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Article

SecureMA: protecting participant privacy in genetic association meta-analysis

21 Aug 2014

Abstract excerpt

MOTIVATION: Sharing genomic data is crucial to support scientific investigation such as genome-wide association studies. However, recent investigations suggest the privacy of the individual participants in these studies can be compromised, leading to serious concerns and consequences, such as overly restricted access to data. RESULTS: We introduce a novel cryptographic strategy to securely perform meta-analysis...

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Source

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Identifiers

PMID: 25147357
DOI: 10.1093/bioinformatics/btu561

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