GScluster is a standalone Shiny/R package for network-weighted gene-set clustering and network visualization.

Installation

Open R program and type following commands in R console.

install.packages('devtools')
library(devtools)
install_github('unistbig/GScluster')
library(GScluster)

Example Run

To run demo file, please type following R code.

GScluster()

To run user's own data, please modify following example R codes.

1. Read gene-set analysis result table.
   

GSAresult=read.delim('https://github.com/unistbig/GScluster/raw/master/sample_geneset.txt', stringsAsFactors=FALSE)

2. Read gene score table.
   

GeneScores=read.delim('https://github.com/unistbig/GScluster/raw/master/sample_genescore.txt', header=F)

3. Run GScluster
   

GScluster(GSAresult = GSAresult, GeneScores = GeneScores, Species = 'H', alpha = 1, GsQCutoff = 0.25, GQCutoff = 0.05)

User's Manual

User's manual is available here.

Example data download

• Type 2 Diabetes Mellitus Data (DIAGRAM)
  Gene-set analysis result file (q-value cutoff: 0.25)
  Genescore file (q-value cutoff: 0.01)
  

• Colon Cancer Data
  Gene-set ananlysis result file (q-value cutoff: 0.01)
  Genescore file (q-value cutoff: 0.01)
  

• Acute Myeloid Leukemia (AML) Data
  Gene-set ananlysis result file (q-value cutoff: 0.01)
  Genescore file (q-value cutoff: 0.01)
  

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Running time of GScluster is shown below for different numbers of input gene-sets.

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Contact: Dougu Nam (dougnam@unist.ac.kr)
Any feedback or comments are greatly appreciated!!