title: Genomic privacy and limits of individual detection in a pool.
abstract: Recent studies have demonstrated that statistical methods can be used to detect the presence of a single individual within a study group based on summary data reported from genome-wide association studies (GWAS). We present an analytical and empirical study of the statistical power of such methods. We thereby aim to provide quantitative guidelines for researchers wishing to make a limited number of SNPs available publicly without compromising subjects' privacy.
authors.affiliation: Computer Science Division, University of California, Berkeley, Berkeley, California, USA.
authors.forename: Sriram
authors.initials: S
authors.lastname: Sankararaman
authors.forename: Guillaume
authors.initials: G
authors.lastname: Obozinski
authors.forename: Michael I
authors.initials: MI
authors.lastname: Jordan
authors.forename: Eran
authors.initials: E
authors.lastname: Halperin
mesh_terms: D003219:Confidentiality; D015894:Genome, Human; D055106:Genome-Wide Association Study / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide
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