GWGGI specifications


Unique identifier OMICS_25315
Alternative name genome-wide gene-gene interaction analyses
Software type Application/Script
Interface Graphical user interface
Restrictions to use Academic or non-commercial use
Output data Statistical significance of detected gene-gene interactions and the marginal contribution of each genetic variant.
Operating system Unix/Linux, Mac OS, Windows
Programming languages C++
Computer skills Medium
Version 1.0
Stability Stable
Source code URL
Registration required Yes
Maintained Yes



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  • person_outline Qing Lu <>

Additional information

Publication for genome-wide gene-gene interaction analyses

GWGGI in publications

PMCID: 5287119
PMID: 28154506
DOI: 10.5808/GI.2016.14.4.160

[…] such tests are computationally demanding and methodologically challenging. recently, a simple but powerful method, named “boolean operation-based screening and testing” (boost), was proposed for genome-wide gene-gene interaction analyses. boost was designed with a boolean representation of genotype data and is approximately equivalent to the log-linear model. it is extremely fast, […]

PMCID: 4564769
PMID: 26442103
DOI: 10.3389/fgene.2015.00285

[…] independent snps additively contributing to the phenotype. as a result, random forests are lacking clear interpretation., more recently, another tree assembling software program was developed: gwggi (wei and lu, ). it differs from the previous methods in two points. first, it uses a tree-growing algorithm which is more computationally efficient (lu et al., ): the standard variable […]

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GWGGI institution(s)
Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA; Department of Biostatistics and Epidemiology, University of North Texas Health Science Center, Fort Worth, TX, USA
GWGGI funding source(s)
Supported by the National Institute on Drug Abuse under Award Number K01DA033346 and by the National Institute of Dental & Craniofacial Research under Award Number R03DE022379.

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