Implementing and testing Bayesian and maximum-likelihood supertree methods in phylogenetics.
Implementing and testing Bayesian and maximum-likelihood supertree methods in phylogenetics.
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DOI：
10.1098/rsos.140436
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发表时间：
2015-08
影响因子：
3.5
通讯作者：
Pisani D
中科院分区：
文献类型：
--
作者：
Akanni WA;Wilkinson M;Creevey CJ;Foster PG;Pisani D
自超树出现以来，超树已经越来越多地用于需要系统发育框架的大规模进化研究，并且已经投入了大量的努力来开发各种超树方法（SMs）。超树理论的最新进展允许实现最大似然（ML）和贝叶斯SMs，基于使用指数分布来模拟输入树和超树之间的不一致。与常用的非参数SMs相比，这种方法有望具有优势，例如具有简约性的矩阵表示（MRP）。我们研究了ML和贝叶斯SMs的新实现，并将它们与一些当前可用的替代方法进行了比较。比较包括先前用于调查SMs在输入树形状和大小方面的偏差的假设示例，以及基于从文献中收获的树木或从系统基因组规模数据推断的树木的实证研究。我们的结果没有提供大小或形状偏差的证据，并证明贝叶斯方法是MRP和其他非参数方法的可行替代方案。输入树可能性的计算允许采用树拓扑的标准测试（例如，近似无偏测试）。贝叶斯方法在以后验概率的形式为超树分支提供支持值方面特别有用。
Since their advent, supertrees have been increasingly used in large-scale evolutionary studies requiring a phylogenetic framework and substantial efforts have been devoted to developing a wide variety of supertree methods (SMs). Recent advances in supertree theory have allowed the implementation of maximum likelihood (ML) and Bayesian SMs, based on using an exponential distribution to model incongruence between input trees and the supertree. Such approaches are expected to have advantages over commonly used non-parametric SMs, e.g. matrix representation with parsimony (MRP). We investigated new implementations of ML and Bayesian SMs and compared these with some currently available alternative approaches. Comparisons include hypothetical examples previously used to investigate biases of SMs with respect to input tree shape and size, and empirical studies based either on trees harvested from the literature or on trees inferred from phylogenomic scale data. Our results provide no evidence of size or shape biases and demonstrate that the Bayesian method is a viable alternative to MRP and other non-parametric methods. Computation of input tree likelihoods allows the adoption of standard tests of tree topologies (e.g. the approximately unbiased test). The Bayesian approach is particularly useful in providing support values for supertree clades in the form of posterior probabilities.