SQC: secure quality control for meta-analysis of genome-wide association studies | Zendy

Zhicong Huang | Zendy; Lin Huang | Zendy; Jacques Fellay | Zendy; Zoltán Kutalik | Zendy; JeanPierre Hubaux | Zendy

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SQC: secure quality control for meta-analysis of genome-wide association studies

Author(s) -

Zhicong Huang,

Lin Huang,

Jacques Fellay,

Zoltán Kutalik,

JeanPierre Hubaux

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx193

Subject(s) - quality (philosophy) , genome wide association study , computer science , association (psychology) , genetic association , meta analysis , control (management) , computational biology , biology , genetics , medicine , artificial intelligence , single nucleotide polymorphism , psychology , gene , philosophy , epistemology , psychotherapist , genotype

Due to the limited power of small-scale genome-wide association studies (GWAS), researchers tend to collaborate and establish a larger consortium in order to perform large-scale GWAS. Genome-wide association meta-analysis (GWAMA) is a statistical tool that aims to synthesize results from multiple independent studies to increase the statistical power and reduce false-positive findings of GWAS. However, it has been demonstrated that the aggregate data of individual studies are subject to inference attacks, hence privacy concerns arise when researchers share study data in GWAMA.

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