Algorithmic improvements to species delimitation and phylogeny estimation under the multispecies coalescent
Algorithmic improvements to species delimitation and phylogeny estimation under the multispecies coalescent
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DOI：
10.1007/s00285-016-1034-0
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发表时间：
2017-01-01
影响因子：
1.9
通讯作者：
Jones, Graham
中科院分区：
文献类型：
--
作者：
Jones, Graham
这篇文章的重点是贝叶斯方法推断两个物种的界定和物种树下的多物种结合模型，使用来自多个位点的分子序列。物种划分不需要先验地将个体分配到物种，也不需要指导树。该方法是在BEAST 2的STACEY包中实现的，它是作者的DISSECT包的扩展。在这里，我们证明了相当大的效率提高，通过使用三个新的运营商从后使用马尔可夫链蒙特卡罗算法进行采样，并通过使用一个模型的人口规模参数沿着分支的物种树，允许这些参数被整合出来。通过对实现的测试证明了这些步骤的正确性。在多物种聚结剂下使用管道方法来物种划界的实践已经显示出在模拟数据上具有主要问题（Olave等人，Syst Biol 63：263-271）。doi：10.1093/sysbio/syt106，2014）。相同的模拟数据集被用来证明本方法的精度和改进的收敛性。我们还比较了 *BEAST在大型数据集上进行固定定界分析的性能，并再次显示了改进的收敛性。
The focus of this article is a Bayesian method for inferring both species delimitations and species trees under the multispecies coalescent model using molecular sequences from multiple loci. The species delimitation requires no a priori assignment of individuals to species, and no guide tree. The method is implemented in a package called STACEY for BEAST2, and is a extension of the author's DISSECT package. Here we demonstrate considerable efficiency improvements by using three new operators for sampling from the posterior using the Markov chain Monte Carlo algorithm, and by using a model for the population size parameters along the branches of the species tree which allows these parameters to be integrated out. The correctness of the moves is demonstrated by tests of the implementation. The practice of using a pipeline approach to species delimitation under the multispecies coalescent, has been shown to have major problems on simulated data (Olave et al. in Syst Biol 63:263-271. doi:10.1093/sysbio/syt106, 2014). The same simulated data set is used to demonstrate the accuracy and improved convergence of the present method. We also compare performance with *BEAST for a fixed delimitation analysis on a large data set, and again show improved convergence.