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
Descripción
Sumario: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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