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基于树模型的系统发育分析方法研究组成异质性。

Phylogenetic Analysis That Models Compositional Heterogeneity over the Tree.

机构信息

Department of Life Sciences, Natural History Museum, London, UK.

出版信息

Methods Mol Biol. 2022;2569:119-135. doi: 10.1007/978-1-0716-2691-7_6.

Abstract

Molecular sequences in a phylogenetic analysis can differ in composition, and that shows that the process of evolution can change over time. However, models of evolution in common use are homogeneous over the tree, and if used in a phylogenetic analysis with compositionally tree-heterogeneous datasets these models can recover incorrect trees. The NDCH or Node-Discrete Compositional Heterogeneity model is able to model such data by accommodating differences in composition over the tree. Usage, problems, and limitations of this model are discussed, and a modification, the NDCH2 model, is described that can ameliorate some of these problems and limitations. Using these models can greatly increase the fit of the model to the data and can find better tree topologies. These models and various statistical tests are illustrated using a bacterial SSU rRNA dataset. These models are implemented in the software P4, and files for the analyses described here are made available.

摘要

系统发生分析中的分子序列在组成上可能存在差异,这表明进化过程可能随时间而变化。然而,常用的进化模型在整个树中是同质的,如果将这些模型用于组成上具有树异质性的数据集的系统发生分析中,这些模型可能会恢复出错误的树。NDCH 或节点离散组成异质性模型能够通过适应树上组成上的差异来对这种数据进行建模。本文讨论了该模型的使用、问题和局限性,并描述了一种改进的 NDCH2 模型,该模型可以改善其中的一些问题和局限性。使用这些模型可以大大提高模型对数据的拟合程度,并找到更好的树拓扑结构。本文使用细菌 SSU rRNA 数据集说明了这些模型和各种统计检验。这些模型在软件 P4 中实现,这里描述的分析文件也可供使用。

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