Secure-GWAS statistics

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Secure-GWAS specifications

Information


Unique identifier OMICS_29737
Name Secure-GWAS
Alternative name Secure-Genome-Wide Association Study
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C, C++
License MIT License
Computer skills Advanced
Stability Stable
Requirements
clang++ compiler, GMP library, libssl-dev, NTL
Maintained Yes

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  • person_outline Bonnie Berger <>
  • person_outline Hoon Cho <>

Publication for Secure-Genome-Wide Association Study

Secure-GWAS in publications

 (3)
PMCID: 4699166
PMID: 26733307
DOI: 10.1186/1472-6947-15-S5-S4

[…] to the bitlength of secret shared values., our implementation incorporates all optimizations and uses parameters ℓ 1 = 11 and ℓ 2 = 21 computed as described in the optimizations subsection of the secure gwas computation section (ℓ 2 = 35 + |k| would be required for integer division, but a lower parameter is requested precision). we can see from the table that sufficient with floating point […]

PMCID: 4699163
PMID: 26733045
DOI: 10.1186/1472-6947-15-S5-S2

[…] genomic datasets. our method is to layer the gwas computations on top of secure multi-party computation (mpc) systems. this approach allows two parties in a distributed system to mutually perform secure gwas computations, but without exposing their private data outside., we demonstrate our technique by implementing a framework for minor allele frequency counting and χ2 statistics calculation, […]

PMCID: 3605601
PMID: 23413435
DOI: 10.1093/bioinformatics/btt066

[…] computation techniques, e.g. (fully) homomorphic encryption. however, these techniques are significantly slower and less feasible on the large genome databases., depicts the overall workflow of secure gwas. the core of such a system consists of three or more dedicated data centers (hosts) that are assumed to be independent organizations. for a worldwide study, these can be biobanks […]


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Secure-GWAS institution(s)
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Department of Computer Science, Stanford University, Stanford, California, USA; Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Secure-GWAS funding source(s)
Supported by the US National Institutes of Health GM108348, by Kwanjeong Educational Foundation and by fellowships from the Simons and National Science Foundations.

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