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Overview of Admixture Mapping
Open accessAbstract
Admixture mapping is a powerful method of gene mapping for diseases or traits that show differential risk by ancestry. Admixture mapping has been applied most often to African Americans who trace ancestry to Europeans and West Africans. Recent developments in admixture mapping include improvements in methods to take advantage of higher densities of genetic variants, as well as extensions to admixed populations with three or more ancestral populations, such as Latino Americans. In this unit, the author outlines the key concepts of admixture mapping. The author describes several approaches for inferring local ancestry and provides strategies for performing admixture mapping depending on the study design. Finally, the author compares and contrasts linkage analysis, association analysis, and admixture mapping, with an emphasis on integrating admixture mapping and association testing. Curr. Protoc. Hum. Genet. 76:1.23.1‐1.23.8. © 2013 by John Wiley & Sons, Inc.
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“European Americans are often used as proxies for Europeans in genetic studies.26”
From The genetic ancestry of African Americans, Latinos, and European Americans across the United States (2015) · cites this paper as [26]
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“performed admixture mapping, a technique designed to identify regions of the genome where locus‐ specific ancestry drives variation in a disease trait (Shriner, 2013) that has been helpful in studies of complex diseases, including asthma and breast cancer (Féjerman et al.”
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McFarlane, S. E., & Pemberton, J. M. (2021) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkab274 · Cited by 7
Population structure and selective signature of Kirghiz sheep by Illumina Ovine SNP50 BeadChip
Yang, R., Han, Z., Zhou, W., Li, X., Zhang, X., Zhu, L., Wang, J., Li, X., Zhang, C.-L., Han, Y., et al. (2024) · PeerJ · doi:10.7717/peerj.17980 · Cited by 6
“We conducted an analysis of K values (representing the number of ancestral populations) from two to six using the admixture software (version 1.3.0) ( Shriner, 2023 ; Montana & Hoggart, 2007 ; Tang et al., 2005 ).”
MethodInfluentialSocial and scientific motivations to move beyond groups in allele frequencies: The TOPMed experience
Nelson, S. C., Gogarten, S. M., Fullerton, S. M., Isasi, C. R., Mitchell, B. D., North, K. E., Rich, S. S., Taylor, M. R., Zöllner, S. K., & Sofer, T. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.07.008 · Cited by 6
Giri, A., Hartmann, K. E., Aldrich, M. C., Ward, R. M., Wu, J. M., Park, A. J., Graff, M., Qi, L., Nassir, R., Wallace, R. B., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0178839 · Cited by 6
Marttinen, T.-L. M. (2022) · Journal of Critical Mixed Race Studies · doi:10.5070/c81258341 · Cited by 6
Malta, M. C. F. D. S., Rodrigues, P. S., Zuccherato, L. W., de Souza, F. C. B., Domingues, E. M. F. L., de Souza, V. R., Tarazona‐Santos, E., & Martins, M. L. (2017) · HLA · doi:10.1111/tan.13102 · Cited by 6
Butković, A., & Elena, S. F. (2022) · Frontiers in Systems Biology · doi:10.3389/fsysb.2022.1005758 · Cited by 5
“Another good measure that can be used is admixture mapping, a method that tries to associate an allele with a disease based on ancestry information between different populations (Shriner, 2013).”
MethodThe genetic ancestry of African, Latino, and European Americans across the United StatesPreprint
Bryc, K., Durand, E., Macpherson, J. M., Reich, D., & Mountain, J. L. (2014) · bioRxiv · doi:10.1101/009340 · Cited by 7
Leal, T. P., Waldo, E., Duarte-Zambrano, F., Inca‐Martinez, M., Ramchandra, J., Chaparro-Solano, H. M., Anello, A. E., Borda, V., Gouveia, M. H., dos Santos, D. T., et al. (2025) · medRxiv · doi:10.1101/2025.07.18.25331793 · Cited by 5
PRECISION MEDICINE: FROM DIPLOTYPES TO DISPARITIES TOWARDS IMPROVED HEALTH AND THERAPIES
Crawford, D. C., Morgan, A. A., Denny, J. C., Aronow, B. J., & Brenner, S. E. (2017) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789813235533_0036 · Cited by 4
Spotting genome-wide pigmentation variation in a brown trout admixture contextPreprint
Valette, T., Leitwein, M., LASCAUX, J. M., Desmarais, É., Berrebi, P., & Guinand, B. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.23.217109 · Cited by 6
Cole, S. A., Lyke, M. M., Christensen, C., Newman, D. E., Bagwell, A., Galindo, S., Glenn, J. P., Layne‐Colon, D., Sayers, K., Tardif, S. D., et al. (2024) · American Journal of Primatology · doi:10.1002/ajp.23630 · Cited by 3
O'Toole, B., Simmons, N. B., & Hekkala, E. R. (2020) · Acta Chiropterologica · doi:10.3161/15081109acc2020.22.2.001 · Cited by 3
Old vs. new local ancestry inference in HCHS/SOL: a comparative study
Chen, X., Wang, H., Broce, I., Dale, A. M., Yu, B., Zhou, L. Y., Li, X., Argos, M., Daviglus, M. L., Cai, J., et al. (2025) · Human Molecular Genetics · doi:10.1093/hmg/ddaf093 · Cited by 2
de Aquino, M. M., Xu, C. Y., Engchuan, W., Trost, B., Zhou, X., Miwa, B., Salazar, N. B., Iglar, J., Thiruvahindrapuram, B., Wallich, L., et al. (2026) · Molecular Psychiatry · doi:10.1038/s41380-026-03886-9 · Cited by 2
Simplified detection of genetic background admixture using artificial intelligence
Pauly, R., & Feltus, F. A. (2024) · Clinical Genetics · doi:10.1111/cge.14527 · Cited by 1
Race Differences: A Very Brief Review
Kirkegaard, E. O. W. (2019) · Mankind Quarterly · doi:10.46469/mq.2019.60.2.2 · Cited by 3
Ruiz-Narváez, E. (2021) · Current Opinion in Clinical Nutrition & Metabolic Care · doi:10.1097/mco.0000000000000757 · Cited by 3
Local ancestry inference in heterogeneous populations—Are recent recombination events more relevant?
