Genomic privacy and limits of individual detection in a pool

  title={Genomic privacy and limits of individual detection in a pool},
  author={Sriram Sankararaman and Guillaume Obozinski and Michael I. Jordan and Eran Halperin},
  journal={Nature Genetics},
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. 
Highly Cited
This paper has 135 citations. REVIEW CITATIONS
Related Discussions
This paper has been referenced on Twitter 2 times. VIEW TWEETS

From This Paper

Topics from this paper.


Publications citing this paper.
Showing 1-10 of 62 extracted citations

Membership Privacy in MicroRNA-based Studies

ACM Conference on Computer and Communications Security • 2016
View 5 Excerpts
Highly Influenced

Algorithms for Human Genetics

View 5 Excerpts
Method Support
Highly Influenced

Robust Traceability from Trace Amounts

2015 IEEE 56th Annual Symposium on Foundations of Computer Science • 2015
View 4 Excerpts
Highly Influenced

A Secure Alignment Algorithm for Mapping Short Reads to Human Genome.

Journal of computational biology : a journal of computational molecular cell biology • 2018

136 Citations

Citations per Year
Semantic Scholar estimates that this publication has 136 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-2 of 2 references

Testing Statistical Hypotheses (Springer

E. L. Lehmann
New York, • 2005

The Wellcome Trust Case Control Consortium

E. L. Lehmann
Testing Statistical Hypotheses • 2005