Parallelized Invariante Set normalization

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Description

Parallelized normalization of arrays using an invariant set.

Usage

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normalizeAffyBatchInvariantsetPara(object,
    prd.td = c(0.003, 0.007), baseline.type = c("mean", "median", "pseudo-mean", "pseudo-median"),
    type = c("separate", "pmonly", "mmonly", "together"),
    phenoData = new("AnnotatedDataFrame"), cdfname = NULL,
    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.

prd.td

A cutoff parameter for normalization.

baseline.type

Specify how to determine the baseline array (mean, median).

type

A string specifying how the normalization should be applied.

phenoData

A AnnotatedDataFrame object.

cdfname

Used to specify the name of an alternative cdf package. If set to NULL, the usual cdf package based on Affymetrix' mappings will be used.

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. default: getOption("verbose")

Details

Parallelized normalization of arrays using an invariant set. The set of invariant intensities between data and ref is found through an iterative process (based on the respective ranks the intensities). This set of intensities is used to generate a normalization curve by smoothing.

For the serial function and more details see the function normalize.invariantset.

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 of normalized objects.

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)

  AffyBatch <- normalizeAffyBatchInvariantsetPara(Dilution, verbose=TRUE)

  stopCluster()
}

## End(Not run)