FADO: a statistical method to detect favored or avoided distances between occurrences of motifs using the Hawkes' model

Statistical Applications in Genetics and Molecular Biology
Gaelle Gusto, Sophie Schbath

Abstract

We propose an original statistical method to estimate how the occurrences of a given process along a genome, genes or motifs for instance, may be influenced by the occurrences of a second process. More precisely, the aim is to detect avoided and/or favored distances between two motifs, for instance, suggesting possible interactions at a molecular level. For this, we consider occurrences along the genome as point processes and we use the so-called Hawkes' model. In such model, the intensity at position t depends linearly on the distances to past occurrences of both processes via two unknown profile functions to estimate. We perform a non parametric estimation of both profiles by using B-spline decompositions and a constrained maximum likelihood method. Finally, we use the AIC criterion for the model selection. Simulations show the excellent behavior of our estimation procedure. We then apply it to study (i) the dependence between gene occurrences along the E. coli genome and the occurrences of a motif known to be part of the major promoter for this bacterium, and (ii) the dependence between the yeast S. cerevisiae genes and the occurrences of putative polyadenylation signals. The results are coherent with known biological proper...Continue Reading

Citations

Sep 11, 2010·BMC Bioinformatics·Lisbeth CarstensenNiels R Hansen
Apr 20, 2014·Journal of Mathematical Neuroscience·Patricia Reynaud-BouretChristine Tuleau-Malot
Sep 26, 2012·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Davide PirinoLuca Ferretti

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