AWclust: point-and-click software for non-parametric population structure analysis |
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Authors: | Xiaoyi Gao Joshua D Starmer |
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Affiliation: | (1) Miami Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136, USA;(2) Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA;(3) Curriculum in Toxicology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA |
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Abstract: | Background Population structure analysis is important to genetic association studies and evolutionary investigations. Parametric approaches, e.g. STRUCTURE and L-POP, usually assume Hardy-Weinberg equilibrium (HWE) and linkage equilibrium among loci in sample population individuals. However, the assumptions may not hold and allele frequency estimation may not be accurate in some data sets. The improved version of STRUCTURE (version 2.1) can incorporate linkage information among loci but is still sensitive to high background linkage disequilibrium. Nowadays, large-scale single nucleotide polymorphisms (SNPs) are becoming popular in genetic studies. Therefore, it is imperative to have software that makes full use of these genetic data to generate inference even when model assumptions do not hold or allele frequency estimation suffers from high variation. |
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