ExaBayes: Massively Parallel Bayesian Tree Inference for the Whole-Genome Era

By Andre J. Aberer, Kassian Kobert, Alexandros Stamatakis. Molecular biology and evolution, 2014

448 citations recorded by the source corpus.

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.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/d894f0dbef1d6f91cdb89aee2d5cffe830b999f4

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Citations in the corpus

StarBEAST2 Brings Faster Species Tree Inference and Accurate Estimates of Substitution Rates (2016, methodology): “Bayesian methods, such as ExaBayes and BEAST (Aberer et al., 2014; Drummond and Rambaut, 2007), will instead return a distribution of trees which are probable given the combined sequence alignment, a set of priors, and the same likelihood function.”
Owlflies are derived antlions: anchored phylogenomics supports a new phylogeny and classification of Myrmeleontidae (Neuroptera) (2018, methodology): “4 (Aberer et al., 2014) and under maximum likelihood (ML) in raxml v. 8.2 (Stamatakis, 2014).”
Evolutionary History of the Hymenoptera. (2017, methodology): “We completed three independent ExaBayes runs with four coupled MCMC chains each.”