A simulation approach for change-points on phylogenetic trees.

ABSTRACT: We observe n sequences at each of m sites and assume that they have evolved from an ancestral sequence that forms the root of a binary tree of known topology and branch lengths, but the sequence states at internal nodes are unknown. The topology of the tree and branch lengths are the same for all sites, but the parameters of the evolutionary model can vary over sites. We assume a piecewise constant model for these parameters, with an unknown number of change-points and hence a transdimensional parameter space over which we seek to perform Bayesian inference. We propose two novel ideas to deal with the computational challenges of such inference. Firstly, we approximate the model based on the time machine principle: the top nodes of the binary tree (near the root) are replaced by an approxim

SUBMITTER: Persing A 

PROVIDER: S-EPMC4283070 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature