normalize.quantiles {affy} | R Documentation |

## Quantile Normalization

### Description

Using a normalization based upon quantiles, this function
normalizes a matrix of probe level intensities.

### Usage

normalize.quantiles(x,copy=TRUE)
normalize.AffyBatch.quantiles(abatch, 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 |

`abatch` |
An `AffyBatch` |

`type` |
A string specifying how the normalization should be
applied. See details for more. |

### 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 `AffyBatch`

.

### Author(s)

Ben Bolstad, bolstad@stat.berkeley.edu

### References

Bolstad, B (2001) *Probe Level Quantile Normalization of High Density
Oligonucleotide Array Data*. Unpublished manuscript
http://oz.berkeley.edu/~bolstad/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://www.stat.berkeley.edu/~bolstad/normalize/normalize.html

### See Also

`normalize`

[Package

*affy* version 1.8.1

Index]