Stamatakis A, Ludwig T, Meier H
Department of Computer Science, Technical University of Munich Boltzmannstrasse 3, D-85748 München, Germany.
Bioinformatics. 2005 Feb 15;21(4):456-63. doi: 10.1093/bioinformatics/bti191. Epub 2004 Dec 17.
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. Availability
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
使用最大似然法或贝叶斯推断等统计模型计算大型系统发育树在计算上极其密集。反复证明,这些模型比简约法或邻接法等不太精细的方法更频繁地恢复真实树或拓扑结构更接近真实树的树。由于组合和计算复杂性,生物学家的个人电脑工作站在合理时间内能够计算的树的大小限于包含大约100个分类单元的树。
在本文中,我们展示了我们的程序RAxML-III的最新版本,用于基于最大似然法快速推断大型进化树,该程序允许在单个PC处理器上不到24小时内计算1000个分类单元的树。我们将RAxML-III与当前用于最大似然法和贝叶斯推断的最快实现:PHYML和MrBayes进行比较。虽然RAxML-III在合成数据上的表现比PHYML和MrBayes差,但在所有使用的真实数据比对上,它在速度和最终似然值方面明显优于这两个程序。可用性
RAxML-III包括本文中提到的所有比对和最终树,可作为开源代码在http://wwwbode.cs.tum/~stamatak免费获取。