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生产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，在不久的将来，对各种疾病患者的人类基因组数据进行大规模荟萃分析的需求预计将大幅增长。然而，满足这一需求的努力并没有受益于测序技术的进步，因为存储和分析NGS数据需要大量的计算资源，研究人员获取数据的程序也很复杂，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，促进安全便捷的DNA数据共享，我们建议研究和开发一套创新和变革的技术，旨在实现实用和成本效益高的基因组数据保护。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分析服务；执行数据用户提交的分析程序，控制分析结果的发布，确保DNA供体的隐私。我们的技术还将以高度保护隐私的方式帮助中心将其没有足够资源来处理的计算任务外包给本地和远程租用的计算系统。拟议的研究将与国家生物医学计算中心iDASH密切合作进行，该中心致力于“整合数据进行分析、匿名化和共享”，利用其数据评估我们的技术及其部署技术的基础设施。

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.