Deterministic identification of specific individuals from GWAS results.

ABSTRACT:

Motivation

Genome-wide association studies (GWASs) are commonly applied on human genomic data to understand the causal gene combinations statistically connected to certain diseases. Patients involved in these GWASs could be re-identified when the studies release statistical information on a large number of single-nucleotide polymorphisms. Subsequent work, however, found that such privacy attacks are theoretically possible but unsuccessful and unconvincing in real settings.

Results

We derive the first practical privacy attack that can successfully identify specific individuals from limited published associations from the Wellcome Trust Case Control Consortium (WTCCC) dataset. For GWAS results computed over 25 randomly selected loci, our algorithm always pinpoints at least one

SUBMITTER: Cai R 

PROVIDER: S-EPMC4443672 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature