Journal article
Detecting Episodic Evolution through Bayesian Inference of Molecular Clock Models
JH Tay, G Baele, S Duchene
Molecular Biology and Evolution | OXFORD UNIV PRESS | Published : 2023
Abstract
Molecular evolutionary rate variation is a key aspect of the evolution of many organisms that can be modeled using molecular clock models. For example, fixed local clocks revealed the role of episodic evolution in the emergence of SARS-CoV-2 variants of concern. Like all statistical models, however, the reliability of such inferences is contingent on an assessment of statistical evidence. We present a novel Bayesian phylogenetic approach for detecting episodic evolution. It consists of computing Bayes factors, as the ratio of posterior and prior odds of evolutionary rate increases, effectively quantifying support for the effect size. We conducted an extensive simulation study to illustrate t..
View full abstractGrants
Awarded by Fonds Wetenschappelijk Onderzoek
Funding Acknowledgements
The authors thank two anonymous reviewers and the Editor for helpful comments and suggestions for earlier versions of this manuscript. J.H.T. and S.D. were supported by the Australian Research Council (FT220100629) and the Australian National Health and Medical Research Council (grant number 2017284). G.B. acknowledges support from the Internal Funds KU Leuven under grant agreement C14/18/094 and from the Research Foundation - Flanders ("Fonds voor Wetenschappelijk Onderzoek - Vlaanderen," G0E1420N and G098321N). The authors acknowledge efforts by originating and submitting laboratories for the sequence data in GISAID EpiCoV on which our empirical analyses are based. This research was undertaken using the LIEF HPC-GPGPU Facility hosted at the University of Melbourne. This facility was established with the assistance of LIEF Grant LE170100200.