Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo.

ABSTRACT: The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon--known as heterotachy--can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify t

SUBMITTER: Pagel M 

PROVIDER: S-EPMC2607421 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature