High-Throughput Computing for Genomics and Bioinformatics Research

用于基因组学和生物信息学研究的高通量计算

基本信息

批准号：
10176848
负责人：
Adrian V Lee
金额：
$ 57.36万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-01 至 2022-06-30
项目状态：
已结题

项目摘要

Biomedical researchers have an increasing ability to comprehensively interrogate cell and molecular biology, for example with advanced imaging and next-generation sequencing. These techniques are producing datasets of increasing size and complexity and necessitate high-performance computing for biomedical researchers. Results from these studies are rapidly changing our understanding of normal development, our taxonomy of disease, and ultimately will enable precision medicine. Recognizing the importance of data science in precision medicine, the Institute for Precision Medicine (IPM) and the University of Pittsburgh invested in a high-throughput computing cluster (HTC), with infrastructure suited for memory-intensive and IO-intensive genomic and bioinformatic operations, and an education program dedicated to enabling computing for health science researchers. The HTC is located in the Center for Research Computing (CRC), a secure and centralized enterprise facility providing computing resources to the whole of the University. The CRC provides a scalable model for research computing with expertise in use and monitoring of advanced computing. In 2015, the HTC was installed with 16 nodes (256 cores). Usage of the HTC grew rapidly (2016 - 0.5M core-hours to 2019 – 3.1M core-hours), and despite the addition of computing nodes in 2017 (4 nodes), 2018 (4 nodes) and 2019 (16 nodes) the system often runs at capacity. Furthermore, the nodes have reached their useable lifespan. In this application, we are requesting funds to replace the HTC cluster and increase computing availability with a new cluster of 20 CPU nodes (960 cores) and 8 GPU cards, 2 CPU nodes as application servers, and 1.2 PB of BeeGFS storage, all linked by Infiniband HDR networking. The new HTC cluster is dedicated to NIH-funded research in biomedical science including medicine, pediatrics, cancer, immunology, and other areas. To assist health science researchers, the IPM, CRC and the health science library system (HSLS) support institution-wide licenses from numerous analysis and bioinformatics software suites, several of which are installed on the HTC server. Importantly, HSLS and CRC provide education outreach through workshops for command line tools, R for genomics and software suites. Researchers using software suites such as CLC Genomics, Open OnDemand, or command line can transparently migrate data and perform analysis on the multi-core HTC. IPM collaboration with the CRC ensures that the new HTC cluster will be operated in the most cost-effective and efficient manner and will be of high value to health sciences researcher performing NIH-supported research. This collaborative effort significantly reduces barriers for biomedical researchers needing to perform computational research.

生物医学研究人员具有越来越多的全面询问细胞和分子生物学的能力，例如，使用高级成像和下一代测序。这些技术正在生产大小和复杂性的增加数据集以及生物医学的必要高性能计算研究人员。这些研究的结果正在迅速改变我们对正常发展的理解疾病的分类法，最终将启用精确医学。认识到数据科学在精密医学中的重要性，精密医学研究所（IPM）匹兹堡大学投资了一个高通量计算集群（HTC），其基础设施适用于记忆密集型和IO密集型基因组和生物信息学操作，以及一个教育计划致力于为健康科学研究人员提供计算。 HTC位于中心研究计算（CRC）是一种安全的集中式企业设施，为计算资源提供了整个大学。 CRC提供了具有使用专业知识的研究计算的可扩展模型，监视高级计算。 2015年，HTC安装了16个节点（256个核心）。使用 HTC迅速增长（2016年至2019年核心小时至2019年的核心小时），并增加计算 2017年的节点（4个节点），2018年（4个节点）和2019年（16个节点），该系统通常以容量运行。此外，节点已经达到了可用的寿命。在此应用程序中，我们要求资金替换HTC 群集并增加了20个CPU节点（960个内核）和8张GPU卡的新群集的计算可用性， 2个CPU节点作为应用程序服务器，BeeGFS存储的1.2 pb，为Infiniband HDR网络链接。新的HTC集群致力于NIH资助的生物医学研究研究，包括医学，儿科，癌症，免疫学和其他领域。为了帮助健康科学研究人员，IPM，CRC和健康科学图书馆系统（HSLS）支持众多分析和生物信息学的机构许可证软件套件，其中几个安装在HTC服务器上。重要的是，HSL和CRC提供通过命令行工具的研讨会教育宣传，用于基因组学和软件套件的R。使用软件套件的研究人员，例如CLC基因组学，开放式ONDEMAND或命令行可以透明地迁移数据并对多核HTC进行分析。 IPM与CRC合作确保新的HTC群集将以最具成本效益和高效的方式运行，并将对健康科学的高价值研究人员进行NIH支持的研究。这项协作努力显着减少了生物医学研究人员的障碍，需要进行计算研究。

项目成果

期刊论文数量（21）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

ESR1 fusion proteins invoke breast cancer subtype-dependent enrichment of ligand independent pro-oncogenic signatures and phenotypes.

ESR1融合蛋白引起乳腺癌亚型依赖性配体独立的促癌特征和表型的富集。

DOI：
10.1101/2023.09.18.558175
发表时间：
2023
期刊：
bioRxiv : the preprint server for biology
影响因子：
0
作者：
Yates,MeganE;Li,Zheqi;Li,Yiting;Guzolik,Hannah;Wang,Xiaosong;Liu,Tiantong;Hooda,Jagmohan;Atkinson,JenniferM;Lee,AdrianV;Oesterreich,Steffi
通讯作者：
Oesterreich,Steffi

Defining spatiotemporal gene modules in liver regeneration using Analytical Dynamic Visual Spatial Omics Representation (ADViSOR).