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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

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

Aberer Andre J AJ Kobert Kassian K Stamatakis Alexandros A

Molecular biology and evolution 20140818 10

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 ...[more]

PMID: 25135941

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