
CalGIF(dataset,class.labels)
When users input interesting gene expression data and the vector of binary labels (class labels), the function can calculate the GIF values for all genes in the global gene-gene network constructed based on the relationships of genes extracted from pathway database.
The argument dataset
is gene expression data set stored in a dataframe. The first column of the dataframe are gene symbols and the names of the dataframe are samples names.
## Not run:
#
# ###calculate the global influence factor (GIF) by using the random walk with restart (RWR) algorithm###
# #example 1
# #get example data
# dataset<-getdataset()
# class.labels<-getclass.labels()
#
# #calculate the global influence factor (GIF)
# GIFscore<-CalGIF(dataset,class.labels)
# #print the top ten results to screen
# GIFscore[rev(order(GIFscore))][1:10]
#
# #Each element is the GIF score and whose name correspond to gene symbol in the gene expression data.
# #If the genes in gene expression data are not included in the global gene-gene network, their GIF
# #scores will be zero.
#
# #example 2
# #get example data
# dataset<-read.table(paste(system.file(package="PAGI"),"/localdata/dataset.txt",sep=""),
# header=T,sep="\t","\"")
# class.labels<-as.character(read.table(paste(system.file(package="PAGI"),
# "/localdata/class.labels.txt",sep=""),quote="\"", stringsAsFactors=FALSE)[1,])
#
# #calculate the global influence factor (GIF)
# GIFscore<-CalGIF(dataset,class.labels)
# #print the top ten results to screen
# GIFscore[rev(order(GIFscore))][1:10]
#
# #Each element is the GIF score and whose name correspond to gene symbol in the gene expression data.
# #If the genes in gene expression data are not included in the global gene-gene network, their
# # GIF scores will be zero.
#
# ## End(Not run)
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