gwascatalog/studies

GWAS Catalog Studies

Dataset Description

This dataset contains study-level metadata from the NHGRI-EBI GWAS Catalog, 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, 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

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)
• —genomic coordinates
• —gene identifiers
• —standardised ancestry label framework

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.

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.

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.

@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. 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.