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BMCBI
2011

Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and STRUCTU

9 years 6 months ago
Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and STRUCTU
Background: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used for detecting structure. However, it has not been adequately investigated whether the TW statistic is susceptible to type I error, especially in large, complex datasets. Non-parametric, Principal Component Analysis (PCA) based methods for resolving structure have been developed which rely on the TW test. Although PCA-based methods can resolve structure, they cannot infer ancestry. Model-based methods are still needed for ancestry analysis, but they are not suitable for large datasets. We propose a new structure analysis framework for large datasets. This includes a new heuristic for detecting structure and incorporation of the structure patterns inferred by a PCA method to complement STRUCTURE analysis. Results: A new heuristic called EigenDev for detecting population structure is presented. When tested on si...
Tulaya Limpiti, Apichart Intarapanich, Anunchai As
Added 24 Aug 2011
Updated 24 Aug 2011
Type Journal
Year 2011
Where BMCBI
Authors Tulaya Limpiti, Apichart Intarapanich, Anunchai Assawamakin, Philip J. Shaw, Pongsakorn Wangkumhang, Jittima Piriyapongsa, Chumpol Ngamphiw, Sissades Tongsima
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