title: Choosing blindly but wisely: differentially private solicitation of DNA datasets for disease marker discovery.
abstract: OBJECTIVE
  To propose a new approach to privacy preserving data selection, which helps the data users access human genomic datasets efficiently without undermining patients' privacy.
  
  
  METHODS
  Our idea is to let each data owner publish a set of differentially-private pilot data, on which a data user can test-run arbitrary association-test algorithms, including those not known to the data owner a priori. We developed a suite of new techniques, including a pilot-data generation approach that leverages the linkage disequilibrium in the human genome to preserve both the utility of the data and the privacy of the patients, and a utility evaluation method that helps the user assess the value of the real data from its pilot version with high confidence.
  
  
  RESULTS
  We evaluated our approach on real human genomic data using four popular association tests. Our study shows that the proposed approach can help data users make the right choices in most cases.
  
  
  CONCLUSIONS
  Even though the pilot data cannot be directly used for scientific discovery, it provides a useful indication of which datasets are more likely to be useful to data users, who can therefore approach the appropriate data owners to gain access to the data.
authors.affiliation: Indiana University, Bloomington, Indiana, USA.
authors.forename: Yongan
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Indiana University, Bloomington, Indiana, USA.
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Wang
authors.affiliation: University of California, San Diego (UCSD), San Diego, California, USA.
authors.forename: Xiaoqian
authors.initials: X
authors.lastname: Jiang
authors.affiliation: University of California, San Diego (UCSD), San Diego, California, USA.
authors.forename: Lucila
authors.initials: L
authors.lastname: Ohno-Machado
authors.affiliation: Indiana University, Bloomington, Indiana, USA.
authors.forename: Haixu
authors.initials: H
authors.lastname: Tang
mesh_terms: D003219:Confidentiality; D004247:DNA; D066264:Datasets as Topic; D005819:Genetic Markers; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D020641:Polymorphism, Single Nucleotide
chemical_list: D005819:Genetic Markers; D004247:DNA
keywords: Differential Privacy; Genome-wide association studies; Haplotype blocks; Privacy-preserving techniques; Single nucleotide polymorphisms (SNPs); Test statistics