test_gsvaRanks <- function() {
message("Running unit tests for GSVA ranks.")
p <- 10 ## number of genes
n <- 30 ## number of samples
nGrp1 <- 15 ## number of samples in group 1
nGrp2 <- n - nGrp1 ## number of samples in group 2
## consider three disjoint gene sets
geneSets <- list(set1=paste("g", 1:3, sep=""),
set2=paste("g", 4:6, sep=""),
set3=paste("g", 7:10, sep=""))
## sample data from a normal distribution with mean 0 and st.dev. 1
## seeding the random number generator for the purpose of this test
set.seed(123)
y <- matrix(rnorm(n*p), nrow=p, ncol=n,
dimnames=list(paste("g", 1:p, sep="") , paste("s", 1:n, sep="")))
## build GSVA parameter object
gsvapar <- gsvaParam(y, geneSets)
## calculate GSVA scores in one step
gsva_es1 <- gsva(gsvapar, verbose=FALSE)
## calculate GSVA scores in two steps
## first calculate GSVA ranks
gsvarankspar <- gsvaRanks(gsvapar, verbose=FALSE)
## second calculate GSVA scores using GSVA ranks
gsva_es2 <- gsvaScores(gsvarankspar, verbose=FALSE)
## both approaches to calculate GSVA scores must give
## the same result with the same input gene sets
checkEqualsNumeric(gsva_es1, gsva_es2)
checkTrue(all.equal(gsva_es1, gsva_es2))
}
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