Efficient Bayesian inference under the structured coalescent.

ABSTRACT:

Motivation

Population structure significantly affects evolutionary dynamics. Such structure may be due to spatial segregation, but may also reflect any other gene-flow-limiting aspect of a model. In combination with the structured coalescent, this fact can be used to inform phylogenetic tree reconstruction, as well as to infer parameters such as migration rates and subpopulation sizes from annotated sequence data. However, conducting Bayesian inference under the structured coalescent is impeded by the difficulty of constructing Markov Chain Monte Carlo (MCMC) sampling algorithms (samplers) capable of efficiently exploring the state space.

Results

In this article, we present a new MCMC sampler capable of sampling from posterior distributions over structured trees: timed phylo

SUBMITTER: Vaughan TG 

PROVIDER: S-EPMC4207426 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature