Genomic privacy and limits of individual detection in a pool

• Published in: Nature genetics Vol. 41; no. 9; pp. 965 - 967
• Main Authors: Sankararaman, Sriram, Obozinski, Guillaume, Jordan, Michael I, Halperin, Eran
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.09.2009; Nature Publishing Group
• Subjects: Agriculture; Analysis; Animal Genetics and Genomics; Biological and medical sciences; Biomedical and Life Sciences; Biomedicine; brief-communication; Cancer Research; Confidentiality; Diverse techniques; Equilibrium; Forensic sciences; Fundamental and applied biological sciences. Psychology; Gene Function; Genetic research; Genetics; Genetics of eukaryotes. Biological and molecular evolution; Genome, Human; Genome-Wide Association Study - methods; Genome-Wide Association Study - statistics & numerical data; Genomics; Genotype; Human Genetics; Humans; Hypothesis testing; Methods; Models, Statistical; Molecular and cellular biology; Polymorphism, Single Nucleotide; Privacy; Statistical methods; Studies; United States; Detection; Genomics; Pool
• ISSN: 1061-4036; 1546-1718; 1546-1718
• DOI: 10.1038/ng.436

David Craig and colleagues recently reported methods allowing detection of individual genotypes from summary data of high-density SNP arrays. Eran Halperin and colleagues now report analyses of the statistical power of these methods, employing likelihood ratio statistics to provide an upper-bound to the limits of detection. 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.