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

ABSTRACT:

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

SUBMITTER: Limpiti T 

PROVIDER: S-EPMC3148578 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature