High Performance Computing Instrumentation for the Yale Center for Genome Analysis

下一代测序（NGS）的出现正在彻底改变生物学和医学， 成为调查的标准工具。认识到NGS的巨大潜力，耶鲁大学 2009年成立耶鲁基因组分析中心（YCGA）。YCGA领导了一个新的发展， 基因组中心模式，专注于具有最高标准创新、数据生产和管理的集中设施。 和分析，但这是开放的访问社区，而不是有项目选择的监督 组这种可扩展的模式为NGS提供了广泛的访问，这刺激了创新，消除了 新用户体验的障碍。由于其对技术发展的重大贡献， 数据生产和分析，伴随着引人注目的科学发现和成功的竞争， 在NIH的资助下，YCGA已经成为美国领先的基因组中心之一。 高性能计算是NGS操作不可或缺的。YCGA平均生产的 每月超过30万亿次的序列数据，需要数据存储，分析和 解释。YCGA目前的专用HPC仪器已为来自327个国家的1，000多名用户提供服务。 机构/部门以及许多非耶鲁大学的研究人员，并作出了巨大的贡献， 生物医学（自2015年以来发表了>500篇研究论文，其中>70篇发表在Science，Nature，Cell， N Engl J Med）报道了导致自闭症、心血管疾病、癌症和先天性心脏病的新基因。 心脏和大脑的疾病，以及对增强子功能的理解的根本性进展， microRNA的形成机制和进化变化机制。YCGA的专用计算 集群和存储设备的使用时间主要为6年，其生产寿命即将结束。该架构必须 如果YCGA要继续为用户服务，就必须更换和升级。所要求的HPC仪器将 增加计算能力以满足日益增长的需求，将大大改善数据存储和联网， 并且将降低功率和冷却要求。 这项建议的优点包括：（1）一个高效率和高效益的中央设施， 非常多样化，大型和多产的主要是NIH资助的研究者用户群;（2）证明的能力 YCGA有效地整合了尖端数据的生产和分析，为数百个NIH 资助耶鲁大学和非耶鲁大学的研究人员，（3）和广泛的基础设施和专业知识，可用于 使所要求的仪器联机，并监督其持续使用。 耶鲁大学在资金和机构人才方面进行了重大投资， 基础设施已经证明是非常成功的。所要求的仪器将高度利用 这一现有的基础设施，确保它将是高价值和广泛的影响，对美国国立卫生研究院支持的生物医学 以及耶鲁大学内外的基础研究。

The advent of next-generation sequencing (NGS) is revolutionizing biology and medicine and is rapidly becoming a standard tool for investigation. Recognizing the tremendous potential of NGS, Yale University establish the Yale Center for Genome Analysis (YCGA) in 2009. YCGA has led the development of a new genome center model, focusing on a centralized facility with the highest standards of innovation, data production and analysis, but which is open access to the community rather than having projects selected by an oversight group. This scalable model has provided broad access to NGS, which has spurred innovation and eliminated barriers to experimentation by new users. By virtue of its substantial contribution to technology development for data production and analysis, accompanied by high profile scientific discoveries and success in competing for NIH funding, YCGA has emerged as one of the leading genome centers in the country. High-performance computation is indispensable for NGS operation. YCGA produces an average of more than 30 terabases of sequence data per month, necessitating infrastructure for data storage, analysis and interpretation. YCGA’s current dedicated HPC instrumentation has served more than 1,000 users from 327 institutions/departments as well as many non-Yale investigators, and is making an enormous contribution to biomedicine (since 2015 published >500 research articles including, >70 publications in Science, Nature, Cell, N Engl J Med) reporting new genes contributing to autism, cardiovascular disease, cancer, and congenital diseases of the heart and brain, as well as fundamental advances in understanding of enhancer function, mechanisms of microRNA formation, and mechanisms of evolutionary change. YCGA's dedicated compute cluster and storage is predominantly 6 years old and near the end of its productive life. This architecture must be replaced and upgraded if YCGA is to continue to serve its users. The requested HPC instrumentation will increase computational capacity to match growing demand, will greatly improve data storage and networking, and will reduce the power and cooling requirements. The strengths of this proposal include; (1) an efficient and effective centralized facility serving an extremely diverse, large and productive mostly NIH funded investigator user base; (2) the demonstrated ability of YCGA to effectively integrate cutting edge data production and analysis for the benefit of hundreds of NIH funded Yale and non-Yale researchers, (3) and the extensive infrastructure and expertise that is available to bring the requested instrumentation online and to oversee its continuous use. Yale University has made a major investment in capital and institutional talent to build a first-rate infrastructure that has proven highly successful. The requested instrumentation will be highly leveraged upon this existing infrastructure ensuring that it will be of high value and broad impact on NIH supported biomedical and basic research within and beyond the Yale community.