gwas-database

What problem does it solve?

Manually sifting through thousands of GWAS publications to find specific SNP-trait associations or summary statistics is incredibly time-consuming and error-prone. This Skill automates access to the NHGRI-EBI GWAS Catalog, streamlining genetic epidemiology, polygenic risk score development, and systematic reviews of genetic evidence.

Core Features & Use Cases

• Comprehensive Association Search: Find SNPs associated with diseases or traits by rs ID, gene, or genomic region, with options to filter by p-value and population.
• Summary Statistics Access: Retrieve full genome-wide association data, including p-values, effect sizes, and allele frequencies, for studies that have deposited complete data.
• Trait & Study Metadata: Access detailed information about phenotypes, diseases (mapped to EFO), and GWAS publications, including author, publication date, and ancestry.
• Use Case: A genetic epidemiologist needs to identify all genome-wide significant variants associated with "type 2 diabetes" and retrieve their effect sizes for a polygenic risk score model. This skill can query the catalog, filter by significance, and extract the precise data needed for downstream analysis.

Quick Start

To find associations for "type 2 diabetes" (EFO_0001360): import requests trait_id = "EFO_0001360" url = f"https://www.ebi.ac.uk/gwas/rest/api/efoTraits/{trait_id}/associations" response = requests.get(url, headers={"Content-Type": "application/json"}) data = response.json() print(f"Found {data.get('page', {}).get('totalElements', 0)} associations")