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A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog
Open accessPublished version of a preprint
Abstract
The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog. We confirm known biases and gaps in diversity, and find that African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations. It is our hope that widespread adoption of this framework will lead to improved analysis, interpretation, and integration of human genomics data.
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“Poor generalizability of genetic studies across populations arises from the overwhelming abundance of European descent studies and dearth of well-powered studies in globally diverse populations25–28.”
From Clinical use of current polygenic risk scores may exacerbate health disparities (2019) · cites this paper as [27]
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“These considerations notwithstanding, there are critical needs and challenges for expanding the scale of genetic studies of heritable traits in diverse populations; this is especially apparent in Africa where humans originated and retain the most genetic diversity, as Africans are understudied but disproportionately informative for genetic analyses and evolutionary history27,73.”
From Clinical use of current polygenic risk scores may exacerbate health disparities (2019) · cites this paper as [27]
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Metadata
- Authors
- Morales, J., Welter, D., Bowler, E. H., Cerezo, M., Harris, L. W., McMahon, A. C., Hall, P., Junkins, H. A., Milano, A., Hastings, E., Malangone, C., Buniello, A., Burdett, T., Flicek, P., Parkinson, H., Cunningham, F., Hindorff, L. A., & MacArthur, J. A. L.
- Affiliations
- European Bioinformatics Institute (GB)
- National Institutes of Health (US)
- Corresponding author
- Morales, Joannella
- MacArthur, Jacqueline A. L.
- ORCID
- Venue
- Genome Biology
- Published
- 2018-02-15
- Volume
- 19
- Issue
- 1
- Pages
- 21-21
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC5815218
- OpenAlex
- W2785412624
- Cited by
- 217
- References
- 28
- Citations by year
- 2026: 17 · 2025: 15 · 2024: 28 · 2023: 35 · 2022: 32 · 2021: 31 · 2020: 29 · 2019: 18 · 2018: 10
- FWCI
- 14.08
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Genome biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- European Molecular Biology Laboratory
- National Institutes of Health
- National Human Genome Research Institute (U41HG006104, U41HG007823)
- National Institute of General Medical Sciences
- Topics
- Social Sciences › Anthropology › Race, Genetics, and Society
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Keywords
- GWAS Catalog, ancestry bias, population diversity, African ancestry, genetic association studies
- MeSH terms
- Humans, Genetic Variation, Genomics, Racial Groups, Genome-Wide Association Study
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