Understanding the links between privacy and public data sharing; Nature.com, 2/25/16

David W. Craig, Nature.com; Understanding the links between privacy and public data sharing:

"Researchers are obligated to share results while maintaining reasonable expectations of privacy. However, there are particular challenges in areas of precision medicine where publically shared data sets are both complex and highly dimensional. In the initial genome-wide association studies, it was assumed that aggregating data into summary statistics such as allele frequencies de-identified individuals from clinical cohorts2. However, work from our lab in 2008 showed that this assumption is surprisingly incorrect and that given a person's genotype data, it is possible to determine cohort membership from single-nucleotide polymorphism (SNP) allele-frequency data3. In 2012, Im et al.4 extended these concepts to other summary-level measures such as expression quantitative trait loci (eQTLs), correlating genotype and expression data to determine study participation.

Harmanci and Gerstein focus on another type of privacy breach, linkage attacks, in which sensitive personal data are linked to exploit correlated features across different data sets (reviewed in ref. 5)."