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使用分子序列数据对四分类单元拓扑结构进行贝叶斯假设检验。

Bayesian hypothesis testing of four-taxon topologies using molecular sequence data.

作者信息

Sinsheimer J S, Lake J A, Little R J

机构信息

Department of Biomathematics, UCLA Medical School 90024, USA.

出版信息

Biometrics. 1996 Mar;52(1):193-210.

PMID:8934592
Abstract

The reconstruction of phylogenetic trees from molecular sequences presents unusual problems for statistical inference. For example, three possible alternatives must be considered for four taxa when inferring the correct unrooted tree (referred to as a topology). In our view, classical hypothesis testing is poorly suited to this triangular set of alternative hypotheses. In this article, we develop Bayesian inference to determine the posterior probability that a four-taxon topology is correct given the sequence data and the evolutionary parsimony algorithm for phylogenetic reconstruction. We assess the frequency properties of our models in a large simulation study. Bayesian inference under the principles of evolutionary parsimony is shown to be well calibrated with reasonable discriminating power for a wide range of realistic conditions, including conditions that violate the assumptions of evolutionary parsimony.

摘要

从分子序列重建系统发育树给统计推断带来了不同寻常的问题。例如,在推断正确的无根树(称为拓扑结构)时,对于四个分类单元必须考虑三种可能的替代方案。我们认为,经典的假设检验不太适合这组三角形的替代假设。在本文中,我们开发了贝叶斯推断,以确定给定序列数据和用于系统发育重建的进化简约算法时,四分类单元拓扑结构正确的后验概率。我们在一项大型模拟研究中评估了我们模型的频率特性。结果表明,在进化简约原则下的贝叶斯推断在广泛的现实条件下,包括违反进化简约假设的条件下,具有良好的校准和合理的判别力。

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