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使用guenomu从全基因组数据估计物种树。

Species Tree Estimation from Genome-Wide Data with guenomu.

作者信息

de Oliveira Martins Leonardo, Posada David

机构信息

Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo, Spain.

Department of Materials, Imperial College London, London, UK.

出版信息

Methods Mol Biol. 2017;1525:461-478. doi: 10.1007/978-1-4939-6622-6_18.

Abstract

The history of particular genes and that of the species that carry them can be different for a variety of reasons. In particular, gene trees and species trees can differ due to well-known evolutionary processes such as gene duplication and loss, lateral gene transfer, or incomplete lineage sorting. Species tree reconstruction methods have been developed to take this incongruence into account; these can be divided grossly into supertree and supermatrix approaches. Here we introduce a new Bayesian hierarchical model that we have recently developed and implemented in the program guenomu. The new model considers multiple sources of gene tree/species tree disagreement. Guenomu takes as input posterior distributions of unrooted gene tree topologies for multiple gene families, in order to estimate the posterior distribution of rooted species tree topologies.

摘要

由于多种原因,特定基因的历史与其所在物种的历史可能会有所不同。特别是,基因树和物种树可能会因基因复制与丢失、横向基因转移或不完全谱系分选等著名的进化过程而有所差异。已经开发出物种树重建方法来考虑这种不一致性;这些方法大致可分为超级树方法和超级矩阵方法。在此,我们介绍一种我们最近开发并在程序guenomu中实现的新的贝叶斯层次模型。新模型考虑了基因树/物种树不一致的多种来源。Guenomu将多个基因家族的无根基因树拓扑结构的后验分布作为输入,以估计有根物种树拓扑结构的后验分布。

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