LimmaBackgroundCorrection: The LimmaBackgroundCorrection class
Usage
LimmaBackgroundCorrection(..., args=NULL, addJitter=FALSE, jitterSd=0.2)
Arguments
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:
process
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, saveJitter 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
By default, only PM signals are background corrected and MMs are
left unchanged.