Description Usage Arguments Value Author(s) References See Also Examples
Table with top gene sets
1 |
mGSZobj |
mGSZ object |
sample.perm.table |
TRUE for table of top gene sets based on sample permutation when both gene and sample permutations were used. |
method |
Method for which table for top gene sets is required (Required only when other methods were used for the gene set analysis) |
no.top.sets |
Number of top gene sets in the table |
A table with top gene sets
Pashupati Mishra, Petri Toronen
Mishra Pashupati, Toronen Petri, Leino Yrjo, Holm Liisa. Gene Set Analysis: Limitations in popular existing methods and proposed improvements (Not yet published) http://ekhidna.biocenter.helsinki.fi/downloads/pashupati/mGSZ.html
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | gene.names <- paste("g",1:1000, sep = "")
# create random gene expression data matrix
set.seed(100)
expr.data <- matrix(rnorm(1000*50),ncol=50)
rownames(expr.data) <- gene.names
b <- matrix(2*rnorm(2500),ncol=25)
ind <- sample(1:100,replace=FALSE)
expr.data[ind,26:50] <- expr.data[ind,26:50] + b
sample.labels <- rep(1:2,c(25,25))
# create random gene sets
gene.sets <- vector("list", 100)
for(i in 1:length(gene.sets)){
gene.sets[[i]] <- sample(gene.names, size = 20)
}
names(gene.sets) <- paste("set", as.character(1:100), sep="")
mGSZ.obj <- mGSZ(expr.data, gene.sets, sample.labels, perm.number = 100)
top.mGSZ.sets <- toTable(mGSZ.obj, no.top.sets = 10)
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