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Real-Time and Remote MCMC Trace Inspection with Beastiary
Wytamma Wirth1, Sebastian Duchene1
1Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia.
Molecular Biology and Evolution
|May 13, 2022
Summary
Bayesian phylogenetics analyses using Markov chain Monte Carlo (MCMC) are computationally intensive. Beastiary is a new web-app for real-time, remote monitoring of MCMC log files from popular phylogenetic software.
Area of Science:
- Computational Biology
- Bioinformatics
- Evolutionary Biology
Background:
- Bayesian phylogenetics is widely used, often employing Markov chain Monte Carlo (MCMC) methods.
- The computational intensity of MCMC necessitates the use of remote servers for analysis.
- Effective monitoring of long-running MCMC analyses is crucial for assessing convergence and efficiency.
Purpose of the Study:
- To introduce Beastiary, a novel web-application for inspecting MCMC log files.
- To provide real-time and remote visualization capabilities for phylogenetic analyses.
- To support popular Bayesian phylogenetic software packages.
Main Methods:
- Development of a web-application named Beastiary.
- Implementation of parsers for log files from BEAST, BEAST2, RevBayes, and MrBayes.
- Design for easy deployment and browser-based access.
Main Results:
- Beastiary offers real-time summarization and visualization of MCMC output.
- The application facilitates remote monitoring of phylogenetic analyses.
- It is compatible with multiple widely-used phylogenetic software packages.
Conclusions:
- Beastiary enhances the workflow of Bayesian phylogenetic analyses by enabling efficient remote monitoring.
- The tool simplifies the inspection of MCMC convergence and model performance.
- It is a valuable resource for researchers utilizing MCMC in phylogenetics.
