ExaBayes: massively parallel bayesian tree inference for the whole-genome era.
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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 |
REPOSITORIES: biostudies-literature
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