Genome-wide association studies for complex diseases are being initiated throughout the world. Accelerated by the arrival of genotyping technologies that have made typing dense but fixed sets of SNPs feasible for the first time, these studies will very soon create a bottleneck at the point where management and analysis of this data, as well as the design of large-scale follow-up experiments will be required. We propose to develop a series of methods which combine genome-wide association data, Human HapMap reference data and external genomics resources to powerfully analyze these data sets and, in addition, will implement and disseminate an integrated and user friendly system for interacting with and using the results of these analyses. ? ? Finding the genes underlying complex diseases offers one of the best long-term prospects for developing the understanding of disease required to develop truly successful preventions and cures. Genome-wide association studies are being undertaken but without optimal methods for analyzing this data and adequate software tools for interpreting the results, these studies will not realize their potential of opening up new avenues for disease research. This proposal aims to meet those analytic and computational needs so that the many studies being undertaken now and in upcoming years will be able to see their full impact. ? ? ?
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