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

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Ressource 1Download: 2017 Kutalik_Bioinformatics .pdf (2536.07 [Ko])
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Version: Author's accepted manuscript
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Serval ID
serval:BIB_879380F4DFDC
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
SQC: secure quality control for meta-analysis of genome-wide association studies.
Journal
Bioinformatics
Author(s)
Huang Z., Lin H., Fellay J., Kutalik Z., Hubaux J.P.
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Publication state
Published
Issued date
01/08/2017
Peer-reviewed
Oui
Volume
33
Number
15
Pages
2273-2280
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
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.
In this article, we propose a secure quality control (SQC) protocol, which enables checking the quality of data in a privacy-preserving way without revealing sensitive information to a potential adversary. SQC employs state-of-the-art cryptographic and statistical techniques for privacy protection. We implement the solution in a meta-analysis pipeline with real data to demonstrate the efficiency and scalability on commodity machines. The distributed execution of SQC on a cluster of 128 cores for one million genetic variants takes less than one hour, which is a modest cost considering the 10-month time span usually observed for the completion of the QC procedure that includes timing of logistics.
SQC is implemented in Java and is publicly available at https://github.com/acs6610987/secureqc.
jean-pierre.hubaux@epfl.ch.
Supplementary data are available at Bioinformatics online.
Keywords
Confidentiality, Genome-Wide Association Study/methods, Genome-Wide Association Study/standards, Humans, Meta-Analysis as Topic, Quality Control
Pubmed
Web of science
Open Access
Yes
Create date
11/04/2017 16:56
Last modification date
01/02/2020 6:19
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