plotRandomDensity: Draw density plot of 'p_pure' values for random gene sets
In schmolze/saps-devel: Significance Analysis of Prognostic Signatures

Description Usage Arguments Value See Also Examples

This function retrieves the p_pure values for the random gene sets generated during the computation of p_random for a given gene set. These are drawn as a density plot, with the value of p_pure for the gene set indicated. The value of p_random for the gene set is displayed as well.

1	plotRandomDensity(geneset, ...)

`geneset`	A geneset as returned by `saps`.
`...`	Additional arguments to be passed to `plot`

The function is used for side-effects (drawing a plot). No value is returned.

saps calculatePRandom

# 25 patients, none lost to followup
followup <- rep(1, 25)

# first 5 patients have good survival (in days)
time <- c(25, 27, 24, 21, 26, sample(1:3, 20, TRUE))*365

# create data for 100 genes, 25 patients
dat <- matrix(rnorm(25*100), nrow=25, ncol=100)
colnames(dat) <- as.character(1:100)

# create two random genesets of 5 genes each
set1 <- sample(colnames(dat), 5)
set2 <- sample(colnames(dat), 5)

genesets <- rbind(set1, set2)

# run saps
results <- saps(genesets, dat, time, followup, random.samples=100)

set <- results$genesets[["set1"]]

# should not be significant
plotRandomDensity(set)

# increase expression levels for set1 for first 5 patients
dat[1:5, set1] <- dat[1:5, set1]+10

# run saps again
results <- saps(genesets, dat, time, followup, random.samples=100)

set <- results$genesets[["set1"]]

# now it should be significant
plotRandomDensity(set)