affy (version 1.50.0)

computeExprSetPara: Parallel generate a set of expression values

Description

Parallel generation of a set of expression values from the probe pair information. The set of expression is returned as an ExpressionSet object.

Usage

computeExprSetPara(object,
    ids = NULL,
    pmcorrect.method, summary.method,
    summary.param = list(), pmcorrect.param = list(),
    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.

pmcorrect.method

The name of the PM adjustement method.

pmcorrect.param

A list of parameters for pmcorrect.method (if needed/wanted).

summary.method

The method used for the computation of expression values

summary.param

A list of parameters to be passed to the summary.method (if wanted).

ids

List of ids for summarization.

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.

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.

Value

• An object of class ExpressionSet.

Details

Parallelized preprocessing function, which goes from raw probe intensities to expression values in one steps: summarization

For the serial function and more details see the function computeExprSet.

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

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

  makeCluster(3)

  esset <- computeExprSetPara(Dilution,
    pmcorrect.method = "pmonly",
    summary.method = "avgdiff",
    verbose = TRUE)

  stopCluster()
}