normalizeAffyBatchInvariantsetPara {affyPara} | R Documentation |
Parallelized normalization of arrays using an invariant set.
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"))
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") |
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.
An AffyBatch of normalized objects.
Markus Schmidberger schmidb@ibe.med.uni-muenchen.de, Ulrich Mansmann mansmann@ibe.med.uni-muenchen.de
## Not run: library(affyPara) if (require(affydata)) { data(Dilution) makeCluster(3) AffyBatch <- normalizeAffyBatchInvariantsetPara(Dilution, verbose=TRUE) stopCluster() } ## End(Not run)