normalizeARRm {ARRmNormalization} | R Documentation |
This function perform Adaptive Robust Regression method (ARRm) normalization on Beta values. The method corrects for background intensity, dye bias and spatial on-chip position. By default, chip mean correction is also performed.
normalizeARRm(betaMatrix, designInfo, backgroundInfo, outliers.perc = 0.02, goodProbes = NULL,chipCorrection=TRUE)
betaMatrix |
|
designInfo |
A |
backgroundInfo |
A |
outliers.perc |
Proportion (between 0 and 1) of outliers to be removed from the ARRm regression |
goodProbes |
Ids of the probes to be normalized (Id. of the form "cg00000029") |
chipCorrection |
logical, should normalization correct for chip mean? |
A matrix
containing the normalized Beta values
Jean-Philippe Fortin <jfortin@jhsph.edu>
getBackground
to see how to obtain background information from control probes, and getDesignInfo
to see how to obtain position and chip indices
data(greenControlMatrix) data(redControlMatrix) data(sampleNames) data(betaMatrix) backgroundInfo=getBackground(greenControlMatrix, redControlMatrix) designInfo=getDesignInfo(sampleNames) normMatrix=normalizeARRm(betaMatrix, designInfo, backgroundInfo, outliers.perc = 0.02)