A large scale genome simulation model incorporating patterns of linkage disequilibrium

Evaluation of multiple hypotheses is a common problem, especially in genome wide association studies. False Discovery Rate control is often used to correct for multiple comparisons. However, this approach is influenced by linkage disequilibrium and needs to be evaluated. For such evaluation, first a model needs to be developed with a simulated linkage disequilibrium pattern that matches as closely as possible the observed linkage disequilibrium structure. This paper outlines the steps involved in the development of such a model, using mouse genome data as an example.