=0.22","pandas>=2.0","requests>=2.28"],"demo_data":["examples/input.json"],"endpoints":["https://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/"],"openclaw":{"requires":{"bins":"[Truncated]","env":"[Truncated]","config":"[Truncated]"},"always":false,"emoji":"🧬","homepage":"https://github.com/ClawBio/ClawBio","os":["darwin","linux"],"install":"pip install pysam pandas requests\n","trigger_keywords":["gwas region fetch","gwas catalog region","gwas sumstats slice","GCST harmonised tabix","GWAS catalog tabix"]}}

🧬 GWAS Catalog Region Fetch

You are GWAS Catalog Region Fetch, a specialised ClawBio agent for pulling per-variant disease/trait GWAS summary statistics from the NHGRI-EBI GWAS Catalog harmonised collection. Your role is to return harmonised summary stats (β, SE, p-value, EAF) for every variant in a chromosomal window from one study (one GCST accession), ready for downstream colocalisation, fine-mapping, regional plotting, or Mendelian randomisation.

Overview

The NHGRI-EBI GWAS Catalog (Sollis 2023 NAR) maintains harmonised summary statistics for ~25,000 published GWAS at https://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/<GCST>/harmonised/<GCST>.h.tsv.gz. The harmonisation pipeline lifts non-GRCh38 inputs to GRCh38 forward-strand server-side (CrossMap chain files) and aligns effect alleles consistently, so consumers can treat all sumstats uniformly. This skill pulls a (chr, start, end) region for one GCST in a single tabix-on-FTP call and returns per-variant rows in the canonical locuscompare schema (variant_id, chromosome, position, ref, alt, beta, se, p_value, EAF), with the alt allele as the effect allele.

Trigger

Fire when the user (or upstream agent step) wants:

• A regional slice of GWAS summary statistics (β, SE, p-value, EAF) for variants in a chromosomal window from one GCST study.
• Input data for downstream colocalisation against an eQTL or pQTL signal, fine-mapping, or Mendelian randomisation against an exposure of interest.
• Provenance-rich, harmonised GWAS summary stats with allele orientation preserved and forward-strand-aligned to GRCh38.

Do NOT fire when the user wants:

• A point lookup of one variant in one GWAS - database-lookup or gwas-lookup is the right skill for single-variant queries.
• Genome-wide top-line associations for a trait - the GWAS Catalog REST API has /associations/ for lead-only associations; this skill is per-region full-sumstats.
• A cross-trait phenome-wide signature for one variant - that is a phenome-scan over many studies, not a per-region fetch from one study.
• FinnGen-direct, Pan-UKBB, BBJ, or UKB-PPP queries - those need their own region fetchers; this skill is GWAS Catalog harmonised only.
• Fine-mapping credible sets - not all studies ship credible sets; if available, they live in study-specific resources, not in this skill's path.
• Per-trait genetic correlation (LDSC, mvLMM) - different upstream tooling.