Bayesian evaluation of temporal signal in measurably evolving populations

S Duchene; P Lemey; T Stadler; SYW Ho; DA Duchene; V Dhanasekaran; G Baele

Journal article

Bayesian evaluation of temporal signal in measurably evolving populations

S Duchene, P Lemey, T Stadler, SYW Ho, DA Duchene, V Dhanasekaran, G Baele

Molecular Biology and Evolution | OXFORD UNIV PRESS | Published : 2020

DOI: 10.1093/molbev/msaa163

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Abstract

Phylogenetic methods can use the sampling times of molecular sequence data to calibrate the molecular clock, enabling the estimation of evolutionary rates and timescales for rapidly evolving pathogens and data sets containing ancient DNA samples. A key aspect of such calibrations is whether a sufficient amount of molecular evolution has occurred over the sampling time window, that is, whether the data can be treated as having come from a measurably evolving population. Here, we investigate the performance of a fully Bayesian evaluation of temporal signal (BETS) in sequence data. The method involves comparing the fit to the data of two models: a model in which the data are accompanied by the ..

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University of Melbourne Researchers

Sebastian Duchene Garzon Author

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Awarded by National Institutes of Health

Funding Acknowledgements

We thank the Editor and two anonymous reviewers for useful comments on previous versions of this manuscript. S.D. was supported by an Australian Research Council Discovery Early Career Researcher Award (DE190100805) and an Australian National Health and Medical Research Council grant (APP1157586). P.L. acknowledges funding from the European Research Council under the European Union's Horizon 2020 research and innovation program (Grant Agreement No. 725422-ReservoirDOCS) and the Research Foundation-Flanders ("Fonds voor Wetenschappelijk Onderzoek-Vlaanderen," G066215N, G0D5117N, and G0B9317N). S.Y.W.H. was funded by the Australian Research Council (FT160100167). V.D. was supported by contract HHSN272201400006C from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, U.S. Department of Health and Human Services, the United States. G.B. acknowledges support from the Interne Fondsen KU Leuven/Internal Funds KU Leuven under grant agreement C14/18/094, and the Research FoundationFlanders ("Fonds voor Wetenschappelijk OnderzoekVlaanderen," G0E1420N).