Detecting recombination with MCMC

Husmeier, Dirk
McGuire, Gráinne

¹Biomathematics and Statistics Scotland (BioSS), JCMB, The King's Buildings, Edinburgh EH9 3JZ, UK
²School of Applied Statistics, University of Reading, Reading RG6 6FN, UK

Received on January 20, 2002; revised and accepted on April 1, 2002

Bioinformatics 18:p S345-S353, July 2002.

Motivation

We present a statistical method for detecting recombination, whose objective is to accurately locate the recombinant breakpoints in DNA sequence alignments of small numbers of taxa (4 or 5). Our approach explicitly models the sequence of phylogenetic tree topologies along a multiple sequence alignment. Inference under this model is done in a Bayesian way, using Markov chain Monte Carlo (MCMC). The algorithm returns the site-dependent posterior probability of each tree topology, which is used for detecting recombinant regions and locating their breakpoints.

Results

The method was tested on a synthetic and three real DNA sequence alignments, where it was found to outperform the established detection methods PLATO, RECPARS, and TOPAL.

Availability

The algorithm has been implemented in the C++ program package BARCE, which is freely available from http://www.bioss.sari.ac.uk/∼dirk/my_software

Contact

[email protected]