A fast, alignment-free, conservation-based method for transcription factor binding site discovery
RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology
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Motivation: Identification of functionally conserved regulatory elements in sequence data from closely related organisms is becoming feasible, due to the rapid growth of public sequence databases. Closely related organisms are most likely to have common regulatory motifs; however, the recent speciation of such organisms results in the high degree of correlation in their genome sequences, confounding the detection of functional elements. Additionally, alignment algorithms that use optimization techniques are limited to the detection of a single alignment that may not be representative. Comparative-genomics studies must be able to address the phylogenetic correlation in the data and efficiently explore the alignment space, in order to make specific and biologically relevant predictions. Results: We describe here a Gibbs sampler that employs a full phylogenetic model and reports an ensemble centroid solution. We describe regulatory motif detection using both simulated and real data, and demonstrate that this approach achieves improved specificity, sensitivity, and positive predictive value over non-phylogenetic algorithms, and over phylogenetic algorithms that report a maximum likelihood solution. Availability: The software is freely available at http://bayesweb.wadsworth.org/gibbs/gibbs.html Contact: William_Thompson_1@brown.edu Supplementary information: Supplementary data are available at Bioinformatics online.