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- Title
Estimation of speciation times under the multispecies coalescent.
- Authors
Peng, Jing; Swofford, David L; Kubatko, Laura
- Abstract
Motivation The multispecies coalescent model is now widely accepted as an effective model for incorporating variation in the evolutionary histories of individual genes into methods for phylogenetic inference from genome-scale data. However, because model-based analysis under the coalescent can be computationally expensive for large datasets, a variety of inferential frameworks and corresponding algorithms have been proposed for estimation of species-level phylogenies and associated parameters, including speciation times and effective population sizes. Results We consider the problem of estimating the timing of speciation events along a phylogeny in a coalescent framework. We propose a maximum a posteriori estimator based on composite likelihood (MAP CL) for inferring these speciation times under a model of DNA sequence evolution for which exact site-pattern probabilities can be computed under the assumption of a constant θ throughout the species tree. We demonstrate that the MAP CL estimates are statistically consistent and asymptotically normally distributed, and we show how this result can be used to estimate their asymptotic variance. We also provide a more computationally efficient estimator of the asymptotic variance based on the non-parametric bootstrap. We evaluate the performance of our method using simulation and by application to an empirical dataset for gibbons. Availability and implementation The method has been implemented in the PAUP* program, freely available at https://paup.phylosolutions.com for Macintosh, Windows and Linux operating systems. Supplementary information Supplementary data are available at Bioinformatics online.
- Subjects
INTERNET servers; LINUX operating systems; GENE regulatory networks; GENETIC speciation; NUCLEOTIDE sequence; DNA sequencing
- Publication
Bioinformatics, 2022, Vol 38, Issue 23, p5182
- ISSN
1367-4803
- Publication type
Article
- DOI
10.1093/bioinformatics/btac679