Nothing

```
##This function takes as input a matrix of p-values for example obtained
##from a GSEA on multiple phenotypes, with a row for each gene set and a
##column for each phenotype and aggregates the p-values by row (i.e. one
##aggregated p-value for each gene set) according to Fisher or Stouffer's
##methods.
aggregatePvals <- function(pvalMatrix, method = "fishers", pAdjustMethod
= "BH", order=TRUE) {
##check 'pvalMatrix'
if(!is(pvalMatrix, "matrix"))
stop("The argument pvalMatrix should be a matrix")
if(is.null(rownames(pvalMatrix)))
stop("The argument pvalMatrix should be a matrix with rownames")
##check 'method'
if(!(method %in% c("stouffers", "fishers") && length(method)==1 ))
stop('The argument method should be one of "stouffers" or
"fishers"')
##check 'pAdjustMethod'
paraCheck("pAdjustMethod", pAdjustMethod)
##do aggregation
aggr.pval <- rep(1, nrow(pvalMatrix))
names(aggr.pval) <- rownames(pvalMatrix)
if (method == "fishers") {
pvalMatrixLogged <- log(pvalMatrix)
aggr.pval <- (-2) * apply(pvalMatrixLogged, 1, sum)
aggr.pval <- pchisq(aggr.pval, df = 2*ncol(pvalMatrix),
lower.tail = FALSE)
}
if (method == "stouffers") {
aggr.pval <- apply(pvalMatrix , 1,
function(x) {
newPval <- pnorm(sum(qnorm(x)) / sqrt(length(x)))
newPval
}
)
}
adj.aggr.pval <- p.adjust(aggr.pval, method = pAdjustMethod)
aggr.pval.table <- cbind(aggr.pval, adj.aggr.pval)
rownames(aggr.pval.table)<-names(aggr.pval)
colnames(aggr.pval.table)<-c("Aggregated.p.value",
"Adjusted.aggregated.p.value")
if(order)
aggr.pval.table <- aggr.pval.table[
order(aggr.pval.table[, "Aggregated.p.value"]), ]
}
```

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