I am not sure that this is the correct place to request new features, but I was wondering if it would be possible to add an alternative parameter to limma::cameraPR to perform one-sided tests? This could be implemented using the following code, which replaces lines 64 to 67 in cameraPR.default (line numbers based on Viewing the function).

# Matches t.test options (this goes near the top of the function)
alternative <- match.arg(alternative, choices = c("two.sided", "less", "greater"))

# ...

Direction <- rep_len("Up", nsets)

# Update p-values and direction of change
switch(alternative,
       two.sided = {
           PValue <- 2 * pmin(Down, Up)
           Direction[Down < Up] <- "Down"
       },
       less = {
           PValue <- Down
           Direction[] <- "Down"
       },
       greater = {
           PValue <- Up
       })

# Originally, PValue = TwoSided, but this is changed to PValue = PValue
if (fixed.cor) 
    tab <- data.frame(NGenes = NGenes, Direction = Direction, 
                      PValue = PValue, stringsAsFactors = FALSE)
else tab <- data.frame(NGenes = NGenes, Correlation = inter.gene.cor, 
                       Direction = Direction, PValue = PValue, 
                       stringsAsFactors = FALSE)

I ask because, while one-sided tests are generally not recommended, if the nonparametric version of CAMERA-PR could perform upper-tail tests, it can be used as an alternative to gene set over-representation analysis (ORA), which uses hypergeometric tests. The input statistics would be cluster membership probabilities from a soft clustering approach like fuzzy C-means. This would allow us to test for localization of gene sets to the cluster centroids; that is, for each set, do the genes have higher cluster membership probabilities than genes not in the set?

Since each cluster would need to be analyzed separately, a for loop or lapply would be needed, and then the results would need to be stacked and p-values adjusted across clusters, since no cluster can be considered independent of the others.

The cameraPR ouput already allows you to extract one-sided tests. For example:

> library(limma)
> example(cameraPR)
> out <- cameraPR(fit$t[,2], list(set1=index1,set2=index2))
> UpperPValue <- LowerPValue <- out$PValue/2
> Up <- out$Direction=="Up"
> UpperPValue[!Up] <- 1-UpperPValue[!Up]
> LowerPValue[Up] <- 1-LowerPValue[Up]

Now you have one-sided p-values.