High Performance Computing System for Human Genomics

人类基因组学高性能计算系统

• 批准号: 7840009
• 负责人: John Blangero
• 金额: $ 206.83万
• 依托单位: TEXAS BIOMEDICAL RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-06 至 2011-05-05
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7840009
• 关键词: Aging; Base Sequence; Biomedical Research; Cardiovascular Diseases; Chromosome Mapping; Communicable Diseases; Complex; Computer Systems; Computing Methodologies; Data; Databases; Diabetes Mellitus; Disease; Dissection; Environmental Risk Factor; Equipment; Family; Foundations; Funding; Genes; Genetic; Genomics; Heart; High Performance Computing; Human; Individual; Lead; Mental disorders; Obesity; Occupations; Performance; Play; Pre-Eclampsia; Price; Process; Request for Applications; Research Personnel; Research Project Grants; Role; Science; Speed; Technology; United States National Institutes of Health; Variant; base; design; disorder risk; gene discovery; genetic pedigree; genetic variant; genome wide association study; novel; parallel computing; public health relevance; theories; transcriptomics

DESCRIPTION (provided by applicant): High performance computation lies at the heart of modern human statistical genomics. In the Department of Genetics at the Southwest Foundation for Biomedical Research (SFBR), we specialize in the genetic dissection of human complex diseases that typically involve the actions of many genes and environmental factors. For a given genetic project on complex diseases, we typically generate vast amounts of sequence- based genetic, transcriptomic, and disease-related phenotypic information. Because family-based gene localization and identification studies are substantially more powerful than those undertaken in unrelated individuals, we also focus on studies involving very large extended pedigrees. Statistical genetic theory can be invoked to show that such a design is optimal when rare genetic variants are likely to play a role in disease risk. Accumulating results from genome-wide association studies, which are capable of only finding common disease-related genetic variants, now strongly suggest that rare variants are of substantial importance in human complex disease. However, the utilization of extended pedigree information incurs a strong computational price, since family-based data are non-independent and therefore must be analyzed simultaneously. These issues all lead to the need for ever more powerful computational technologies. In this application, we request funds to purchase a large Opteron-based high performance parallel computing cluster (an M&A 5000 Core Computational Cluster) to specifically aid ongoing research projects with more than $81 million dollars of NIH funding. PUBLIC HEALTH RELEVANCE: The Department of Genetics at the Southwest Foundation for Biomedical Research focuses on understanding the genetic factors involved in human common complex diseases, including cardiovascular disease, diabetes, obesity, aging, pre-eclampsia, psychiatric disorders and infectious diseases. Investigators employ state-of-the science statistical/computational methods to process vast amounts of sequence-based genetic, transcriptomic, and disease-related phenotypic data to localize and identify novel genes influencing disease risk. Acquisition of a high performance parallel computing cluster (the M&A 5000 Core Computational Cluster) will speed the pace of gene discovery in such disorders. The proposed equipment will also significantly enhance both job creation and job retention at the Southwest Foundation for Biomedical Research and M&A Technology, Inc.

描述(申请人提供)：高性能计算是现代人类统计基因组学的核心。在西南生物医学研究基金会(SFBR)的遗传学系，我们专门研究人类复杂疾病的基因解剖，这些疾病通常涉及许多基因和环境因素的作用。对于一个关于复杂疾病的给定基因项目，我们通常会生成大量基于序列的遗传、转录和与疾病相关的表型信息。由于基于家族的基因定位和鉴定研究比在无关个体中进行的研究要强大得多，我们也关注涉及非常大的扩展家系的研究。可以引用统计遗传理论来表明，当罕见的基因变异可能在疾病风险中发挥作用时，这样的设计是最佳的。全基因组关联研究的累积结果现在强烈表明，罕见的变异在人类复杂疾病中具有重要意义。全基因组研究只能找到常见的与疾病相关的遗传变异。然而，由于基于家族的数据不是独立的，因此必须同时进行分析，因此利用扩展的谱系信息会产生很大的计算代价。这些问题都导致了对更强大的计算技术的需求。在此应用程序中，我们申请资金购买一个基于Opteron的大型高性能并行计算集群(一个并购5000核心计算集群)，以专门为正在进行的研究项目提供超过8100万美元的NIH资金。 公共卫生相关性：西南生物医学研究基金会遗传学系专注于了解人类常见的复杂疾病所涉及的遗传因素，包括心血管疾病、糖尿病、肥胖、衰老、先兆子痫、精神障碍和传染病。调查人员使用最先进的科学技术 统计/计算方法来处理大量基于序列的遗传、转录 以及疾病相关表型数据，以定位和识别影响疾病风险的新基因。收购高性能并行计算集群(M&A 5000核心计算集群)将加快此类疾病的基因发现步伐。拟议中的设备还将显著增加西南生物医学研究和并购技术基金会的就业机会和留住就业机会。