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GAMETES specifications


Unique identifier OMICS_15343
Alternative name Genetic Architecture Model Emulator for Testing and Evaluating Software
Software type Package/Module
Interface Graphical user interface
Restrictions to use None
Operating system Windows
Programming languages Java
License GNU General Public License version 2.0
Computer skills Medium
Version 2.1
Stability Stable
Maintained Yes




No version available



  • person_outline Jason Moore

Publication for Genetic Architecture Model Emulator for Testing and Evaluating Software

GAMETES citations


Detecting gene gene interactions using a permutation based random forest method

BioData Min
PMCID: 4822295
PMID: 27053949
DOI: 10.1186/s13040-016-0093-5

[…] active SNPs could then be identified by ranking the different classification errors from the above two permutation schemes. We tested our hypothesis systematically on simulated datasets obtained from Genetic Architecture Model Emulator for Testing and Evaluating Software (GAMETES) with different genetic constraints including heritability, number of SNPs, sample size, etc, and achieved good success […]


Weighted Risk Score Based Multifactor Dimensionality Reduction to Detect Gene Gene Interactions in Nasopharyngeal Carcinoma

Int J Mol Sci
PMCID: 4100176
PMID: 24933637
DOI: 10.3390/ijms150610724

[…] of 400 cases and 400 controls. The other three sets are imbalanced, and the simulated dataset was composed of 1200 cases and 400 controls. All the genetic models and datasets were generated using the Genetic Architecture Model Emulator for Testing and Evaluating Software (GAMETES) []. In particular, GAMETES is designed to generate epistasis models that we refer to as pure and strict. Purely and st […]


A classification and characterization of two locus, pure, strict, epistatic models for simulation and detection

BioData Min
PMCID: 4094921
PMID: 25057293
DOI: 10.1186/1756-0381-7-8

[…] for evaluating and comparing strategies for the detection and modeling of multiple predictive loci.A handful of studies have introduced methods for generating epistatic models [,-] including our own Genetic Architecture Model Emulator for Testing and Evaluating Software (GAMETES) [] designed to randomly generate an architecturally diverse population of pure, strict, epistatic models. Architecture […]


An information gain approach to detecting three way epistatic interactions in genetic association studies

PMCID: 3721169
PMID: 23396514
DOI: 10.1136/amiajnl-2012-001525

[…] We applied both three-way synergy measures and to synthetic datasets and a real dataset on pulmonary tuberculosis from a West African population. The synthetic datasets were generated using genetic architecture model emulator for testing and evaluating software (GAMETES), a direct approach to simulating bi-allelic n-locus epistatic models. In GAMETES, an n-locus epistasis model is gener […]


Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection

BioData Min
PMCID: 3549792
PMID: 23014095
DOI: 10.1186/1756-0381-5-15

[…] EDM: Ease of Detection Measure; SNP: Single nucleotide polymorphism; EA: Evolutionary Algorithm; COR: Customized Odds Ratio; GAMETES: Genetic Architecture Model Emulator for Testing and Evaluating Software; MLG: Multi-locus genotype; HWE: Hardy-Weinberg Equilibrium; MAF: Minor Allele Frequency; K: Population Prevalence; MDR: Multifa […]

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GAMETES institution(s)
Department of Genetics, Institute for Quantitative Biomedical Sciences, Dartmouth Medical School, Lebanon, NH, USA
GAMETES funding source(s)
This work was supported by the William H. Neukom 1964 Institute for Computational Science at Dartmouth College along with NIH grants AI59694, LM009012, and LM010098.

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