normalize.ExpressionSet {affyPLM} | R Documentation

## Normalization applied to ExpressionSets

### Description

Allows the user to apply normalization routines to ExpressionSets.

### Usage

      normalize.ExpressionSet.quantiles(eset, transfn=c("none","log","antilog"))
      normalize.ExpressionSet.loess(eset, transfn=c("none","log","antilog"),...)
      normalize.ExpressionSet.contrasts(eset, span = 2/3,
          choose.subset=TRUE, subset.size=5000, verbose=TRUE, family="symmetric",
          transfn=c("none","log","antilog"))
      normalize.ExpressionSet.qspline(eset, transfn=c("none","log","antilog"),...)
      normalize.ExpressionSet.invariantset(eset,prd.td=c(0.003, 0.007),
          verbose=FALSE, transfn=c("none","log","antilog"),
          baseline.type=c("mean","median","pseudo-mean","pseudo-median"))
      normalize.ExpressionSet.scaling(eset, trim=0.02, baseline=-1,
          transfn=c("none","log","antilog"))

### Arguments

`eset` | An `ExpressionSet`
`span` | parameter to be passed to the function `loess`.
`choose.subset` | use a subset of values to establish the normalization relationship
`subset.size` | number to use for subset
`verbose` | verbosity flag
`family` | parameter to be passed to the function `loess`.
`prd.td` | cutoff parameter (details in the bibliographic reference)
`trim` | How much to trim from the top and bottom before computing the mean when using the scaling normalization
`baseline` | Index of array to use as baseline, negative values (-1,-2,-3,-4) control different baseline selection methods
`transfn` | Transform the ExpressionSet before normalizing. Useful when dealing with expression values that are log-scale
`baseline.type` | A method of selecting the baseline array
`...` | Additional parameters that may be passed to the normalization routine

### Details

This function carries out normalization of expression values. In general you should either normalize at the probe level or at the expression value level, not both.

Typing `normalize.ExpressionSet.methods` should give you a list of methods that you may use. note that you can also use the `normalize` function on ExpressionSets. Use `method` to select the normalization method.

### Value

A normalized `ExpressionSet`.

### Author(s)

Ben Bolstad, bmb@bmbolstad.com

### References

Bolstad, BM (2004) Low Level Analysis of High-density Oligonucleotide Array Data: Background, Normalization and Summarization. PhD Dissertation. University of California, Berkeley.

### Examples

    if (require(affydata)) {
      data(Dilution)
      eset <- rma(Dilution, normalize=FALSE, background=FALSE)
      normalize(eset)
    }

[Package affyPLM version 1.64.0 Index]