University of Washington - Department of Statistics
Recombination is a biological process that occurs during cellular meiosis, resulting in a "mixing-up" of our genetic material. The estimation of fine-scale rates of recombination in the human genome is an intriguing -- and difficult -- problem. There are two known kinds of recombination: crossover and gene conversion. Recently, fine-scale crossover rates have been inferred to some success using statistical methodology applied to population genetic data (ie genetic data on random samples of individuals from a population). However, reliable gene conversion rates have proved more difficult to come by. In this talk we introduce this problem for a statistical audience, and present a new model for the joint estimation of gene conversion and crossover rates from population genetic data. Specifically, we have incorporated gene conversion into the "Product of Approximate Conditionals" (PAC) model of Li and Stephens (2003). We compare the properties of estimates based on this new model with those of other joint gene conversion / crossover models, and discuss future work.