Two-stage design of sequencing studies for testing association with rare variants

Multiple rare variants have been suggested as accounting for some of the associations with common single nucleotide polymorphisms identified in genome-wide association studies or possibly some of the as yet undiscovered heritability. We consider the power of various approaches to designing substudies aimed at using next-generation sequencing technologies to discover novel variants and to select some subsets that are possibly causal for genotyping in the original case-control study and testing for association using various weighted sum indices. We find that the selection of variants based on the statistical significance of the case-control difference in the subsample yields good power for testing rare variant indices in the main study, and that multivariate models including both the summary index of rare variants and the associated common single nucleotide polymorphisms can distinguish which is the causal factor. By simulation, we explore the effects of varying the size of the discovery subsample, choice of index, and true causal model.