Accurate inference of subtle population structure (and other genetic discontinuities) using principal coordinates.

ABSTRACT:

Background

Accurate inference of genetic discontinuities between populations is an essential component of intraspecific biodiversity and evolution studies, as well as associative genetics. The most widely-used methods to infer population structure are model-based, Bayesian MCMC procedures that minimize Hardy-Weinberg and linkage disequilibrium within subpopulations. These methods are useful, but suffer from large computational requirements and a dependence on modeling assumptions that may not be met in real data sets. Here we describe the development of a new approach, PCO-MC, which couples principal coordinate analysis to a clustering procedure for the inference of population structure from multilocus genotype data.

Methodology/principal findings

PCO-MC uses data from all p

SUBMITTER: Reeves PA 

PROVIDER: S-EPMC2625398 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature