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Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7
Author(s) -
Andrew Rambaut,
Alexei J. Drummond,
Dong Xie,
Guy Baele,
Marc A. Suchard
Publication year - 2018
Publication title -
systematic biology
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 7.128
H-Index - 182
eISSN - 1076-836X
pISSN - 1063-5157
DOI - 10.1093/sysbio/syy032
Subject(s) - markov chain monte carlo , posterior probability , bayesian probability , bayesian inference , computer science , inference , artificial intelligence , biology
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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