Parallelized Background Correction

Description

Parallelized functions for background correction of probe intensities.

Usage

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bgCorrectPara(object,
	phenoData = new("AnnotatedDataFrame"), method,
	cluster, verbose = getOption("verbose"))

Arguments

object

An object of class AffyBatch OR a character vector with the names of CEL files OR a (partitioned) list of character vectors with CEL file names.

phenoData

An AnnotatedDataFrame object

method

A character that defines what background correction method will be used. Available methods are given by bg.correct.methods. The name of the method to apply must be double-quoted.

cluster

A cluster object obtained from the function makeCluster in the SNOW package. For default .affyParaInternalEnv$cl will be used.

verbose

A logical value. If TRUE it writes out some messages.

Details

bgCorrectPara is the parallelized function for background correction of probe intensities. For serial function an more details see bg.correct.

For using this function a computer cluster using the SNOW package has to be started. Starting the cluster with the command makeCluster generates an cluster object in the affyPara environment (.affyParaInternalEnv) and no cluster object in the global environment. The cluster object in the affyPara environment will be used as default cluster object, therefore no more cluster object handling is required. The makeXXXcluster functions from the package SNOW can be used to create an cluster object in the global environment and to use it for the preprocessing functions.

Value

An AffyBatch for which the intensities have been background adjusted. For some methods (RMA), only PMs are corrected and the MMs remain the same.

Author(s)

Markus Schmidberger schmidb@ibe.med.uni-muenchen.de, Ulrich Mansmann mansmann@ibe.med.uni-muenchen.de

Examples

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## Not run: 
library(affyPara)
if (require(affydata)) {
  data(Dilution)

  makeCluster(3)

  ##bgc will be the bg corrected version of Dilution 
  bgc <- bgCorrectPara(Dilution, method="rma", verbose=TRUE)

  stopCluster()
}

## End(Not run)