Multi-locus analysis of genomic time series data from experimental evolution.

ABSTRACT: Genomic time series data generated by evolve-and-resequence (E&R) experiments offer a powerful window into the mechanisms that drive evolution. However, standard population genetic inference procedures do not account for sampling serially over time, and new methods are needed to make full use of modern experimental evolution data. To address this problem, we develop a Gaussian process approximation to the multi-locus Wright-Fisher process with selection over a time course of tens of generations. The mean and covariance structure of the Gaussian process are obtained by computing the corresponding moments in discrete-time Wright-Fisher models conditioned on the presence of a linked selected site. This enables our method to account for the effects of linkage and selection, both along the geno

SUBMITTER: Terhorst J 

PROVIDER: S-EPMC4388667 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature