--- license: other license_name: embl-ebi license_link: https://www.ebi.ac.uk/about/terms-of-use/ --- # GWAS Catalog Studies ## Dataset Description This dataset contains study-level metadata from the [NHGRI-EBI GWAS Catalog](https://ebi.ac.uk/gwas), a manually curated repository of published genome-wide association studies (GWAS). Each record corresponds to a single GWAS publication or study entry curated by the GWAS Catalog. Unlike the [GWAS Associations dataset](https://huggingface.co/datasets/gwascatalog/associations), which represents individual SNP–trait associations, this dataset describes the study itself, including publication metadata, sample descriptions, genotyping platforms, traits investigated, and information about available summary statistics. The GWAS Catalog includes all GWAS studies, including those which do not report any significant associations, so some studies may not have corresponding associations in the /associations dataset. The GWAS Catalog aggregates results from thousands of genome-wide association studies and standardises metadata related to studies, cohorts, phenotypes, and genotyping technologies. This Hugging Face dataset provides a tabular representation of study metadata, enabling research workflows such as: * bibliometric analysis of GWAS publications * meta-analysis of GWAS study designs * analysis of cohort composition and population diversity * exploration of genotyping technologies used in GWAS * linking study metadata with association datasets --- ## Dataset Summary * Task categories: genomics, biomedical metadata analysis * Data type: tabular * Primary domain: genome-wide association studies (GWAS) * Unit of observation: GWAS study / publication * Source: curated literature database Typical uses include: * mapping GWAS studies to traits and cohorts * analysing sample sizes and population representation * linking study metadata with variant–trait association records * identifying studies with available summary statistics * studying technological trends in genotyping platforms --- # Dataset Structure Each row represents a single GWAS study entry in the GWAS Catalog. ## Columns | Column | Description | | -------------------------- | ---------------------------------------------------------------------------------------------------------------- | | DATE ADDED TO CATALOG | Date the study was added to the GWAS Catalog. | | PUBMEDID | PubMed identifier for the publication reporting the study. | | FIRST AUTHOR | Last name and initials of the first author of the publication. | | DATE | Publication date (online/epub date if available). | | JOURNAL | Abbreviated journal name in which the study appeared. | | LINK | URL linking to the publication record in PubMed. | | STUDY | Title of the publication reporting the GWAS. | | DISEASE/TRAIT | Disease or trait investigated in the study. | | INITIAL SAMPLE SIZE | Total number of individuals included in the Stage 1 discovery cohort(s) of the GWAS. | | REPLICATION SAMPLE SIZE | Total number of individuals included in replication cohort(s) used to validate associations. | | PLATFORM (SNPS PASSING QC) | Genotyping platform used in the Stage 1 GWAS after quality control filtering of SNPs. | | ASSOCIATION COUNT | Number of SNP–trait associations curated for this study in the GWAS Catalog. | | MAPPED_TRAIT | Standardised Experimental Factor Ontology (EFO) trait mapped to the study phenotype. | | MAPPED_TRAIT_URI | URI identifier corresponding to the mapped Experimental Factor Ontology trait. | | STUDY ACCESSION | Unique accession identifier assigned to the study in the GWAS Catalog (e.g., GCST identifiers). | | GENOTYPING TECHNOLOGY | Genotyping technology used in the study, including array types where applicable (e.g., Immunochip, Exome array). | | COHORT | Discovery-stage cohort(s) included in the study; multiple cohorts may be listed if applicable. | | FULL SUMMARY STATISTICS | Boolean indicator specifying whether full genome-wide summary statistics are available for the study. | | SUMMARY STATS LOCATION | Repository or location where the full summary statistics can be accessed or downloaded. | | GxE | Indicates whether the study includes a genome-wide genotype-by-environment interaction analysis. | --- # Curation Process The GWAS Catalog is curated through a combination of automated and manual processes. ### 1. Literature identification Publications describing genome-wide association studies are identified through: * literature searches * author submissions ### 2. Manual curation Expert curators review publications and extract key information including: * variant identifiers (e.g., rsIDs) * associated traits or diseases * statistical significance metrics * effect sizes * sample descriptions ### 3. Standardisation Extracted data are normalised using standardised vocabularies and identifiers where possible, including: * controlled trait terms from the [Experimental Factor Ontology (EFO)](https://www.ebi.ac.uk/efo/) * genomic coordinates * gene identifiers * standardised ancestry label [framework](https://link.springer.com/article/10.1186/s13059-018-1396-2) ### 4. Annotation Variants are annotated with additional genomic information such as: * mapped genes * variant context (e.g., intronic, intergenic) * genomic distances to nearby genes ### 5. Quality control Curated records undergo internal quality checks to ensure: * consistency across records * correct variant identifiers * valid genomic annotations For more information about the curation process, please see the GWAS Catalog documentation. The Hugging Face dataset mirrors the [tabular studies records published by the GWAS Catalog on 2026-03-17](https://www.ebi.ac.uk/gwas/docs/file-downloads). --- # Bias, Limitations, and Population Representation Genome-wide association studies have several limitations that affect analyses using this dataset. ## Population Bias A large proportion of GWAS studies have historically been conducted with individuals genetically similar to European reference populations. Please note: * genetic associations may not generalise across populations * allele frequencies may differ substantially between ancestries * effect sizes may vary across populations Users should exercise caution when applying results derived from GWAS to diverse populations. ## Publication Bias Because the catalog is derived from published studies, it may reflect: * overrepresentation of statistically significant findings * underrepresentation of null results * bias towards traits that are frequently studied ## Study Heterogeneity GWAS studies vary substantially in: * sample size * cohort composition * phenotype definitions * genotyping platforms * statistical analysis methods These factors may influence comparability across studies. --- # Credits This dataset is derived from the [NHGRI-EBI GWAS Catalog](https://ebi.ac.uk/gwas). We would like to thank: * authors who submit their data to the catalog, including full summary statistics * authors of the original GWAS publications included in the catalog * GWAS Catalog team members, past and present * research participants who contributed data to the underlying genetic studies --- # Citation If you use this dataset in research, please cite the GWAS Catalog publication: Maria Cerezo et al. *The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity.* Nucleic Acids Research, 2025. ```bibtex @article{cerezo2025nhgri, title={The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity}, author={Cerezo, Maria and Sollis, Elliot and Ji, Yue and Lewis, Elizabeth and Abid, Ala and Bircan, Karatu{\u{g}} Ozan and Hall, Peggy and Hayhurst, James and John, Sajo and Mosaku, Abayomi and others}, journal={Nucleic acids research}, volume={53}, number={D1}, pages={D998--D1005}, year={2025}, publisher={Oxford University Press} } ``` --- # Licence The NHGRI-EBI GWAS Catalog and all its contents are available under the [general Terms of Use for EMBL-EBI Services](https://ebi.ac.uk/about/terms-of-use). Summary statistics are made available under CC0 unless otherwise stated. Consumers of data hosted by the GWAS Catalog should review the licence terms of individual datasets where applicable to their specific use case.