tooluniverse-gwas-study-explorer

Use the compare_gwas_studies function with a trait name like type 2 diabetes to retrieve studies from the GWAS Catalog, filter by sample size and ancestry, and identify replicated versus novel loci. It returns a quality summary including total samples and ancestry diversity.

Call meta_analyze_locus with an rsID and trait to fetch all associations for that SNP, then pool per-study betas using inverse-variance weighting. It reports a combined p-value plus Cochran's Q and I² heterogeneity statistics when effect sizes are available.

When associations lack a usable beta and confidence interval, no formal pooling is performed. The result is marked method descriptive, combined_beta and I² are None, and the reported p-value is simply the smallest reported p, not a meta-analytic one.

I² below 25% indicates low heterogeneity suitable for fixed-effects models, 25-50% is moderate, 50-75% is substantial and favors random-effects, and above 75% suggests meta-analysis may be inappropriate. High values often reflect ancestry or phenotype differences.

Yes, assess_replication takes discovery and replication study accession IDs and checks each discovery locus for presence and significance in the replication study. It classifies each locus as strongly replicated, nominally replicated, or not replicated.

It uses the NHGRI-EBI GWAS Catalog API for study metadata and associations, and the Open Targets Genetics GraphQL API for credible sets, fine-mapping results, and variant allele frequencies. Both are accessed through ToolUniverse tools.