preprocess: Background correct and Normalize

In affyPLM: Methods for fitting probe-level models

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 [e-mail]

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

if (require(affydata)) {
  data(Dilution)

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

affyPLM documentation built on Nov. 8, 2020, 6:53 p.m.