Securing Genomic Computations for Research and Clinical Decision Support

The use of genomic information holds great promise in understanding, diagnosing, and treating human disease. This promise, however, is tempered by an equally significant threat to individual privacy. Recent work has shown that even anonymized genomic data is vulnerable to reidentification attacks, demanding new techniques for protecting data in research and clinical settings. This paper describes Genecloud, a secure framework for storing and analyzing genomic data. Genecloud balances data access and privacy considerations by applying persistent governance to sensitive information and to the analytics that operate upon it, managing the interaction between the two. As a practical application of the framework, we describe several models for integration with PAPAyA, a full-featured clinical decision support platform created by Philips to bring next generation sequencing and analysis into the clinic.