ExaBayes: massively parallel bayesian tree inference for the whole-genome era.

ABSTRACT: Modern sequencing technology now allows biologists to collect the entirety of molecular evidence for reconstructing evolutionary trees. We introduce a novel, user-friendly software package engineered for conducting state-of-the-art Bayesian tree inferences on data sets of arbitrary size. Our software introduces a nonblocking parallelization of Metropolis-coupled chains, modifications for efficient analyses of data sets comprising thousands of partitions and memory saving techniques. We report on first experiences with Bayesian inferences at the whole-genome level using the SuperMUC supercomputer and simulated data.

SUBMITTER: Aberer AJ 

PROVIDER: S-EPMC4166930 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature