ASGSCA-package {ASGSCA} | R Documentation |
The package provides tools to model and test the association between multiple genotypes and multiple traits, taking into account the prior biological knowledge. Functional genomic regions, e.g., genes, and clinical pathways are incorporated in the model as latent variables that are not directly observed. The method is based on Generalized Structured Component Analysis (GSCA).
Package: | ASGSCA |
Type: | Package |
Version: | 1.0 |
Date: | 2014-07-30 |
License: | GPL-3 |
Hela Romdhani, Stepan Grinek, Heungsun Hwang and Aurelie Labbe.
Maintainer: Hela Romdhani <hela.romdhani@mcgill.ca>
Romdhani, H., Hwang, H., Paradis, G., Roy-Gagnon, M.-H. and Labbe, A. (2014). Pathway-based Association Study of Multiple Candidate Genes and Multiple Traits Using Structural Equation Models. Submitted.
data(GenPhen) W0 <- matrix(c(rep(1,2),rep(0,8),rep(1,2),rep(0,8),rep(1,3),rep(0,7),rep(1,2)),nrow=8,ncol=4) B0 <- matrix(c(rep(0,8),rep(1,2),rep(0,3),1,rep(0,2)),nrow=4,ncol=4) #Estimation only GSCA(GenPhen,W0, B0,estim=TRUE,path.test=FALSE) #Estimation and test for all the path coefficients in the model GSCA(GenPhen,W0, B0,estim=TRUE,path.test=TRUE) #Test only GSCA(GenPhen,W0, B0,estim=FALSE,path.test=TRUE) #Give names to the latent variables GSCA(GenPhen,W0, B0,latent.names=c("Gene1","Gene2","Clinical pathway 1","Clinical pathway 2"), estim=TRUE,path.test=TRUE) #Testing only a subset of path coefficients GSCA(GenPhen,W0, B0,estim=FALSE,path.test=TRUE,path=matrix(c(1,2,3,4),ncol=2))