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

BEAST Bayesian phylogenetics Skygrid TempEst Tracer coalescent pathogen phylodynamics

Journal

Molecular biology and evolution
ISSN: 1537-1719
Titre abrégé: Mol Biol Evol
Pays: United States
ID NLM: 8501455

Informations de publication

Date de publication:
01 Nov 2019
Historique:
medline: 1 8 2019
pubmed: 1 8 2019
entrez: 1 8 2019
Statut: ppublish

Résumé

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 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.

Identifiants

pubmed: 31364710
pii: 5541799
doi: 10.1093/molbev/msz172
pmc: PMC6805224
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2620-2628

Informations de copyright

© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Auteurs

Verity Hill (V)

Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom.

Guy Baele (G)

Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium.

Classifications MeSH