Bioinformatics Advance Access first published online on May 24, 2005
This version published online on May 27, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti459
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1 Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095-1766, USA
* To whom correspondence should be addressed.
Motivation: We introduce a dual multiple change-point (MCP) model for recombination detection among aligned nucleotide sequences. The dual MCP model is an extension of the model introduced by Suchard and co-workers. In the original single MCP model, one change-point process is used to model spatial phylogenetic variation. Here, we show that using two change-point processes, one for spatial variation of tree topologies and the other for spatial variation of substitution process parameters, increases recombination detection accuracy. Statistical analysis is done in a Bayesian framework using reversible jump Markov chain Monte Carlo sampling to approximate the joint posterior distribution of all model parameters. Results: We use primate mitochondrial DNA data with simulated recombination break-points at specific locations to compare the two models. We also analyze two real HIV sequences to identify recombination break-points using the dual MCP model. Availability: A software program "DualBrothers" implementing the dual MCP model is available in the form of a Java package at http://www.biomath.ucla.edu/msuchard/DualBrothers. Supplementary information: http://www.biomath.ucla.edu/msuchard/DualBrothers.
Received August 5, 2004
Revised April 14, 2005
Accepted April 18, 2005
Article
Dual multiple change-point model leads to more accurate recombination detection
2 Department of Statistics, Iowa State University, Ames, IA 50011, USA; Department of Genetics, Cell & Development Biology, Iowa State University, Ames, IA 50011, USA; Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, USA
3 Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, USA
Marc A. Suchard, E-mail: msuchard{at}ucla.edu
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