An ancestry informative marker set for determining continental origin: validation and extension using human genome diversity panels

Case-control genetic studies of complex human diseases can be confounded by population stratification. This issue can be addressed using panels of ancestry informative markers (AIMs) that can provide substantial population substructure information. Previously, we described a panel of 128 SNP AIMs th...

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Veröffentlicht in:BMC genetics 2009-07, Vol.10 (1), p.39-39, Article 39
Hauptverfasser: Nassir, Rami, Kosoy, Roman, Tian, Chao, White, Phoebe A, Butler, Lesley M, Silva, Gabriel, Kittles, Rick, Alarcon-Riquelme, Marta E, Gregersen, Peter K, Belmont, John W, De La Vega, Francisco M, Seldin, Michael F
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Sprache:eng
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Zusammenfassung:Case-control genetic studies of complex human diseases can be confounded by population stratification. This issue can be addressed using panels of ancestry informative markers (AIMs) that can provide substantial population substructure information. Previously, we described a panel of 128 SNP AIMs that were designed as a tool for ascertaining the origins of subjects from Europe, Sub-Saharan Africa, Americas, and East Asia. In this study, genotypes from Human Genome Diversity Panel populations were used to further evaluate a 93 SNP AIM panel, a subset of the 128 AIMS set, for distinguishing continental origins. Using both model-based and relatively model-independent methods, we here confirm the ability of this AIM set to distinguish diverse population groups that were not previously evaluated. This study included multiple population groups from Oceana, South Asia, East Asia, Sub-Saharan Africa, North and South America, and Europe. In addition, the 93 AIM set provides population substructure information that can, for example, distinguish Arab and Ashkenazi from Northern European population groups and Pygmy from other Sub-Saharan African population groups. These data provide additional support for using the 93 AIM set to efficiently identify continental subject groups for genetic studies, to identify study population outliers, and to control for admixture in association studies.
ISSN:1471-2156
1471-2156
DOI:10.1186/1471-2156-10-39