Beowulf LINUX Cluster Computer

描述（由申请人提供）：人类基因组计划的主要目标是获取遗传信息，以了解和预防和/或治疗人类疾病。最近完成的人类基因组测序“草案”和生物技术的最新进展使基因分型样品的快速处理量成为可能，这创造了巨大的信息资源。然而，解剖影响常见疾病易感性的遗传和环境因素的挑战仍然是统计复杂和计算密集型的。波士顿大学医学院的遗传流行病学家和统计遗传学家在识别与简单孟德尔疾病以及复杂性状风险相关的基因方面有着悠久的成功历史。为了延续这一成功并实现统计遗传学的最新进展，我们正在申请一个Beowulf级的192个Intel处理器的Linux集群。该计算系统将专门用于遗传分析，包括连锁分析和关联测试。该系统将支持14个NIH资助项目的研究。虽然表型和研究人群之间的资助项目的主要用户有很大的不同，有大量的计算密集型遗传分析技术，将在这个系统上进行重叠。该集群将使身份的计算通过扩展谱系中的体面关系，通过模拟计算经验p值，以及复杂的基因与基因和基因与环境相互作用模型的应用。政府承诺为全职系统管理员提供资金并长期支持升级和维护，这证明了对该系统的强有力的机构支持。将该计算资源置于该提案的调查人员中将在遗传学领域产生广泛的影响，并进一步加深我们对亨廷顿氏病、阿尔茨海默氏病、肥胖、中风和止血因素的遗传学的理解，认知能力下降，高血压，心血管特征，以及可卡因和阿片类药物依赖等。

DESCRIPTION (provided by applicant): 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.