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affy (version 1.50.0)

normalizeAffyBatchLoessPara: Parallelized loess normalization

Description

Parallelized loess normalization of arrays.

Usage

normalizeAffyBatchLoessPara(object,
	phenoData = new("AnnotatedDataFrame"), cdfname = NULL,
	type=c("separate","pmonly","mmonly","together"), 
	subset = NULL,
	epsilon = 10^-2, maxit = 1, log.it = TRUE, 
	span = 2/3, family.loess ="symmetric",
	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.
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.
type
A string specifying how the normalization should be applied.
subset
a subset of the data to fit a loess to.
epsilon
a tolerance value (supposed to be a small value - used as a stopping criterium).
maxit
maximum number of iterations.
log.it
logical. If TRUE it takes the log2 of mat
span
parameter to be passed the function loess
family.loess
parameter to be passed the function loess. "gaussian" or "symmetric" are acceptable values for this parameter.
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")

Value

Details

Parallelized loess normalization of arrays. For the serial function and more details see the function normalize.AffyBatch.loess. 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. In the loess normalization the arrays will compared by pairs. Therefore at every node minimum two arrays have to be!

Examples

Run this code
library(affyPara)
if (require(affydata)) {
  data(Dilution)

  makeCluster(3)

  AffyBatch <- normalizeAffyBatchLoessPara(Dilution, verbose=TRUE)

  stopCluster()
}

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