Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia.

ABSTRACT: Searching for genetic variants with unusual differentiation between subpopulations is an established approach for identifying signals of natural selection. However, existing methods generally require discrete subpopulations. We introduce a method that infers selection using principal components (PCs) by identifying variants whose differentiation along top PCs is significantly greater than the null distribution of genetic drift. To enable the application of this method to large datasets, we developed the FastPCA software, which employs recent advances in random matrix theory to accurately approximate top PCs while reducing time and memory cost from quadratic to linear in the number of individuals, a computational improvement of many orders of magnitude. We apply FastPCA to a cohort of 54,73

SUBMITTER: Galinsky KJ 

PROVIDER: S-EPMC4827102 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature