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Introducing a general class of species diversification models for phylogenetic trees

机译：介绍了系统发育树种的一般种类多样化模型

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摘要

Phylogenetic trees are types of networks that describe the temporal relationship between individuals, species, or other units that are subject to evolutionary diversification. Many phylogenetic trees are constructed from molecular data that is often only available for extant species, and hence they lack all or some of the branches that did not make it into the present. This feature makes inference on the diversification process challenging. For relatively simple diversification models, analytical or numerical methods to compute the likelihood exist, but these do not work for more realistic models in which the likelihood depends on properties of the missing lineages. In this article, we study a general class of species diversification models, and we provide an expectation-maximization framework in combination with a uniform sampling scheme to perform maximum likelihood estimation of the parameters of the diversification process.
机译：系统发育树是描述受进化多样化的个体，物种或其他单元之间的时间关系的网络类型。许多系统发育树由分子数据构成，该数据通常仅适用于现存物种，因此它们缺乏未使其进入现在的一切或一些分支。此功能对多元化过程的挑战进行了推论。对于相对简单的多样化模型，存在计算可能性的分析或数值方法，但这些方法不适用于更现实的模型，其中可能取决于缺失谱系的属性。在本文中，我们研究了一般的物种多样化模型，我们提供了一个期望 - 最大化框架，与统一的采样方案结合，以执行多样化过程参数的最大似然估计。

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  • 来源
    《Statistica neerlandica》 |2020年第3期|261-274|共14页
  • 作者

    Francisco Richter; Bart Haegeman; Rampal S. Etienne; Ernst C.Wit;

  • 作者单位

    Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen The Netherlands Groningen Institute for Evolutionary Life Sciences University of Groningen Groningen The Netherlands;

    Theoretical and Experimental Ecology Station CNRS and Paul Sabatier University Toulouse France;

    Groningen Institute for Evolutionary Life Sciences University of Groningen Groningen The Netherlands;

    Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen The Netherlands Institute of Computational Science Universita della Svizzera italiana (USI) Lugano Switzerland;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    EM algorithm; generalized linear models; importance sampling; nonhomogeneous Poisson process; phylogenetic trees;

    机译：EM算法;广义线性模型;重要性抽样;非均匀泊松过程;系统发育树木;

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