gwascatalog/associations
GWAS Catalog Associations Dataset Description This dataset contains curated genetic association results from the NHGRI-EBI GWAS Catalog, a manually curated resource of published genome-wide association studies (GWAS). The dataset captures SNP–trait associations reported in peer-reviewed studies. Each row represents an association between a genetic variant (typically a single nucleotide polymorphism, SNP) and a disease or trait reported in a publication. The GWAS… See the full description on the dataset page: https://huggingface.co/datasets/gwascatalog/associations.
GWAS Catalog Associations
Dataset Description
This dataset contains curated genetic association results from the NHGRI-EBI GWAS Catalog, a manually curated resource of published genome-wide association studies (GWAS).
The dataset captures SNP–trait associations reported in peer-reviewed studies. Each row represents an association between a genetic variant (typically a single nucleotide polymorphism, SNP) and a disease or trait reported in a publication.
The GWAS catalog aggregates information from thousands of GWAS publications and standardises metadata about studies, genomic loci, variants, genes, and statistical significance.
This Hugging Face dataset provides a tabular representation of the association records suitable for downstream analysis, machine learning, and genomics research workflows.
Dataset Summary
- Task categories: genomics, biomedical data mining
- Data type: tabular
- Primary domain: genome-wide association studies (GWAS)
- Unit of observation: SNP–trait association
- Source: curated literature database
Typical uses include:
- genomic risk analysis
- variant annotation pipelines
- phenotype–genotype relationship studies
- machine learning on genetic associations
- meta-analysis of GWAS findings
Dataset Structure
Each row corresponds to a reported association between a variant and a trait.
Columns
Curation Process
The GWAS Catalog is curated through a combination of automated and manual processes:
- Literature identification
- Publications describing genome-wide association studies are identified through literature searches and author submissions.
- 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
- Standardisation
- Extracted data are normalized using standardized vocabularies and identifiers where possible, including:
- controlled trait terms, including ontology terms from the Experimental Factor Ontology (EFO)
- genomic coordinates
- gene identifiers
- standardised ancestry label framework
- Annotation
- Variants are annotated with additional genomic information such as:
- mapped genes
- variant context (e.g., intronic, intergenic)
- genomic distances to nearby genes
- Quality control
- Curated records undergo internal quality checks to ensure consistency, correct variant identifiers, and valid genomic annotations.
For more information about the curation process, please see our documentation
The Hugging Face dataset mirrors the tabular association records published by the GWAS Catalog on 2026-03-17.
Bias, Limitations, and Population Representation
Genome-wide association studies have several well-known limitations that may 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
The catalog reflects published associations, which introduces potential bias:
- studies with statistically significant findings are more likely to be published
- null results are often underrepresented
- some loci may appear more frequently because they are studied more extensively
Study Heterogeneity
GWAS included in the catalog differ in:
- sample size
- cohort composition
- genotyping platform
- statistical methodology
- phenotype definitions
These differences can influence reported effect sizes and significance levels.
Summary statistics
This dataset includes only GWAS-significant associations.
Full summary statistics, including variants which fail to meet GWAS significance, are available directly from the GWAS Catalog.
Summary statistics files in the GWAS Catalog undergo extensive quality control steps to improve their reusability.
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, Elliot Sollis, Yue Ji, Elizabeth Lewis, Ala Abid, Karatuğ Ozan Bircan, Peggy Hall, James Hayhurst, Sajo John, Abayomi Mosaku, Santhi Ramachandran, Amy Foreman, Arwa Ibrahim, James McLaughlin, Zoë Pendlington, Ray Stefancsik, Samuel A Lambert, Aoife McMahon, Joannella Morales, Thomas Keane, Michael Inouye, Helen Parkinson, Laura W Harris, The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity, Nucleic Acids Research, Volume 53, Issue D1, 6 January 2025, Pages D998–D1005, https://doi.org/10.1093/nar/gkae1070
@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}
}License
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. We advise consumers of data hosted by the GWAS Catalog to note the license terms of individual datasets, if applicable to their specific use case.
