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Published in

Oxford University Press, Molecular Biology and Evolution, 11(36), p. 2620-2628, 2019

DOI: 10.1093/molbev/msz172

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Bayesian Estimation of Past Population Dynamics in BEAST 1.10 Using the Skygrid Coalescent Model

Journal article published in 2019 by Verity Hill ORCID, Guy Baele ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Postprint: archiving allowed
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Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

AbstractInferring past population dynamics over time from heterochronous molecular sequence data is often achieved using the Bayesian Skygrid model, a nonparametric coalescent model that estimates the effective population size over time. Available in BEAST, a cross-platform program for Bayesian analysis of molecular sequences using Markov chain Monte Carlo, this coalescent model is often estimated in conjunction with a molecular clock model to produce time-stamped phylogenetic trees. We here provide a practical guide to using BEAST and its accompanying applications for the purpose of drawing inference under these models. We focus on best practices, potential pitfalls, and recommendations that can be generalized to other software packages for Bayesian inference. This protocol shows how to use TempEst, BEAUti, and BEAST 1.10 (http://beast.community/; last accessed July 29, 2019), LogCombiner as well as Tracer in a complete workflow.