IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies.

IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies.
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DOI:
10.1093/molbev/msu300
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发表时间:
2015-01
影响因子:
10.7
通讯作者:
Minh BQ
Minh BQ
中科院分区:
生物学1区
文献类型:
--
作者:
Nguyen LT;Schmidt HA;von Haeseler A;Minh BQ

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大型系统发育学数据集需要快速的树推理方法,特别是对于最大似然(ML)系统发育。快速程序是存在的,但由于寻找最佳树的固有启发式方法,目前还不清楚是否找到了最佳树。因此,需要采用不同的搜索策略来查找ML树并且与当前可用的ML程序一样快的附加方法。我们证明了爬山方法和随机摄动方法的结合可以在时间上有效地实现。如果我们允许与RAxML和PhyML相同的CPU时间,那么我们的软件IQ-tree在62.2%到87.1%的研究比对中发现了更高的可能性,从而有效地探索了树空间。如果使用IQ树停止规则,RAxML和PhyML分别在75.7%和47.1%的DNA比对和42.2%和100%的蛋白质比对中更快。然而,IQ-树获得较高似然的范围提高到了73.3-97.1%。智商树可以在http://www.cibiv.at/software/iqtree.上免费获得
Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3–97.1%. IQ-TREE is freely available at http://www.cibiv.at/software/iqtree.
DOI: 10.1093/molbev/mst024
发表时间: 2013-05
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