Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We...

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Detalles Bibliográficos
Autores principales: Rambaut, Andrew, Drummond, Alexei J, Xie, Dong, Baele, Guy, Suchard, Marc A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Software for Systematics and Evolution
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101584/
https://www.ncbi.nlm.nih.gov/pubmed/29718447
http://dx.doi.org/10.1093/sysbio/syy032
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author Rambaut, Andrew
Drummond, Alexei J
Xie, Dong
Baele, Guy
Suchard, Marc A
author_facet Rambaut, Andrew
Drummond, Alexei J
Xie, Dong
Baele, Guy
Suchard, Marc A
author_sort Rambaut, Andrew
collection PubMed
description Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.
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spelling pubmed-61015842018-08-27 Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7 Rambaut, Andrew Drummond, Alexei J Xie, Dong Baele, Guy Suchard, Marc A Syst Biol Software for Systematics and Evolution Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer. Oxford University Press 2018-09 2018-04-27 /pmc/articles/PMC6101584/ /pubmed/29718447 http://dx.doi.org/10.1093/sysbio/syy032 Text en © The Author(s) 2018. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For Permissions, please email: journals.permissions@oup.com
spellingShingle Software for Systematics and Evolution
Rambaut, Andrew
Drummond, Alexei J
Xie, Dong
Baele, Guy
Suchard, Marc A
Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7
title Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7
title_full Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7
title_fullStr Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7
title_full_unstemmed Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7
title_short Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7
title_sort posterior summarization in bayesian phylogenetics using tracer 1.7
topic Software for Systematics and Evolution
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101584/
https://www.ncbi.nlm.nih.gov/pubmed/29718447
http://dx.doi.org/10.1093/sysbio/syy032
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