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Area of Science:

  • Genomic Data Security
  • Bioinformatics
  • Human Genetics

Background:

  • The human genetics community requires secure methods for sharing participant genomic data.
  • Genetic beacons are web servers that respond to allele presence queries with binary outputs.
  • Current beacon technology may not adequately protect participant privacy.

Purpose of the Study:

  • To assess the re-identification risk for individuals within genetic beacons.
  • To develop and evaluate a statistical test for detecting individual membership in a beacon.
  • To determine the feasibility of re-identification under various conditions, including sequencing errors.

Main Methods:

  • Development of a likelihood-ratio test to determine if a specific individual is present in a genetic beacon.
  • Simulation studies using varying beacon sizes and query numbers.
  • Empirical testing on real-world datasets, including the 1000 Genomes Project and Personal Genome Project.

Main Results:

  • Re-identification of individuals in a beacon of 1,000 participants is possible with as few as 5,000 queries.
  • Detection of beacon membership is feasible with a limited number of single nucleotide polymorphism (SNP) queries (e.g., 250 SNPs for 65 individuals).
  • The proposed likelihood-ratio test is powerful and independent of allele frequencies, even with sequencing errors.

Conclusions:

  • Genetic beacons, as currently implemented, do not inherently protect participant privacy.
  • Membership and potential phenotypic information can be disclosed through beacon queries.
  • Risk mitigation strategies, such as minimum beacon sizes and policy controls, are necessary.