GAMuT: Gene Association with Multiple Traits
In Broadaway et al. (2016), we created a test based on kernel distance-covariance methodology called GAMuT for gene-based association testing of rare variants with multiple phenotypes in a sample of unrelated subjects. The analyzed phenotypes can be either continuous or categorical in nature. The method also allows for adjustment of covariates using adjusted residuals.
GAMuT is implemented as a set of R routines, which can be executed within an R environment.
The R environment
R is a widely-used, free and open source software environment for statistical computing and graphics. The most recent version of R can be downloaded from the Comprehensive R Archive Network (CRAN) CRAN provides precompiled binary versions of R for Windows, MacOS, and select Linux distributions that are likely sufficient for many users' needs. Users can also install R from source code; however this may require a significant amount of effort. For specific details on how to compile, install, and manage R and R-packages, refer to the manual R Installation and Administration.
R packages required for analysis
GAMuT requires the installation of the following R library:
The easiest method to install these packages is with the following command entered in an R shell:
One can also install R packages from the command line.
For the example, we provide sample files consisting of 1000 unrelated variants possessing 6 phenotypes and who are sequenced for a set of rare variants in a gene of interest. We show in our example R code how to implement the GAMuT test to perform an association test between the 6 phenotypes and the rare variants within the gene of interest.
In the GAMuT example analysis page, we provide a step-by-step instruction on how the GAMuT code operates here.
Questions and technical support
For questions or concerns with the GAMuT R routines, please contact Richard Duncan and Michael Epstein
We appreciate any feedback you have with our site and instructions.