aroma.affymetrix (version 2.2.0)

QuantileNormalization: The QuantileNormalization class

Description

Package: aroma.affymetrix Class QuantileNormalization Object ~~| ~~+--AromaTransform ~~~~~~~| ~~~~~~~+--Transform ~~~~~~~~~~~~| ~~~~~~~~~~~~+--ProbeLevelTransform ~~~~~~~~~~~~~~~~~| ~~~~~~~~~~~~~~~~~+--QuantileNormalization Directly known subclasses: DChipQuantileNormalization public static class QuantileNormalization extends ProbeLevelTransform This class represents a normalization function that transforms the probe-level signals towards the same empirical distribution.

Usage

QuantileNormalization(..., subsetToUpdate=NULL, typesToUpdate=NULL, targetDistribution=NULL, subsetToAvg=subsetToUpdate, typesToAvg=typesToUpdate)

Arguments

...

Arguments passed to the constructor of ProbeLevelTransform.

subsetToUpdate

The probes to be updated. If NULL, all probes are updated.

typesToUpdate

Types of probes to be updated.

targetDistribution

A numeric vector. The empirical distribution to which all arrays should be normalized to.

subsetToAvg

The probes to calculate average empirical distribution over. If a single numeric in (0,1), then this fraction of all probes will be used. If NUL

typesToAvg

Types of probes to be used when calculating the average empirical distribution. If "pm" and "mm" only perfect-match and mismatch probes are used, respectively. If "pmmm" both types are used.

Fields and Methods

Methods: rll{ clearCache - process Normalizes the data set. } Methods inherited from Transform: getOutputDataSet, getOutputDataSetOLD20090509, getOutputFiles Methods inherited from AromaTransform: getExpectedOutputFiles, getExpectedOutputFullnames, getFullName, getInputDataSet, getName, getOutputDataSet, getOutputDataSet0, getOutputFiles, getPath, getTags, isDone, process, setTags Methods inherited from Object: asThis, getChecksum, $, $<-, [[, [[<-, as.character, attach, attachLocally, clearCache, clearLookupCache, clone, detach, equals, extend, finalize, gc, getEnvironment, getFieldModifier, getFieldModifiers, getFields, getInstantiationTime, getStaticInstance, hasField, hashCode, ll, load, objectSize, print, registerFinalizer, save

Examples

for (zzz in 0) {

# Setup verbose output
verbose <- Arguments$getVerbose(-2)
timestampOn(verbose)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Define an example dataset
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Find any dataset
path <- NULL
if (is.null(path))
  break

ds <- AffymetrixCelSet$fromFiles(path)
print(ds)

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Normalization
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
norm <- QuantileNormalization(ds, subsetToAvg=1/3)
dsQN <- process(norm, verbose=verbose)
print(dsQN)

} # for (zzz in 0)
rm(zzz)