Privacy Protection in Sharing Personal Genome Sequencing Data

The past few years has witnessed rapid development in human genome research, in particular the genome-wide association studies (GWAS) and personalized medicine, which has been made possible by the advance in the Next Generation Sequencing (NGS) technologies that produces a large amount of sequencing data at an exceedingly low cost. New technologies for large-scale meta-analysis on genomic data continue to be developed, enabling the application of human genome research to clinical diagnosis and therapy, a trend dubbed “base pairs to bedside”. However, further progress in this area has been increasingly impeded by the constraints in accessing sequencing data, due in part to privacy concerns involved in data sharing. The current approach to protecting human genomic data is mainly based upon data-use agreements, which involves a time-consuming application/review/agreement process. To enable more convenient data access, this paper proposes a data analysis model that allows biomedical researchers and healthcare practitioners to use the sensitive genomic data that cannot be directly released in an efficient fashion, through the computing service over the data (instead of direct access to the data) provided by a large data center.