Bioinformatics Advance Access originally published online on December 17, 2004
Bioinformatics 2005 21(4):456-463; doi:10.1093/bioinformatics/bti191
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Bioinformatics vol. 21 issue 4 © Oxford University Press 2005; all rights reserved.
RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees
1 Department of Computer Science, Technical University of Munich Boltzmannstrasse 3, D-85748 München, Germany
2 Department of Computer Science, University of Heidelberg Im Neuenheimer Feld 348, D-69120 Heidelberg, Germany
*To whom correspondence should be addressed.
Motivation: The computation of large phylogenetic trees with statistical models such as maximum likelihood or bayesian inference is computationally extremely intensive. It has repeatedly been demonstrated that these models are able to recover the true tree or a tree which is topologically closer to the true tree more frequently than less elaborate methods such as parsimony or neighbor joining. Due to the combinatorial and computational complexity the size of trees which can be computed on a Biologist's PC workstation within reasonable time is limited to trees containing approximately 100 taxa.
Results: In this paper we present the latest release of our program RAxML-III for rapid maximum likelihood-based inference of large evolutionary trees which allows for computation of 1.000-taxon trees in less than 24 hours on a single PC processor. We compare RAxML-III to the currently fastest implementations for maximum likelihood and bayesian inference: PHYML and MrBayes. Whereas RAxML-III performs worse than PHYML and MrBayes on synthetic data it clearly outperforms both programs on all real data alignments used in terms of speed and final likelihood values.
Availability Supplementary information: RAxML-III including all alignments and final trees mentioned in this paper is freely available as open source code at http://wwwbode.cs.tum/~stamatak
Contact: stamatak{at}cs.tum.edu
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