van Eeden, G., Uren, C., van der Spuy, G. D., Tromp, G. C., & Möller, M. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab300 · Cited by 2
Rivera, W. G. G., Liu, Y., Mirmira, T., Ma, N., Kim, J., Antonio, M. D., Dube, U., Frazer, K. A., & Gymrek, M. (2025) · medRxiv · doi:10.64898/2025.12.29.25343152 · Cited by 2
A comprehensive overview of the biological foundations of ADHD
Folego-Temoteo, I., Lima, Y. C., Grevet, E. H., Vidor, M. V., Tavares, M. E., da Silva, B. S., Bau, C. H. D., & Rovaris, D. L. (2026) · Bioscience Reports · doi:10.1042/bsr20254061 · Cited by 1
“Recognizing this statistical reality is fundamental for a balanced and mature interpretation of biological findings.”
Genetics and Genomics of Preterm Birth
Nadeem, L., Lye, S. J., & Shynlova, O. P. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-813570-9.00015-2 · Cited by 1
Fenech, A. G., Sayers, I., & Portelli, M. A. (2015) · Advances in predictive, preventive and personalised medicine · doi:10.1007/978-3-319-15344-5_9 · Cited by 1
Tardo, L. M., Salter, A. R., Truong-Le, M., Horton, L. A., Blackburn, K. M., & Sguigna, P. V. (2023) · Therapeutic Advances in Chronic Disease · doi:10.1177/20406223231202645 · Cited by 1
Estudio de la relación de la ancestría genética con el riesgo al cáncer colorrectal en Colombia
Criollo, Á., Bohórquez, M., Lott, P. C., Carracedo, Á., Tomlinson, I. P. M., Carvajal‐Carmona, L. G., & Echeverry, M. (2019) · Revista de la Asociación Colombiana de Ciencias Biológicas · doi:10.47499/revistaaccb.v1i31.183 · Cited by 1
Mito-nuclear effects uncovered in admixed populationsPreprint
Zaidi, A. A., & Makova, K. (2018) · bioRxiv · doi:10.1101/349126 · Cited by 1
Modeling of linkage disequilibrium in whole genome genetic association studies
Johnson, R. (2014) · theses.fr (ABES) · doi:10.70675/077a2830z02f9z4591za4e5z254e19208d13
“Review (Shriner 2013) Review (Thompson 2013) Type Software Used Map Citation !”
BackgroundMapeamento por miscigenação em amostra de pacientes brasileiros com insuficiência cardíaca
Cardena, M. M. S. G. (2018) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.5.2018.tde-11092018-134127
Hsu, C., Yang, H., & McGrath, J. A. (2019) · Springer eBooks · doi:10.1007/978-981-32-9791-3_4
Discovery through Diversity: Insights into the Genetics of Lung Function in Latino Youth
Jones, T. K., & Christie, J. D. (2020) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202006-2404ed
“Admixture mapping, a methodology that leverages shared genetic variance and differing allele frequencies among ancestral populations, holds promise for uncovering associations between ancestry at specific genetic loci and disease states (10).”
Background
Metadata
- Authors
- Shriner, D.
- Affiliations
- National Human Genome Research Institute (US)
- Corresponding author
- Shriner, Daniel
- ORCID
- Shriner, Daniel
- Venue
- Current Protocols in Human Genetics
- Publisher
- Wiley
- Published
- 2013-01
- Volume
- 76
- Issue
- 1
- Pages
- 1.23.1-1.23.8
- ISSN
- 1934-8258 (ISSN-L)
- 1934-8266
- PMC
- PMC3556814
- OpenAlex
- W1588484659
- Cited by
- 111
- References
- 24
- Citations by year
- 2026: 6 · 2025: 7 · 2024: 8 · 2023: 9 · 2022: 11 · 2021: 16 · 2020: 10 · 2019: 13 · 2018: 8 · 2017: 11 · 2016: 2 · 2015: 3 · 2014: 7
- FWCI
- 2.65
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Current Protocols in Human Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (Z99 HL999999, Z99 MH999999, Z99 HG999999, 1ziahg200362-15, Z01HG200362))
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- admixture mapping, local ancestry inference, gene mapping, African Americans, Hispanic Americans, linkage analysis, association analysis, admixed populations, genetic variants
- MeSH terms
- Black or African American, Chromosome Mapping, Hispanic or Latino, Humans, Genetic Linkage, Phenotype, Genome, Human, Quantitative Trait Loci, Black People, White People, Genetic Association Studies
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