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Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7.

Andrew Rambaut1, Alexei J Drummond2,3, Dong Xie2,3

  • 1Institute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, King's Buildings, Edinburgh, EH9 3FL, UK.

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|May 3, 2018
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Summary
This summary is machine-generated.

Tracer (version 1.7) software aids in visualizing and analyzing Bayesian phylogenetic inference results. This tool helps researchers understand evolutionary history from molecular data by examining Markov chain Monte Carlo (MCMC) outputs.

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Area of Science:

  • Computational Biology
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Bayesian inference using Markov chain Monte Carlo (MCMC) is crucial for reconstructing evolutionary history from molecular sequences.
  • Analyzing MCMC-generated posterior distributions is essential for robust Bayesian phylogenetic inference.

Purpose of the Study:

  • To introduce Tracer (version 1.7), an open-source software package designed for visualizing and analyzing MCMC trace files.
  • To provide researchers with tools for effective interpretation of Bayesian phylogenetic analyses.

Main Methods:

  • Development and presentation of the Tracer software package (version 1.7).
  • Implementation of features including kernel density estimation, multivariate visualization, demographic trajectory reconstruction, and conditional posterior distribution summaries.

Main Results:

  • Tracer facilitates comprehensive analysis of MCMC trace files from Bayesian phylogenetic inference.
  • The software offers a suite of visualization and analytical tools to aid in understanding evolutionary relationships.

Conclusions:

  • Tracer (version 1.7) is a valuable, open-source resource for the bioinformatics and evolutionary biology communities.
  • The software enhances the process of interpreting complex phylogenetic datasets derived from MCMC analyses.