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Privacy-preserving data exploration software tools | Genome-wide association analysis

Privacy-preserving data exploration software tools | Genome-wide association analysis

Genome-wide association studies (GWAS) are a cornerstone of genotype–phenotype association in humans. These studies use various statistical tests to measure which polymorphisms in the genome are important for a given phenotype and which are not. With the increasing collection of genomic data in the clinic, there has been a push towards using this information to validate classical GWAS findings and generate new ones (Weber et al., 2009). Unfortunately, there is growing concern that the results of these studies might lead to loss of privacy for those who participate in them (Erlich and Narayanan, 2014; Homer et al., 2008; Lumley and Rice, 2010).

References:
(Weber et al., 2009) The Shared Health Research Information Network (SHRINE): a prototype federated query tool for clinical data repositories. J Am Med Inform Assoc.
(Erlich and Narayanan, 2014) Routes for breaching and protecting genetic privacy. Nat Rev Genet.
(Homer et al., 2008) Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet.
(Lumley and Rice, 2010) Potential for revealing individual-level information in genome-wide association studies. JAMA.

Source text:
(Simmons and Berger, 2016) Realizing privacy preserving genome-wide association studies. Bioinformatics.

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