Grant: Discovery Grants Program - Individual

The coalescent process, a stochastic process used to simulate population genealogies, has attracted much attention recently, mostly due to the numerous applications in human genetics research. We have developed a method, which uses the coalescent process with recombination (Larribe et al. 2002, Larribe 2004) to estimate the location of a genetic mutation influencing a disease, e.g. to do genetic fine mapping. After having improved the stability of the estimates using ""windows"" of genetic marker and composite-conditional-likelihood strategy (Larribe and Lessard 2008), we propose to develop further the method in the context of complex genetic disease, which is of major interest in human genetics today. The goal is to be able to estimate parameters of a genetic model (incomplete penetrance and phenocopy), to take these estimated parameters into account in the method, to be able to model complex schemes of interactions between genes, to be able to treat quantitative trait and to develop the method at the genome scale.Moreover, we would like to be able to take into account non-random selection of cases and controls (over representation of cases in the sample) by model the frequency of the disease mutation backward in time. Finally, we will propose a new way to estimate to make inference in the context of the coalescent.