A major goal of the human genome initiative is to access genetic information to understand and to prevent and/or treat human disease. The recently completed """"""""draft"""""""" sequencing of the human genome and the recent advances in biotechnology that allow rapid throughput of samples for genotyping have created a vast resource of information. However, the challenge to dissect the genetic and environmental factors influencing susceptibility for common diseases remains statistically complex and computationally intensive. The genetic epidemiologists and statistical geneticists at the Boston University Medical Campus have a long history of success in identifying genes associated with risk for both simple Mendelian diseases as well as complex traits. In order to continue this success and to implement the most recent advances in statistical genetics, we are requesting, a Beowulf class LINUX cluster of 192 Intel processors. This computing system will be dedicated to genetic analysis including linkage analyses and association testing. The system will support the research of 14 NIH funded projects. Although the phenotypes and study populations differ widely among the funded projects of the major users, there is substantial overlap in the computationally intensive genetic analysis techniques that will be performed on this system. This cluster will enable computation of identity by decent relationships in extended pedigrees, computation of empirical p-values via simulation, and application of complex gene by gene and gene by environment interaction models. There is strong institutional support for this system evidenced by the administration's commitment to funding a full time systems administrator and long term support of upgrades and maintenance The placement of this computing resource among the investigators of this proposal will have a broad impact in the field of genetics and further our understanding of the genetics of Huntington's Disease, Alzheimer's Disease, Obesity, Stroke and Hemostatic Factors, Cognitive Decline, Hypertension, Cardiovascular traits, and Cocaine and Opioid Dependency among others.
