Quantile Normalization {oligo} | R Documentation |
Functions to perform quantile normalization
normalize.quantiles(x, copy = TRUE) normalize.FeatureSet.quantiles(obatch, type=c("separate","pmonly","mmonly","together"))
x |
A matrix of intensities where each column corresponds to a chip and each row is a probe. |
copy |
Make a copy of matrix before normalizing. Usually safer to work with a copy. |
obatch |
An FeatureSet object. |
type |
A string specifying how the normalization should be applied. |
This method is based upon the concept of a quantile-quantile plot extended to n dimensions. No special allowances are made for outliers. If you make use of quantile normalization either through 'rma' or 'expresso' please cite Bolstad et al, Bioinformatics (2003).
The type arguement should be one of "separate", "pmonly", "mmonly", "together" which indicates whether to normalize only one probe type (PM,MM) or both together or separately.
A normalized FeatureSet
.
Bolstad, B (2001) Probe Level Quantile Normalization of High Density Oligonucleotide Array Data. Unpublished manuscript http://bmbolstad.com/stuff/qnorm.pdf
Bolstad, B. M., Irizarry R. A., Astrand, M, and Speed, T. P. (2003) A Comparison of Normalization Methods for High Density Oligonucleotide Array Data Based on Bias and Variance. Bioinformatics 19(2) ,pp 185-193. http://bmbolstad.com/misc/normalize/normalize.html