LimmaBackgroundCorrection: The LimmaBackgroundCorrection class

Description

Package: aroma.affymetrix Class LimmaBackgroundCorrection Object ~~| ~~+--ParametersInterface ~~~~~~~| ~~~~~~~+--AromaTransform ~~~~~~~~~~~~| ~~~~~~~~~~~~+--Transform ~~~~~~~~~~~~~~~~~| ~~~~~~~~~~~~~~~~~+--ProbeLevelTransform ~~~~~~~~~~~~~~~~~~~~~~| ~~~~~~~~~~~~~~~~~~~~~~+--BackgroundCorrection ~~~~~~~~~~~~~~~~~~~~~~~~~~~| ~~~~~~~~~~~~~~~~~~~~~~~~~~~+--LimmaBackgroundCorrection Directly known subclasses: NormExpBackgroundCorrection public static class LimmaBackgroundCorrection extends BackgroundCorrection This class represents the various "background" correction methods implemented in the limma package.

Usage

LimmaBackgroundCorrection(..., args=NULL, addJitter=FALSE, jitterSd=0.2)

Arguments

...

Arguments passed to the constructor of BackgroundCorrection.

args

A list of additional arguments passed to the correction algorithm.

addJitter

If TRUE, Zero-mean gaussian noise is added to the signals before being background corrected.

jitterSd

Standard deviation of the jitter noise added.

Fields and Methods

Methods: rll{ process Performs background correction. }

Methods inherited from BackgroundCorrection: getParameters, process

Methods inherited from ProbeLevelTransform: getRootPath

Methods inherited from Transform: getOutputDataSet, getOutputFiles

Methods inherited from AromaTransform: as.character, findFilesTodo, getAsteriskTags, getExpectedOutputFiles, getExpectedOutputFullnames, getFullName, getInputDataSet, getName, getOutputDataSet, getOutputDataSet0, getOutputFiles, getPath, getRootPath, getTags, isDone, process, setTags

Methods inherited from ParametersInterface: getParameterSets, getParameters, getParametersAsString

Methods inherited from Object: $, $<-, [[, [[<-, as.character, attach, attachLocally, clearCache, clearLookupCache, clone, detach, equals, extend, finalize, gc, getEnvironment, getFieldModifier, getFieldModifiers, getFields, getInstantiationTime, getStaticInstance, hasField, hashCode, ll, load, objectSize, print, save, asThis

Jitter noise

The fitting algorithm of the normal+exponentital background correction model may not converge if there too many small and discrete signals. To overcome this problem, a small amount of noise may be added to the signals before fitting the model. This is an ad hoc solution that seems to work. However, adding Gaussian noise may generate non-positive signals.

Details