Phylogenomic branch length estimation using quartets

Author:

Tabatabaee Yasamin1,Zhang Chao2,Warnow Tandy1,Mirarab Siavash3ORCID

Affiliation:

1. Department of Computer Science, University of Illinois at Urbana-Champaign , Urbana, IL 61801, United States

2. Department of Integrative Biology, University of California at Berkeley , Berkeley, CA 94720, United States

3. Department of Electrical and Computer Engineering, University of California, San Diego , La Jolla, CA 92093, United States

Abstract

Abstract Motivation Branch lengths and topology of a species tree are essential in most downstream analyses, including estimation of diversification dates, characterization of selection, understanding adaptation, and comparative genomics. Modern phylogenomic analyses often use methods that account for the heterogeneity of evolutionary histories across the genome due to processes such as incomplete lineage sorting. However, these methods typically do not generate branch lengths in units that are usable by downstream applications, forcing phylogenomic analyses to resort to alternative shortcuts such as estimating branch lengths by concatenating gene alignments into a supermatrix. Yet, concatenation and other available approaches for estimating branch lengths fail to address heterogeneity across the genome. Results In this article, we derive expected values of gene tree branch lengths in substitution units under an extension of the multispecies coalescent (MSC) model that allows substitutions with varying rates across the species tree. We present CASTLES, a new technique for estimating branch lengths on the species tree from estimated gene trees that uses these expected values, and our study shows that CASTLES improves on the most accurate prior methods with respect to both speed and accuracy. Availability and implementation CASTLES is available at https://github.com/ytabatabaee/CASTLES.

Funder

National Science Foundation

NSF

National Institute of Health

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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