iGC is an integrated analysis package of gene expression and copy number alteration. It can identify differentially expressed gene driven by copy number alterations (CNA) from samples with both gene expression and CNA data.
One can directly install iGC from Bioconductor 3.2+ (released in Oct 2015),
source("http://www.bioconductor.org/biocLite.R")
biocLite('iGC')
Otherwise, including installing the development version of iGC, one can install by devtools.
install.packages("devtools")
devtools::install_github("ccwang002/iGC", build_vignettes = TRUE)
Note: Some requisites are needed on some platforms.
For example, Rtools is required on Windows; Xcode is required on OSX; A compiler and various development libraries are needed on Linux (details vary across different distros).
One can view the vignettes and man pages by the following commands,
browseVignettes("iGC")
help(iGC)
If you use iGC package, please consider citing our publication.
Yi-Pin Lai, Liang-Bo Wang, Liang-Chuan Lai, Mong-Hsun Tsai, Tzu-Pin Lu, and Eric Y. Chuang. iGC–an integrated analysis package of Gene expression and Copy number alteration, (pending publication), (2015).