affyPara (version 1.30.0)

readAffybatchPara: Parallelized Read-AffyBatch function

Description

Parallelization of the read.affybatch function. This parallel implementation is especially useful for multicore machines.

Usage

read.affybatchPara(object,
		phenoData = new("AnnotatedDataFrame"),
		description = NULL, notes = "",	
		cluster, verbose=getOption("verbose"), cdfname)

Arguments

object

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

phenoData

An AnnotatedDataFrame object.

description

a 'MIAME' object.

notes

notes.

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")

cdfname

cdfname to pass to the AffyBatch call

Value

An AffyBatch object.

Details

Parallelized creation of an AffyBatch object. Especially useful on multi-core machines to accelerate the creation of the AffyBatch object.

For the serial function and more details see the function read.affybatch.

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.

Examples

## Not run: 
# library(affyPara)
# if (require(affydata)) {
# 	celpath <- system.file("celfiles", package="affydata")
#     fns <- list.celfiles(path=celpath,full.names=TRUE)
# 
# 	makeCluster(3)
# 	
# 	##read a text celfile
#    	abatch <- read.affybatchPara(fns[2], verbose=TRUE)
# 	
# 	stopCluster()
# }
# ## End(Not run)