Make rapid visualizations of RNA-seq data in R
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README.md

ViDGER

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Overview

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.

Installation

The stable version of this package is available on Bioconductor . You can install it by:

source("http://bioconductor.org/biocLite.R")
biocLite("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")

Functions

The stable release of vidger has 9 visualization functions:

  • vsScatterPlot()
  • vsScatterMatrix()
  • vsBoxplot()
  • vsDEGMatrix()
  • vsVolcano()
  • vsVolcanoMatrix()
  • vsMAPlot()
  • vsMAMatrix()
  • vsFourWay()

Loading test data

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.

Getting help

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: 2018-06-08