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PMID: 19701190 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Genomic privacy and limits of individual detection in a pool.

Nature genetics ·Vol. 41 ·No. 9 ·2009-09-00 ·Pages 965-7

Sankararaman S, Obozinski G, Jordan MI, Halperin E

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.

MeSH Terms
Confidentiality Genome, Human Genome-Wide Association Study/methods,statistics & numerical data Humans Models, Statistical Polymorphism, Single Nucleotide
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Sankararaman Sriram
Computer Science Division, University of California, Berkeley, Berkeley, California, USA.
Obozinski Guillaume
Jordan Michael I
Halperin Eran
References (5)
5 references, click to expand
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    PLoS Genet. 2008 Aug 29;4(8):e1000167 PMID: 18769715
  4. Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci.
    Nat Genet. 2008 Dec;40(12):1399-401 PMID: 18978792
  5. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.
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Article Info
Journal
Nature genetics
Abbr.
Nat Genet
ISSN
1546-1718
Published
2009-09-00
Epub
2009-00-23
Pages
965-7
Language
English
Region
United States
NLM ID
9216904
Subset
IM
Grants
NIGMS NIH HHS · GM071749 · United States
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