The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
TcGSA
TcGSA is a package which performs Time-course Gene
Set Analysis from microarray data, and provide
nice representations of its results.
On top of the CRAN help pdf-file, the following article explains what TcGSA is about:
Hejblum, BP, Skinner, J, & Thiébaut, R (2015). Time-Course Gene Set Analysis for Longitudinal Gene Expression Data. PLOS Computational Biology, 11(6):e1004310. <doi: 10.1371/journal.pcbi.1004310>
TcGSA imports the multtest package which is not
available on CRAN, but is
available on the Bioconductor
repository. Before installing TcGSA, be sure to have this
multtest package installed. If not, you can do so by
running the following:
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("multtest")The easiest way to get TcGSA is to install it from CRAN:
install.packages("TcGSA")or to get the development version from GitHub:
#install.packages("devtools")
devtools::install_github("sistm/TcGSA")TcGSA relies on a Gaussian assumption for the expression
data, which is suitable for normalized microarray data. Due to their
count and heteroskedastic nature, RNA-seq data need to be handled
differently and TcGSA cannot deal with RNA-seq
data. For RNA-seq data, please have a look at the Bioconductor package
dearseq which incorporates similar functionality for
analyzing RNA-seq data.
– Boris Hejblum
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.