Differentially private genome data dissemination through top-down specialization

Shuang Wang, Noman Mohammed*, Rui CHEN

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

Advanced sequencing techniques make large genome data available at an unprecedented speed and reduced cost. Genome data sharing has the potential to facilitate significant medical breakthroughs. However, privacy concerns have impeded efficient genome data sharing. In this paper, we present a novel approach for disseminating genomic data while satisfying differential privacy. The proposed algorithm splits raw genome sequences into blocks, subdivides the blocks in a top-down fashion, and finally adds noise to counts to preserve privacy. The experimental results suggest that the proposed algorithm can retain certain data utility in terms of a high sensitivity.

Original languageEnglish
Article numberS2
JournalBMC Medical Informatics and Decision Making
Volume14
Issue number1
DOIs
Publication statusPublished - 8 Dec 2014

Scopus Subject Areas

  • Health Policy
  • Health Informatics

User-Defined Keywords

  • data dissemination
  • differential privacy
  • Genome-wide association studies (GWAS)

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