Fast admixture analysis and population tree estimation for SNP and NGS data.

ABSTRACT:

Motivation

Structure methods are highly used population genetic methods for classifying individuals in a sample fractionally into discrete ancestry components.

Contribution

We introduce a new optimization algorithm for the classical STRUCTURE model in a maximum likelihood framework. Using analyses of real data we show that the new method finds solutions with higher likelihoods than the state-of-the-art method in the same computational time. The optimization algorithm is also applicable to models based on genotype likelihoods, that can account for the uncertainty in genotype-calling associated with Next Generation Sequencing (NGS) data. We also present a new method for estimating population trees from ancestry components using a Gaussian approximation. Using coalescence simul

SUBMITTER: Cheng JY 

PROVIDER: S-EPMC6543773 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature