Description Usage Arguments Value Author(s) See Also Examples
View source: R/NormalizeARRm.R
This function perform Adaptive Robust Regression method (ARRm) normalization on Beta values. The method corrects for background intensity, dye bias and spatial onchip position. By default, chip mean correction is also performed.
1 2  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
JeanPhilippe 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
1 2 3 4 5 6 7  data(greenControlMatrix)
data(redControlMatrix)
data(sampleNames)
data(betaMatrix)
backgroundInfo=getBackground(greenControlMatrix, redControlMatrix)
designInfo=getDesignInfo(sampleNames)
normMatrix=normalizeARRm(betaMatrix, designInfo, backgroundInfo, outliers.perc = 0.02)

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.