tests/normalizeAverage.matrix.R

In aroma.light: Light-Weight Methods for Normalization and Visualization of Microarray Data using Only Basic R Data Types

library("aroma.light")

# Simulate three samples with on average 20% missing values
N <- 10000
X <- cbind(rnorm(N, mean=3, sd=1),
           rnorm(N, mean=4, sd=2),
           rgamma(N, shape=2, rate=1))
X[sample(3*N, size=0.20*3*N)] <- NA_real_

# Normalize quantiles
Xn <- normalizeAverage(X, na.rm=TRUE, targetAvg=median(X, na.rm=TRUE))

# Plot the data
layout(matrix(1:2, ncol=1))
xlim <- range(X, Xn, na.rm=TRUE)
plotDensity(X, lwd=2, xlim=xlim, main="The three original distributions")
plotDensity(Xn, lwd=2, xlim=xlim, main="The three normalized distributions")