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Bioinformatics 2008 24(16):i160-i166; doi:10.1093/bioinformatics/btn282
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Efficient representation and P-value computation for high-order Markov motifs

Paulo G. S. da Fonseca 1,2,*, Katia S. Guimarães 1 and Marie-France Sagot 2

1Centro de Informática, Universidade Federal de Pernambuco, 50732-970, Recife, Brazil and 2Université de Lyon, F-69000, Lyon; Université Lyon 1; INRIA Rhône-Alpes; CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, F-69622, Villeurbanne, France

*To whom correspondence should be addressed.


  Abstract

Motivation: Position weight matrices (PWMs) have become a standard for representing biological sequence motifs. Their relative simplicity has favoured the development of efficient algorithms for diverse tasks such as motif identification, sequence scanning and statistical significance evaluation. Markov chainbased models generalize the PWM model by allowing for interposition dependencies to be considered, at the cost of substantial computational overhead, which may limit their application.

Results: In this article, we consider two aspects regarding the use of higher order Markov models for biological sequence motifs, namely, the representation and the computation of P-values for motifs described by a set of occurrences. We propose an efficient representation based on the use of tries, from which empirical position-specific conditional base probabilities can be computed, and extend state-of-the-art PWM-based algorithms to allow for the computation of exact P-values for high-order Markov motif models.

Availability: The software is available in the form of a Java objectoriented library from http://www.cin.ufpe.br/~paguso/kmarkov.

Contact: paguso{at}cin.ufpe.br


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