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Bayesian estimation of past population dynamics in BEAST 1.10 using the Skygrid coalescent model.


ABSTRACT: Inferring past population dynamics over time from heterochronous molecular sequence data is often achieved using the Bayesian Skygrid model, a non-parametric 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/), LogCombiner as well as Tracer in a complete workflow.

SUBMITTER: Hill V 

PROVIDER: S-EPMC6805224 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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

Hill Verity V   Baele Guy G  

Molecular biology and evolution 20191101 11


Inferring 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 p  ...[more]

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