Originally published as Genetics Published Articles Ahead of Print on April 3, 2007.

Genetics, Vol. 176, 1035-1047, June 2007, Copyright © 2007
doi:10.1534/genetics.106.068874

An Exact Nonparametric Method for Inferring Mosaic Structure in Sequence Triplets

Maciej F. Boni^*,,1, David Posada and Marcus W. Feldman

^* Stanford Genome Technology Center, Palo Alto, California 94304, Department of Biological Sciences, Stanford University, Stanford, California 94305 and Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo 36310, Spain

¹ Corresponding author: Stanford Genome Technology Center, 855 S. California Ave., Palo Alto, CA 94304.
E-mail: maciek{at}charles.stanford.edu

Statistical tests for detecting mosaic structure or recombination among nucleotide sequences usually rely on identifying a pattern or a signal that would be unlikely to appear under clonal reproduction. Dozens of such tests have been described, but many are hampered by long running times, confounding of selection and recombination, and/or inability to isolate the mosaic-producing event. We introduce a test that is exact, nonparametric, rapidly computable, free of the infinite-sites assumption, able to distinguish between recombination and variation in mutation/fixation rates, and able to identify the breakpoints and sequences involved in the mosaic-producing event. Our test considers three sequences at a time: two parent sequences that may have recombined, with one or two breakpoints, to form the third sequence (the child sequence). Excess similarity of the child sequence to a candidate recombinant of the parents is a sign of recombination; we take the maximum value of this excess similarity as our test statistic _m,n,b. We present a method for rapidly calculating the distribution of _m,n,b and demonstrate that it has comparable power to and a much improved running time over previous methods, especially in detecting recombination in large data sets.

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