AdditiveCovariatesNormalization: The AdditiveCovariatesNormalization class

Description

Package: aroma.affymetrix Class AdditiveCovariatesNormalization Object ~~| ~~+--AromaTransform ~~~~~~~| ~~~~~~~+--Transform ~~~~~~~~~~~~| ~~~~~~~~~~~~+--ChipEffectTransform ~~~~~~~~~~~~~~~~~| ~~~~~~~~~~~~~~~~~+--AdditiveCovariatesNormalization Directly known subclasses: GcContentNormalization2 public abstract static class AdditiveCovariatesNormalization extends ChipEffectTransform This class represents a normalization method that corrects for GC-content effects on copy-number chip-effect estimates.

Usage

AdditiveCovariatesNormalization(dataSet=NULL, ..., target=NULL, subsetToFit="-XY", shift=0, onMissing=c("median", "ignore"))

Arguments

dataSet

A SnpChipEffectSet.

...

Additional arguments passed to the constructor of ChipEffectTransform.

target

(Optional) A character string or a function specifying what to normalize toward.

subsetToFit

The units from which the normalization curve should be estimated. If NULL, all are considered.

onMissing

Specifies how to normalize units for which the GC contents are unknown.

shift

An optional amount the data points should be shifted (translated).

Fields and Methods

Methods: rll{ clearCache - getCdf - getCovariates - getOutputDataSet00 - 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, $, $<-, [[, [[<-, as.character, attach, attachLocally, clearCache, clone, detach, equals, extend, finalize, gc, getEnvironment, getFields, getInstantiationTime, getStaticInstance, hasField, hashCode, ll, load, objectSize, print, registerFinalizer, save

Details

For SNPs, the normalization function is estimated based on the total chip effects, i.e. the sum of the allele signals. The normalizing is done by rescale the chip effects on the intensity scale such that the mean of the total chip effects are the same across samples for any given GC content. For allele-specific estimates, both alleles are always rescaled by the same amount. Thus, when normalizing allele-specific chip effects, the total chip effects is change, but not the relative allele signal, e.g. the allele B frequency.