An overview of human genetic privacy.
The study of human genomics is becoming a Big Data science, owing to recent biotechnological advances leading to availability of millions of personal genome sequences, which can be combined with biometric measurements from mobile apps and fitness trackers, and of human behavior data monitored from mobile devices and social media. With increasing research opportunities for integrative genomic studies through data sharing, genetic privacy emerges as a legitimate yet challenging concern that needs to be carefully addressed, not only for individuals but also for their families. In this paper, we present potential genetic privacy risks and relevant ethics and regulations for sharing and protecting human genomics data. We also describe the techniques for protecting human genetic privacy from three broad perspectives: controlled access, differential privacy, and cryptographic solutions.
Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, North Carolina.
Xinghua
X
Shi
Department of Computer Science and Computer Engineering, University of Arkansas, Fayetteville, Arkansas.
Xintao
X
Wu
D001499:Bayes Theorem; D019295:Computational Biology / Q000941:ethics / Q000592:standards / Q000639:trends; D016494:Computer Security; D057225:Data Mining / Q000941:ethics / Q000592:standards / Q000639:trends; D030661:Genetic Privacy / Q000941:ethics / Q000331:legislation & jurisprudence / Q000592:standards / Q000639:trends; D055106:Genome-Wide Association Study; D023281:Genomics / Q000941:ethics / Q000379:methods* / Q000592:standards / Q000639:trends; D006801:Humans; D063731:Mobile Applications / Q000941:ethics / Q000592:standards / Q000639:trends; D012308:Risk Management; D061108:Social Media / Q000941:ethics / Q000592:standards / Q000639:trends
Big Data; ethics; genetic privacy; regulations