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Bioinformatics Advance Access originally published online on November 30, 2004
Bioinformatics 2005 21(9):1797-1806; doi:10.1093/bioinformatics/bti151
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© The Author 2004. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Detecting interspecific recombination with a pruned probabilistic divergence measure

Dirk Husmeier 1,*, Frank Wright 2 and Iain Milne 2

1Biomathematics and Statistics Scotland, JCMB The King's Buildings, Edinburgh, EH9 3JZ, UK
2Biomathematics and Statistics Scotland, SCRI Invergowrie, Dundee, DD2 5DA, UK

*To whom correspondence should be addressed.

Motivation: A promising sliding-window method for the detection of interspecific recombination in DNA sequence alignments is based on the monitoring of changes in the posterior distribution of tree topologies with a probabilistic divergence measure. However, as the number of taxa in the alignment increases or the sliding-window size decreases, the posterior distribution becomes increasingly diffuse. This diffusion blurs the probabilistic divergence signal and adversely affects the detection accuracy. The present study investigates how this shortcoming can be redeemed with a pruning method based on post-processing clustering, using the Robinson–Foulds distance as a metric in tree topology space.

Results: An application of the proposed scheme to three synthetic and two real-world DNA sequence alignments illustrates the amount of improvement that can be obtained with the pruning method. The study also includes a comparison with two established recombination detection methods: Recpars and the DSS (difference of sum of squares) method.

Availability: Software, data and further supplementary material are available at the following website: http://www.bioss.sari.ac.uk/~dirk/Supplements/

Contact: dirk{at}bioss.ac.uk


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