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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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rbrothers: R Package for Bayesian Multiple Change-Point Recombination Detection.

Jan Irvahn1, Sujay Chattopadhyay, Evgeni V Sokurenko

  • 1Department of Statistics, University of Washington, Seattle, WA, 98195, USA.

Evolutionary Bioinformatics Online
|July 3, 2013
PubMed
Summary

This study introduces rbrothers, an R package for detecting phylogenetic recombination using a Bayesian change-point model. It simplifies integrating advanced recombination analysis into R-based evolutionary biology workflows.

Keywords:
SalmonellaevolutionfimAfimHphylogenetics

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Area of Science:

  • Bioinformatics
  • Evolutionary Biology
  • Computational Biology

Background:

  • Phylogenetic recombination detection is crucial for understanding molecular evolution.
  • Existing computational tools for recombination detection are often not integrated with R, a popular statistical analysis environment.
  • There is a need for accessible, model-based tools for phylogenetic recombination analysis within R.

Purpose of the Study:

  • To introduce rbrothers, an R package that provides access to a sophisticated Bayesian multiple change-point model for phylogenetic recombination detection.
  • To enhance the usability and application domain of the Bayesian change-point model through pre- and post-processing routines.
  • To facilitate the integration of advanced recombination detection into existing R-based phylogenetic analysis workflows.

Main Methods:

  • Development of the rbrothers R package.
  • Implementation of a Bayesian multiple change-point model for recombination detection.
  • Inclusion of algorithms for input tree generation and Markov chain Monte Carlo (MCMC) convergence diagnostics.
  • Provision of functions for result summarization and graphical representation.
  • Application to analyze recombination in Salmonella enterica fimA and fimH genes.

Main Results:

  • The rbrothers package successfully integrates a Bayesian multiple change-point model into the R environment.
  • Pre- and post-processing routines were implemented to broaden the applicability of the model.
  • The package includes essential functionalities for tree input, MCMC convergence checking, and result visualization.
  • A comparative analysis of Salmonella enterica genes fimA and fimH was performed using rbrothers.

Conclusions:

  • The rbrothers package makes advanced Bayesian phylogenetic recombination detection accessible to R users.
  • It enables seamless integration of recombination analysis into existing R-based phylogenetic workflows.
  • The package is expected to empower researchers in evolutionary biology and bioinformatics to conduct more comprehensive analyses.