normalize.quantiles.in.blocks {affyPLM} | R Documentation

## Quantile Normalization carried out separately within blocks of rows

### Description

Using a normalization based upon quantiles this function normalizes the columns of a matrix such that different subsets of rows get normalized together.

### Usage

      normalize.quantiles.in.blocks(x,blocks,copy=TRUE)

### 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
`blocks` | A vector giving block membership for each each row

### 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).

### Value

From `normalize.quantiles.use.target` a normalized `matrix`.

### Author(s)

Ben Bolstad, bmb@bmbolstad.com

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 Unpublished manuscript http://bmbolstad.com/stuff/qnorm.pdf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

### See Also

`normalize`

### Examples

       ### setup the data
       blocks <- c(rep(1,5),rep(2,5),rep(3,5))
       par(mfrow=c(3,2))
       x <- matrix(c(rexp(5,0.05),rnorm(5),rnorm(5,10)))
       boxplot(x ~ blocks)
       y <- matrix(c(-rexp(5,0.05),rnorm(5,10),rnorm(5)))
       boxplot(y ~ blocks)
       pre.norm <- cbind(x,y)

       ### the in.blocks version
       post.norm <- normalize.quantiles.in.blocks(pre.norm,blocks)
       boxplot(post.norm[,1] ~ blocks)
       boxplot(post.norm[,2] ~ blocks)

       ### the usual version
       post.norm  <- normalize.quantiles(pre.norm)
       boxplot(post.norm[,1] ~ blocks)
       boxplot(post.norm[,2] ~ blocks)

[Package affyPLM version 1.10.0 Index]