Nothing

```
##This function compute the nominal p-value associated with a GSEA for a
##collection of gene sets, from the outputs of collectionGsea
permutationPvalueCollectionGsea <- function(permScores, dataScores){
##check 'permScores'
if(!is.matrix(permScores))
stop("The argument permScores should be a matrix")
#check 'dataScores'
if(!is.vector(dataScores) || is.null(names(dataScores)))
stop("The argument dataScores should be a named vector")
if(!is.integer(dataScores) && !is.numeric(dataScores))
stop("The argument dataScores should be a numerical vector")
##check that the dimensions of permScores and dataScores match to
##what is expected
l.dataScores <- length(dataScores)
nPerm <- ncol(permScores)
if(nrow(permScores) != l.dataScores)
warning("The number of rows of the permScores matrix is not ",
"equal to the length of dataScores")
##initialize a pvalues vector
pval <- rep(1, l.dataScores)
##go through each element of dataScores and see how many permScores
##in the corresponding row are higher (in magnitude)
##this is done separately for negative and positive scores
##the scores of zero are simply not treated because they are left
##at the initial pvalue of 1
valid.id <- which(!is.na(dataScores))
pval <- sapply(valid.id, function(i) {
ifelse(
dataScores[i] > 0,
sum(permScores[i, ] > dataScores[i])/nPerm,
sum(permScores[i, ] < dataScores[i])/nPerm
)
})
names(pval)<-names(dataScores)
return(pval)
}
```

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