preprocess {affyPLM} | R Documentation

## Background correct and Normalize

### Description

This function pre-processes an `AffyBatch`.

### Usage

    preprocess(object,subset=NULL, normalize=TRUE,background=TRUE,background.method="RMA.2",normalize.method="quantile",background.param = list(),normalize.param=list(),verbosity.level=0)

### Arguments

`object` | an `AffyBatch`
`subset` | a vector with the names of probesets to be used. If NULL then all probesets are used.
`normalize` | logical value. If `TRUE` normalize data using quantile normalization
`background` | logical value. If `TRUE` background correct using RMA background correction
`background.method` | name of background method to use.
`normalize.method` | name of normalization method to use.
`background.param` | list of parameters for background correction methods
`normalize.param` | list of parameters for normalization methods
`verbosity.level` | An integer specifying how much to print out. Higher values indicate more verbose. A value of 0 will print nothing

### Details

This function carries out background correction and normalization pre-processing steps. It does not summarize to produce gene expression measures. All the same pre-processing methods supplied by `threestep` are supported by this function.

### Value

An `AffyBatch`

### 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.

### See Also

`expresso`, `rma`

### Examples

    data(affybatch.example)

    # should be equivalent to the bg and norm of rma()
    abatch.preprocessed <- preprocess(affybatch.example)

[Package affyPLM version 1.12.0 Index]