title: A new way to protect privacy in large-scale genome-wide association studies.
abstract: BACKGROUND
  Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues.
  
  
  RESULTS
  We show how to conduct such studies without violating privacy of individual donors and without leaking the data to third parties. The presented solution has provable security guarantees.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: Institute of Computer Science, University of Tartu, Liivi 2, Tartu 50409, Estonia.
authors: Liina
authors: L
authors: Kamm
authors: Dan
authors: D
authors: Bogdanov
authors: Sven
authors: S
authors: Laur
authors: Jaak
authors: J
authors: Vilo
mesh_terms: D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D055106:Genome-Wide Association Study; D060005:Genotyping Techniques; D006801:Humans; D018907:Privacy