Participant identification in genetic association studies: improved methods and practical implications

Nicholas Masca, Paul R Burton, Nuala A Sheehan

Research output: Contribution to journalArticle (Academic Journal)peer-review

16 Citations (Scopus)

Abstract

In a recent paper by Homer et al. (Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet 2008;4:e1000167), a method for detecting whether a given individual is a contributor to a particular genomic mixture was proposed. This prompted grave concern about the public dissemination of aggregate statistics from genome-wide association studies. It is of clear scientific importance that such data be shared widely, but the confidentiality of study participants must not be compromised. The issue of what summary genomic data can safely be posted on the web is only addressed satisfactorily when the theoretical underpinnings of the proposed method are clarified and its performance evaluated in terms of dependence on underlying assumptions.
Original languageEnglish
Pages (from-to)1629-1642
Number of pages14
JournalInternational Journal of Epidemiology
Volume40
Issue number6
DOIs
Publication statusPublished - Dec 2011

Keywords

  • Cohort Studies
  • Ethics, Research
  • Genetic Association Studies
  • Genetic Privacy
  • Genotype
  • Human Experimentation
  • Humans
  • Linear Models
  • Polymorphism, Single Nucleotide
  • Research Design

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