Privacy preserving technologies for human genome data analysis and dissemination

描述（由申请人提供）：下一代测序（NGS）技术的快速发展显著降低了产生DNA数据的成本。因此，基因组测序可能很快成为临床诊断和治疗选择的常规工具。与此同时，对来自各种疾病患者的人类基因组数据的大规模荟萃分析的需求预计将在不久的将来大幅增长。然而，满足这种需求的努力并没有受益于测序技术的进步，这是由于存储和分析NGS数据所需的大量计算资源以及研究人员访问数据的复杂程序，这些程序是为了保护人类受试者的隐私而设置的。为了应对这些挑战并促进安全方便的DNA数据共享，我们建议研究和开发一套创新和变革性的技术，旨在实现实用和具有成本效益的基因组数据保护。利用这些技术，NIH数据中心可以对其托管的基因组数据提供集中的分析服务，执行数据用户提交的分析程序，并控制分析结果的发布，以确保DNA捐赠者的隐私。我们的技术还将帮助中心外包的计算任务，它没有足够的资源来处理本地和远程租用的计算系统在一个高度保护隐私的方式。拟议的研究将与iDASH密切合作进行，iDASH是一个国家生物医学计算中心，旨在“整合数据以进行分析，分析和共享”，利用其数据来评估我们的技术及其部署它们的基础设施。

DESCRIPTION (provided by applicant): The rapid development of Next Generation Sequencing (NGS) technologies significantly reduces the cost for producing DNA data. As a result, genome sequencing may soon become a routine tool for clinical diagnosis and therapy selection. In the meantime, the demand for large-scale meta-analysis of human genomic data from patients with various diseases is expected to grow substantially in the near future. However, the effort to meet such a demand has not benefited from the progress in sequencing technologies, due to the massive amount of computational resources needed for storing and analyzing the NGS data and the complicated procedures for researchers to get access to the data, which are put in place to protect the privacy of human subjects. To address such challenges and facilitate secure and also convenient DNA data sharing, we propose to study and develop a suite of innovative and transformative techniques aimed at achieving practical and cost-effective genomic data protection. Using these techniques, NIH data center can offer a centralized analysis service on the genome data it hosts; execute the analysis programs submitted by the data users, and control release of analysis outcomes to ensure the privacy of DNA donors. Our techniques will also help the center outsource the computation tasks it does not have sufficient resources to handle to the computing systems rented locally and remotely in a highly privacy-preserving manner. The proposed research will be conducted in a close collaboration with iDASH, a National Center for Biomedical Computing for "integrating Data for Analysis, Anonymization and Sharing", using its data to evaluate our techniques and its infrastructure to deploy them.