Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

TLDR

Bayesian phylogenetic inference via MCMC is essential for reconstructing evolutionary history, and visualizing the resulting posterior samples is a critical step in any substantial analysis. The authors introduce Tracer 1.7, a tool for visualizing and analyzing MCMC trace files from Bayesian phylogenetic inference. Tracer implements kernel density estimation, multivariate visualizations, demographic trajectory reconstruction, and conditional posterior summaries to analyze MCMC traces. Tracer is open‑source and can be downloaded from http://beast.community/tracer.

Abstract

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.