Computing the probability of gene trees concordant with the species tree in the multispecies coalescent

被引:1
|
作者
Truszkowski, Jakub [1 ,4 ]
Scornavacca, Celine [2 ,3 ]
Pardi, Fabio [1 ,3 ]
机构
[1] Univ Montpellier, CNRS, LIRMM, Montpellier, France
[2] Univ Montpellier, CNRS, ISEM, Montpellier, France
[3] Inst Biol Computat, Montpellier, France
[4] RBC Borealis AI, Waterloo, ON, Canada
关键词
Multispecies coalescent; Gene tree; Species tree; Coalescent; Dynamic programming; Incomplete lineage sorting; INFERENCE; GENEALOGY; ALGORITHM;
D O I
10.1016/j.tpb.2020.12.002
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The multispecies coalescent process models the genealogical relationships of genes sampled from several species, enabling useful predictions about phenomena such as the discordance between a gene tree and the species phylogeny due to incomplete lineage sorting. Conversely, knowledge of large collections of gene trees can inform us about several aspects of the species phylogeny, such as its topology and ancestral population sizes. A fundamental open problem in this context is how to efficiently compute the probability of a gene tree topology, given the species phylogeny. Although a number of algorithms for this task have been proposed, they either produce approximate results, or, when they are exact, they do not scale to large data sets. In this paper, we present some progress towards exact and efficient computation of the probability of a gene tree topology. We provide a new algorithm that, given a species tree and the number of genes sampled for each species, calculates the probability that the gene tree topology will be concordant with the species tree. Moreover, we provide an algorithm that computes the probability of any specific gene tree topology concordant with the species tree. Both algorithms run in polynomial time and have been implemented in Python. Experiments show that they are able to analyze data sets where thousands of genes are sampled in a matter of minutes to hours. (c) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页码:22 / 31
页数:10
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