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# simulate data for package testing and demonstration purposes
# nCols: number of samples
# nRows: number of features (genes)
# nEffectRows: number of differentially expressed features
# nNoEffectCols: number of samples for which the profile
# of a differentially expressed feature will be
# set similar to the other class
simulateData <- function(nCols = 40, nRows = 1000, nEffectRows = 5, nNoEffectCols = 5,
betweenClassDifference = 1, withinClassSd = 0.5){
## response
if (nCols %% 2 == 1) stop("'nCols' should be even")
if (nNoEffectCols < 0) stop("'nNoEffectCols' should be positive (or zero)")
# TODO: only works when even number of nCols !! TV (cf. infra as well)
yData <- as.factor(rep(c("A", "B"), each = nCols / 2))
## no effect
xData <- matrix(rnorm(nRows * nCols, mean = 8.73), ncol = nCols)
colnames(xData) <- paste("Sample", 1:nCols, sep = "")
rownames(xData) <- paste("Gene", 1:nRows, sep = ".") # change TV to prevent
# possible bug in new MLInterfaces version
## add effect to a certain number of rows
xDataEffect <- matrix(0, nrow = nEffectRows, ncol = nCols)
if (nNoEffectCols == 0){
if (nEffectRows > 0) {
## create signal
for (i in seq(nEffectRows)){
xDataEffect[i, ] <- rnorm(nCols, mean = 0, sd = withinClassSd) +
betweenClassDifference * as.numeric(yData)
}
xData[seq(nEffectRows), ] <- xDataEffect
}
} else {
## create misbehaving samples
yDataAnti <- factor(levels(yData)[(as.numeric(yData) %% 2) + 1], levels = levels(yData))
yDataNoEffectCols <- yData
yDataNoEffectCols[1:nNoEffectCols] <- yDataAnti[1:nNoEffectCols]
if (nEffectRows > 0) {
## create signal
for (i in seq(nEffectRows)){
xDataEffect[i, ] <- rnorm(nCols, mean = 0, sd = withinClassSd) +
betweenClassDifference * as.numeric(yDataNoEffectCols)
}
xData[seq(nEffectRows), ] <- xDataEffect
}
}
### turn data into an ExpressionSet object
info <- data.frame(yData, row.names = colnames(xData))
colnames(info) <- "type"
labels <- data.frame(type = "type")
pd <- new("AnnotatedDataFrame", data = info, varMetadata = labels)
# new("ExpressionSet", exprs = as.matrix(xData), phenoData = pd)
eset.all <- new("ExpressionSet", exprs = as.matrix(xData), phenoData = pd)
# "ExpressionSet") # will generate a lot of warnings
}
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