Quantile Normalization {oligo}R Documentation

Quantile Normalization Functions

Description

Functions to perform quantile normalization

Usage

normalize.quantiles(x, copy = TRUE)
normalize.FeatureSet.quantiles(obatch, type=c("separate","pmonly","mmonly","together"))

Arguments

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.

Details

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.

Value

A normalized FeatureSet.

References

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 Unpublished manuscript http://bmbolstad.com/stuff/qnorm.pdf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


[Package oligo version 0.99.15 Index]