CC* Integration-Small: Harnessing FABRIC for Scalable Human Genome Sequence Analysis

人类基因组包含有价值的信息，可为治疗危及生命的疾病和改善健康结果提供新方法。然而，人类基因组的规模非常大，需要大量的计算、网络和存储资源进行处理和分析。该项目的目标是利用FABRIC （https://fabric-testbed.net，一个nsf资助的国家研究基础设施）对人类基因组序列进行高效、安全的处理和分析。学生将参与该项目的研究和推广活动。将开发软件，供教育和研究界广泛使用。该项目将带来一套新的算法和技术，利用集群计算技术和FABRIC上可用的尖端可编程硬件，大规模高效、安全地处理和分析人类基因组。研究重点包括(a)使用硬件加速器和大数据工具加速变体调用管道，(b)使用先进的网络功能安全有效地处理基因组，以及(c)将FABRIC资源与CloudLab （https://cloudlab）相结合的工作负载分配方案。us/（另一个nsf资助的试验台）用于基因组处理。FABRIC和CloudLab的测量数据将被收集以供进一步分析。该项目将推动可扩展的人类基因组序列分析技术的发展，这对于癌症等复杂疾病的预防和治疗以及药物发现至关重要。它将带来一个开源软件，用于大规模、经济高效的人类基因组序列分析，使用尖端的、无处不在的可编程测试平台。调查结果将以出版物、软件、数据集和培训材料的形式传播。将为计算机科学和信息学的学生开发新的课程。将为高中生举办夏令营。该项目网站位于https://github.com/MU-Data-Science/GAF。该存储库将在项目完成后维持5年。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Human genomes contain valuable information that can enable new ways of treating life-threatening diseases and improving health outcomes. However, human genomes are very large in size and require substantial computing, networking, and storage resources for processing and analysis. The goal of this project is to leverage FABRIC (https://fabric-testbed.net, an NSF-funded national research infrastructure) for efficient and secure processing and analysis of human genome sequences. Students will be involved in the research and outreach activities of the project. Software will be developed for broader use by the education and research community.This project will lead to a suite of new algorithms and techniques for efficient and secure processing and analysis of human genomes at scale using cluster computing technologies and cutting-edge, programmable hardware available on FABRIC. The research thrusts include (a) acceleration of variant calling pipelines using hardware accelerators and Big Data tools, (b) secure and efficient processing of genomes using advanced networking capabilities, and (c) a workload distribution scheme for combining the resources of FABRIC with CloudLab (https://cloudlab.us/, another NSF-funded testbed) for genome processing. Measurement data on FABRIC and CloudLab will be collected for further analysis.This project will advance the state of the art in scalable human genome sequence analysis, which is essential for the prevention and treatment of complex diseases like cancer as well as drug discovery. It will lead to an open source software for large-scale, cost-effective human genome sequence analysis using cutting-edge, everywhere programmable testbeds. The findings will be disseminated in the form of publications, software, datasets, and training materials. New coursework will be developed for computer science and informatics students. A summer camp will be conducted for high school students.The project website is hosted at https://github.com/MU-Data-Science/GAF. This repository will be maintained for 5 years after the completion of the project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.