Dual multiple change-point model leads to more accurate recombination detection.
BACKGROUND
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 previously 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.
Minin
Vladimir N
VN
Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, CA 90095-1766, USA.
Dorman
Karin S
KS
Fang
Fang
F
Suchard
Marc A
MA
D000465:Algorithms; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D004252:DNA Mutational Analysis / Q000379:methods*; D004272:DNA, Mitochondrial / Q000235:genetics*; D019143:Evolution, Molecular; D008957:Models, Genetic; D015233:Models, Statistical; D011995:Recombination, Genetic / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
D004272:DNA, Mitochondrial