Checking homogeneity of motifs' distribution in heterogenous sequences.
Studying the distribution of a motif along sequences may help in the understanding of its biological function, or to detect regions of interest. A statistical model is needed to assess the significance of the observed distribution. We propose a heterogenous compound Poisson process to model the possibility of overlap between occurrences and some heterogeneity of the sequence known a priori. The estimation procedure of the parameters is described and tests of homogenous sub-models are proposed. We also consider the detection of rich regions using either cumulated distances or moving intervals, via a homogenization technique. Illustrations of the method are given with applications to bacterial genomes.
Ledent
Sabrina
S
Unité Mathématique, Informatique et Génome, Institut National de la Recherche Agronomique (INRA), F-78350 Jouy-en-Josas, France.
Robin
Stéphane
S
D000465:Algorithms; D020816:Amino Acid Motifs; D019295:Computational Biology; D003198:Computer Simulation; D004926:Escherichia coli / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D016012:Poisson Distribution; D011336:Probability; D016415:Sequence Alignment