Genome scans for detecting footprints of local adaptation using a Bayesian factor model.

ABSTRACT: There is a considerable impetus in population genomics to pinpoint loci involved in local adaptation. A powerful approach to find genomic regions subject to local adaptation is to genotype numerous molecular markers and look for outlier loci. One of the most common approaches for selection scans is based on statistics that measure population differentiation such as FST. However, there are important caveats with approaches related to FST because they require grouping individuals into populations and they additionally assume a particular model of population structure. Here, we implement a more flexible individual-based approach based on Bayesian factor models. Factor models capture population structure with latent variables called factors, which can describe clustering of individuals into po

SUBMITTER: Duforet-Frebourg N 

PROVIDER: S-EPMC4137708 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature