preproPara: Parallelized preprocessing

In affyPara: Parallelized preprocessing methods for Affymetrix Oligonucleotide Arrays

Description

Parallelized preprocessing function, which goes from raw probe intensities to expression values in three steps: Background correction, normalization and summarization

Usage

preproPara(object, cluster,
    bgcorrect = TRUE, bgcorrect.method = NULL, bgcorrect.param = list(),
    normalize = TRUE, normalize.method = NULL, normalize.param = list(),
    pmcorrect.method = NULL, pmcorrect.param = list(),
    summary.method = NULL, summary.param = list(),
    ids = NULL,phenoData = new("AnnotatedDataFrame"), cdfname = NULL,
    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.
bgcorrect	A boolean to express whether background correction is wanted or not.
bgcorrect.method	The name of the background adjustment method to use.
bgcorrect.param	A list of parameters for bgcorrect.method (if needed/wanted)
normalize	A boolean to express whether normalization is wanted or not.
normalize.method	The name of the normalization method to use.
normalize.param	A list of parameters to be passed to the normalization method (if wanted).
pmcorrect.method	The name of the PM adjustment 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. default: getOption("verbose")
...	Further arguments that get passed to the affyBatch creation process.

Details

Parallelized preprocessing function, which goes from raw probe intensities to expression values in three steps: Background correction, normalization and summarization

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

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.

Available methods:

bgcorrect.method:

see bgcorrect.methods()

normalize.method:

'quantil', 'constant', 'invariantset','loess'

summary.method:

see generateExprSet.methods() and 'none'.

Value

An object of class ExpressionSet.

Author(s)

Markus Schmidberger [e-mail], Ulrich Mansmann [e-mail]

Examples

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

  makeCluster(3)

  esset <- preproPara(Dilution,
    bgcorrect = TRUE, bgcorrect.method = "rma",
    normalize = TRUE, normalize.method = "quantiles",
    pmcorrect.method = "pmonly",
    summary.method = "avgdiff",
    verbose = TRUE)
    
  stopCluster()
}

## End(Not run)

affyPara documentation built on Nov. 8, 2020, 11:08 p.m.