Privacy-preserving data exploration in genome-wide association studies

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn Part F128815, Issue , 2013, Pages 1079-1087

  Johnson, Aaron ^a   Shmatikov, Vitaly ^b  

^a NAVAL RESEARCH LABORATORY   (United States)

^b UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

Differential privacy; Genome wide association studies

Indexed keywords

DATA MINING; DNA SEQUENCES; GENES; STATISTICAL TESTS;

COLLABORATIVE RESEARCH; DIFFERENTIAL PRIVACIES; DNA SEQUENCE VARIATIONS; EXPLORATORY DATA ANALYSIS; GENOME-WIDE ASSOCIATION STUDIES; PRIVACY PRESERVING; PRIVACY-PRESERVING DATA MINING ALGORITHMS; REAL-WORLD DATASETS;

DATA PRIVACY;

EID: 84995401548     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2487575.2487687     Document Type: Conference Paper

References (35)

1. J. Barrett et al. Haploview: Analysis and visualization of LD and haplotype maps. Bioinformatics, 21(2), 2005.
2. R. Bhaskar et al. Discovering frequent patterns in sensitive data. In KDD, 2010.
3. H. Brenner and K. Nissim. Impossibility of differentially private universally optimal mechanisms. In FOCS, 2010.
4. G. Church et al. Public access to genome-wide data: Five views on balancing research with privacy and protection. PLoS Genet, 5(10), 2009.
5. R. Duerr et al. A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science, 314(5804), 2006.
6. C. Dwork et al. Calibrating noise to sensitivity in private data analysis. In TCC, 2006.
7. C. Dwork and J. Lei. Differential privacy and robust statistics. In STOC, 2009.
8. S. Fienberg, A. Slavkovic, and C. Uhler. Privacy preserving GWAS data sharing. In PADM, 2011.
9. S. Gabriel et al. The structure of haplotype blocks in the human genome. Science, 296(5576), 2002.
10. A. Ghosh, T. Roughgarden, and M. Sundararajan. Universally utility-maximizing privacy mechanisms. In STOC, 2009.
11. M. Hay et al. Accurate estimation of the degree distribution of private networks. In ICDM, 2009.
12. N. Homer et al. Resolving individuals contributing trace amounts of DNA to highly complex mixtures using highdensity SNP genotyping microarrays. PLoS Genet, 4, 2008.
13. D. Hunter et al. A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nature Genetics, 39(7), 2007.
14. International HapMap Constortium. A second generation human haplotype map of over 3.1 million SNPs. Nature, 449, 2007.
15. A. Johnson and V. Shmatikov. Privacy-preserving data exploration in genome-wide association studies. Technical Report TR-13-13, The University of Texas at Austin, Department of Computer Science, 2013.
16. A. Korolova et al. Releasing search queries and clicks privately. In WWW, 2009.
17. N. Li and T. Li. t-closeness: Privacy beyond k-Anonymity and l-diversity. In ICDE, 2007.
18. G. Loukides, A. Gkoulalas-Divanis, and B. Malin. Anonymization of electronic medical records for validating genome-wide association studies. Proc. of NAS, 107(17), 2010.
19. A. Machanavajjhala et al. l-diversity: Privacy beyond kanonymity. TKDD, 1(1), 2007.
20. F. McSherry and R. Mahajan. Differentially-private network trace analysis. CCR, 41(4), 2010.
21. F. McSherry and I. Mironov. Differentially private recommender systems: Building privacy into the Netflix Prize contenders. In KDD, 2009.
22. F. McSherry and K. Talwar. Mechanism design via differential privacy. In FOCS, 2007.
23. K. Nissim, S. Raskhodnikova, and A. Smith. Smooth sensitivity and sampling in private data analysis. In STOC, 2007.
24. D. Reshef et al. Detecting novel associations in large data sets. Science, 334(6062), 2011.
25. A. Roth and T. Roughgarden. Interactive privacy via the median mechanism. In STOC, 2010.
26. S. Sankararaman et al. Genomic privacy and limits of individual detection in a pool. Nature Genetics, 41(9), 2009.
27. L. Scott et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science, 2007.
28. R. Sladek et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature, 445(7130), 2007.
29. L. Sweeney. Achieving k-Anonymity privacy protection using generalization and suppression. 10(5), 2002.
30. A. Tamhane and D. Dunlop. Statistics and Data Analysis: from Elementary to Intermediate. Prentice-Hall, Inc., 2000.
31. D. Vu and A. Slavkovic. Differential privacy for clinical trial data: Preliminary evaluations. In ICDMW, 2009.
32. N. Wang et al. Distribution of recombination crossovers and the origin of haplotype blocks: The interplay of population history, recombination, and mutation. The American Journal of Human Genetics, 71(5), 2002.
33. R. Wang, Y. Li, et al. Learning your identity and disease from research papers: Information leaks in genome wide association study. In CCS, 2009.
34. M. Yeager et al. Genome-wide association study of prostate cancer identifies a second risk locus at 8q24. Nature Genetics, 39(5), 2007.
35. E. Zerhouni and E. Nabel. Protecting aggregate genomic data. Science, 322(5898), 2008.