The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource

TLDR

The NHGRI‑EBI GWAS Catalog is a FAIR knowledgebase that aggregates over 45 000 published GWAS, more than 40 000 full‑summary‑statistics datasets, and >5 000 traits, serving >200 000 users annually amid a rapidly expanding GWAS data volume. The Catalog curates data from publications and author submissions via a new portal, has upgraded software to scale with growing data, expanded to include sequencing‑based, gene‑based, and CNV analyses, and enhanced interoperability through links to external resources and a standard GWAS format. Community outreach has boosted the sharing of datasets for under‑represented traits such as cancer and highlighted the persistent lack of population diversity in GWAS.

Abstract

Abstract The NHGRI-EBI GWAS Catalog (www.ebi.ac.uk/gwas) is a FAIR knowledgebase providing detailed, structured, standardised and interoperable genome-wide association study (GWAS) data to >200 000 users per year from academic research, healthcare and industry. The Catalog contains variant-trait associations and supporting metadata for >45 000 published GWAS across >5000 human traits, and >40 000 full P-value summary statistics datasets. Content is curated from publications or acquired via author submission of prepublication summary statistics through a new submission portal and validation tool. GWAS data volume has vastly increased in recent years. We have updated our software to meet this scaling challenge and to enable rapid release of submitted summary statistics. The scope of the repository has expanded to include additional data types of high interest to the community, including sequencing-based GWAS, gene-based analyses and copy number variation analyses. Community outreach has increased the number of shared datasets from under-represented traits, e.g. cancer, and we continue to contribute to awareness of the lack of population diversity in GWAS. Interoperability of the Catalog has been enhanced through links to other resources including the Polygenic Score Catalog and the International Mouse Phenotyping Consortium, refinements to GWAS trait annotation, and the development of a standard format for GWAS data.