GWAS Catalog Samples

Dataset Description

This dataset contains sample-level metadata from the NHGRI-EBI GWAS Catalog, describing the populations included in genome-wide association studies (GWAS).

Each record represents a population sample used within a GWAS study, including information about sample size, ancestry category, and geographic origin. The dataset provides a structured representation of the participant populations contributing to published GWAS results.

Unlike the GWAS Catalog Studies dataset, which focuses on publication-level metadata, and the Associations dataset, which captures SNP–trait associations, the Samples dataset describes the populations and cohorts contributing to GWAS analyses.

This dataset is particularly valuable for understanding genetic ancestry representation in GWAS research, enabling analyses of population diversity, recruitment geography, and ancestry distribution across studies.

Typical research uses include:

• examining ancestry representation in GWAS cohorts
• analysing geographic recruitment patterns in genomic studies
• studying population diversity across GWAS datasets
• assessing ancestry imbalance or underrepresentation in genetic studies
• linking population metadata with study-level and association-level GWAS data

The GWAS Catalog applies a standardised framework for representing ancestry data in genomics studies. For more details, please see:

Morales, J., Welter, D., Bowler, E.H. et al. A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog. Genome Biol 19, 21 (2018). https://doi.org/10.1186/s13059-018-1396-2

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Dataset Summary

• Task categories: genomics, biomedical metadata analysis
• Data type: tabular
• Primary domain: genome-wide association studies (GWAS)
• Unit of observation: GWAS sample population
• Source: curated literature database

Typical uses include:

• analysing ancestry composition of GWAS cohorts
• evaluating population diversity in genomic research
• linking ancestry metadata with GWAS study results
• studying recruitment geography and sampling strategies in GWAS

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Dataset Structure

Each row represents a specific sample population used in a GWAS study, typically corresponding to either the discovery stage or a replication stage cohort.

A single study may contain multiple sample entries representing different cohorts, recruitment locations, or ancestry groups.

Columns

Column	Description
STUDY ACCESSION	Accession identifier assigned to a GWAS study in the GWAS Catalog (e.g., GCST identifiers).
PUBMEDID	PubMed identifier for the publication reporting the GWAS.
FIRST AUTHOR	Last name and initials of the first author of the publication.
DATE	Publication date (online/epub date if available).
INITIAL SAMPLE DESCRIPTION	Description of the discovery-stage GWAS cohort, including sample size and ancestry information.
REPLICATION SAMPLE DESCRIPTION	Description of replication cohort(s) used to validate associations reported in the study.
STAGE	Stage of the GWAS to which the sample description applies (e.g., initial discovery stage or replication stage).
NUMBER OF INDIVIDUALS	Number of individuals included in the sample population.
BROAD ANCESTRAL CATEGORY	High-level ancestry classification assigned to place samples into broader genetic ancestry groups.
COUNTRY OF ORIGIN	Country associated with the ancestral origin of the individuals in the sample.
COUNTRY OF RECRUITMENT	Country where participants were recruited for the study.
ADDITIONAL ANCESTRY DESCRIPTION	Additional descriptors providing more detailed ancestry information for the sample population.

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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
• genomic location information

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

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 ancestry records published by the GWAS Catalog on 2026-03-17.

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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.

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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

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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}
}

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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.