Distance metrics for ranked evolutionary trees.

Distance metrics for ranked evolutionary trees.
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排名进化树的距离指标。

DOI:
10.1073/pnas.1922851117
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发表时间:
2020-11-17
影响因子:
11.1
通讯作者:
Palacios JA
Palacios JA
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Kim J;Rosenberg NA;Palacios JA

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从分子序列数据推断的有根二叉树提供了关于种群和物种进化历史的信息。我们介绍的指标排名树的形状和排名系谱,其中的形状和时间的分支顺序在一棵树被认为是,但不是分类标签。我们的指标,使量化的进化差异,树的不确定性评估,并建设一个树分布的统计摘要。它们在计算上是高效的,特别适用于比较涉及异源样本的传染病的传播动力学,以及生活在不同地理区域的生物体的比较分析。系谱树建模是群体遗传学和群体遗传学中估计进化参数的基本方法。最近的数学结果排名家谱没有叶标签解锁的机会,在分析进化树。特别是,排名系谱之间的比较有利于研究在多个时间段采样的不同生物体的进化过程。我们提出的指标排名树的形状和排名谱系等时和异时采样。我们提出的树度量使得有可能进行排名树形状和定时排名树形状或排名家谱的统计分析。这种分析使我们能够评估树分布的差异,量化估计的不确定性,并总结树分布。我们通过模拟和传染病的应用程序,我们的指标的效用。
Rooted binary trees inferred from molecular sequence data provide information about the evolutionary history of populations and species. We introduce metrics on ranked tree shapes and ranked genealogies, in which the shape and temporal branching order in a tree are considered, but not the taxon labels. Our metrics enable quantification of evolutionary differences, assessment of tree uncertainty, and construction of statistical summaries of a tree distribution. They are computationally efficient and particularly useful for comparing phylodynamics of infectious diseases involving heterochronous samples and for comparative analyses of organisms that live in different geographic regions. Genealogical tree modeling is essential for estimating evolutionary parameters in population genetics and phylogenetics. Recent mathematical results concerning ranked genealogies without leaf labels unlock opportunities in the analysis of evolutionary trees. In particular, comparisons between ranked genealogies facilitate the study of evolutionary processes of different organisms sampled at multiple time periods. We propose metrics on ranked tree shapes and ranked genealogies for lineages isochronously and heterochronously sampled. Our proposed tree metrics make it possible to conduct statistical analyses of ranked tree shapes and timed ranked tree shapes or ranked genealogies. Such analyses allow us to assess differences in tree distributions, quantify estimation uncertainty, and summarize tree distributions. We show the utility of our metrics via simulations and an application in infectious diseases.
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发表时间: 2003-02-01
影响因子: 1.4
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