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• W2116777908 abstract "Association mapping for complex diseases using unrelated individuals can be more powerful than family-based analysis in many settings. In addition, this approach has major practical advantages, including greater efficiency in sample recruitment. Association mapping may lead to false-positive findings, however, if population stratification is not properly considered. In this paper, we propose a method that makes it possible to infer the number of subpopulations by a mixture model, using a set of independent genetic markers and then testing the association between a genetic marker and a trait. The proposed method can be effectively applied in the analysis of both qualitative and quantitative traits. Extensive simulations demonstrate that the method is valid in the presence of a population structure." @default.
• W2116777908 created "2016-06-24" @default.
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• W2116777908 date "2002-08-01" @default.
• W2116777908 modified "2023-10-08" @default.
• W2116777908 title "Association mapping, using a mixture model for complex traits" @default.
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• W2116777908 doi "https://doi.org/10.1002/gepi.210" @default.
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