ViDGER (Visualization of Differential Gene Expression using R), is an R package that can rapidly generate information-rich visualizations for the interpretation of differential gene expression results from three widely-used tools: Cuffdiff, DESeq2, and edgeR.
The stable version of this package is available on Bioconductor . You can install it by:
if (!require("BiocManager")) install.packages("BiocManager")
BiocManager::install("vidger")
If you want the latest version, install it directly from this GitHub repo:
if (!require("devtools")) install.packages("devtools")
devtools::install_github("btmonier/vidger", ref = "devel")
The stable release of vidger has 9 visualization functions:
vsScatterPlot()vsScatterMatrix()vsBoxplot()vsDEGMatrix()vsVolcano()vsVolcanoMatrix()vsMAPlot()vsMAMatrix()vsFourWay()To simulate the usage of the three aformentioned tools, "toy" data sets have been implemented in this package. Each of these data sets represents their respective R class:
df.cuff A cuffdiff output file.df.deseq A DESeq2 object class.df.edger An edgeR object class.To load these data sets, use the following command:
data("<object-type>")
...where "<object-type>" is one of the previously mentioned data sets.
For additional information on these functions, please see the given documentation in the vidger package by adding the ? help operator before any of the given functions in this package or by using the help() function.
For a more in-depth analysis, consider reading the vignette provided with this package:
vignette("vidger")
Last updated: 2019-01-18