Genome Center and Department of Evolution and Ecology, University of California, Davis, CA 95616, USA.
Syst Biol. 2011 Mar;60(2):126-37. doi: 10.1093/sysbio/syq073. Epub 2010 Nov 18.
Numerous simulation studies have investigated the accuracy of phylogenetic inference of gene trees under maximum parsimony, maximum likelihood, and Bayesian techniques. The relative accuracy of species tree inference methods under simulation has received less study. The number of analytical techniques available for inferring species trees is increasing rapidly, and in this paper, we compare the performance of several species tree inference techniques at estimating recent species divergences using computer simulation. Simulating gene trees within species trees of different shapes and with varying tree lengths (T) and population sizes (), and evolving sequences on those gene trees, allows us to determine how phylogenetic accuracy changes in relation to different levels of deep coalescence and phylogenetic signal. When the probability of discordance between the gene trees and the species tree is high (i.e., T is small and/or is large), Bayesian species tree inference using the multispecies coalescent (BEST) outperforms other methods. The performance of all methods improves as the total length of the species tree is increased, which reflects the combined benefits of decreasing the probability of discordance between species trees and gene trees and gaining more accurate estimates for gene trees. Decreasing the probability of deep coalescences by reducing also leads to accuracy gains for most methods. Increasing the number of loci from 10 to 100 improves accuracy under difficult demographic scenarios (i.e., coalescent units ≤ 4N(e)), but 10 loci are adequate for estimating the correct species tree in cases where deep coalescence is limited or absent. In general, the correlation between the phylogenetic accuracy and the posterior probability values obtained from BEST is high, although posterior probabilities are overestimated when the prior distribution for is misspecified.
许多模拟研究已经调查了最大简约法、最大似然法和贝叶斯技术下基因树系统发育推断的准确性。相对而言，物种树推断方法的模拟准确性研究较少。可用于推断物种树的分析技术数量正在迅速增加，在本文中，我们使用计算机模拟比较了几种物种树推断技术在估计近期物种分歧方面的性能。在不同形状的物种树内模拟基因树，并改变树长（T）和种群大小（），以及在这些基因树上进化序列，使我们能够确定在不同的深合并和系统发育信号水平下，系统发育准确性如何变化。当基因树与物种树之间的分歧概率较高（即 T 较小且/或较大）时，使用多物种合并（BEST）的贝叶斯物种树推断表现优于其他方法。随着物种树总长度的增加，所有方法的性能都得到了提高，这反映了减少物种树和基因树之间分歧概率和获得更准确的基因树估计值的综合效益。通过减少深合并的概率也会导致大多数方法的准确性提高。从 10 个增加到 100 个位点可以提高困难的种群动态（即合并单位≤4N(e)）情况下的准确性，但在深合并有限或不存在的情况下，10 个位点足以估计正确的物种树。一般来说，BEST 获得的系统发育准确性与后验概率值之间的相关性很高，尽管在后验分布有误的情况下，后验概率值会被高估。
