Posterior summarization in Bayesian phylogenetics using Tracer 1.7

Rambaut A, Drummond AJ, Xie D, Baele G & Suchard MA

(2018) Systematic Biology 67, 901-904.

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. ? The Author(s) 2018. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Andrew Rambaut, 2007