Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7 Article Swipe

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Markov chain Monte Carlo Posterior probability Bayesian probability Bayesian inference Computer science Inference Artificial intelligence Biology

Andrew Rambaut , Alexei J. Drummond , Dong Xie , Guy Baele , Marc A. Suchard ·

YOU? · · 2018 · Open Access · · DOI: https://doi.org/10.1093/sysbio/syy032 · OA: W2801159594

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.