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Reversible polymorphism-aware phylogenetic models and their application to tree inference

Abstract

We present a reversible Polymorphism-Aware Phylogenetic Model (revPoMo) for species tree estimation from genome-wide data. revPoMo enables the reconstruction of large scale species trees for many within-species samples. It expands the alphabet of DNA substitution models to include polymorphic states, thereby, naturally accounting for incomplete lineage sorting. We implemented revPoMo in the maximum likelihood software IQ-TREE. A simulation study and an application to great apes data show that the runtimes of our approach and standard substitution models are comparable but that revPoMo has much better accuracy in estimating trees, divergence times and mutation rates. The advantage of revPoMo is that an increase of sample size per species improves estimations but does not increase runtime. Therefore, revPoMo is a valuable tool with several applications, from speciation dating to species tree reconstruction.

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Authors
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Citation
Category
Journal Paper
Divisions
Bioinformatics and Computational Biology
Journal or Publication Title
Journal of Theoretical Biology
ISSN
0022-5193
Publisher
Elsevier
Place of Publication
Amsterdam, Netherlands
Page Range
pp. 362-370
Volume
407
Date
October 2016
Official URL
http://dx.doi.org/10.1016/j.jtbi.2016.07.042
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