Skip to content

Latest commit

 

History

History
63 lines (46 loc) · 2.16 KB

README.md

File metadata and controls

63 lines (46 loc) · 2.16 KB

TcGSA

CRAN_Status_Badge R-CMD-check Downloads

Overview

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>

Installation

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")

Microarrays vs RNA-seq

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