RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees

TLDR

Maximum‑likelihood and Bayesian phylogenetic inference are computationally intensive but more accurate than simpler methods such as parsimony or neighbor‑joining. This study introduces RAxML‑III, a fast maximum‑likelihood program capable of inferring 1,000‑taxon trees in under 24 hours on a single PC. RAxML‑III is compared to the fastest existing ML and Bayesian tools, PHYML and MrBayes, and is freely available as open‑source code. On real data, RAxML‑III outperforms PHYML and MrBayes in speed and likelihood, though it is less accurate on synthetic datasets.

Abstract

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.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. AvailabilityRAxML-III including all alignments and final trees mentioned in this paper is freely available as open source code at http://wwwbode.cs.tum/~[e-mail].