期刊
PLOS COMPUTATIONAL BIOLOGY
卷 5, 期 3, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1000318
关键词
-
资金
- National Institutes of Health (NIH)/National Human Genome Research Institute [GM076705, 5T32HG00047]
We propose a novel method for detecting sites of molecular recombination in multiple alignments. Our approach is a compromise between previous extremes of computationally prohibitive but mathematically rigorous methods and imprecise heuristic methods. Using a combined algorithm for estimating tree structure and hidden Markov model parameters, our program detects changes in phylogenetic tree topology over a multiple sequence alignment. We evaluate our method on benchmark datasets from previous studies on two recombinant pathogens, Neisseria and HIV-1, as well as simulated data. We show that we are not only able to detect recombinant regions of vastly different sizes but also the location of breakpoints with great accuracy. We show that our method does well inferring recombination breakpoints while at the same time maintaining practicality for larger datasets. In all cases, we confirm the breakpoint predictions of previous studies, and in many cases we offer novel predictions.
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