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Participant identification in genetic association studies: improved methods and practical implications
Author(s) -
Nicholas G. D. Masca,
Paul R. Burton,
Nuala A. Sheehan
Publication year - 2011
Publication title -
international journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.406
H-Index - 208
eISSN - 1464-3685
pISSN - 0300-5771
DOI - 10.1093/ije/dyr149
Subject(s) - identification (biology) , association (psychology) , genetic association , computational biology , medicine , genetics , biology , computer science , psychology , genotype , single nucleotide polymorphism , gene , botany , psychotherapist
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.

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