Stanford University cryptographer Dan Boneh and geneticist Gill Bejerano have developed a secure multiparty computation (SMC) algorithm to discover disease-linked genetic mutations without actually seeing anyone's genome, making the protection of genomic privacy practical.
The researchers combined the SMC technique of Yao's protocol with genomics to yield three distinct types of privacy-securing analyses, and in one example sought the most common mutations in patients with four rare diseases.
In each case they revealed the known causal gene, and also diagnosed a baby's sickness by comparing his genome with those of his parents. In addition, the team found a previously unknown disease gene by having two hospitals search their genomic databases for patients with identical mutations, without disclosing their full genomes.
Stanford's Karthik Jagadeesh says genomic privacy not only eases the worries of genome database caretakers, but also offers help for "second- and third-degree relatives, [who] share a significant fraction of the genome."
From Scientific American
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