normalizeQuantile.AffymetrixCelSet {aroma.affymetrix}
Normalizes samples to have the same empirical distribution
Description
Normalizes samples to have the same empirical distribution.
Usage
## S3 method for class 'AffymetrixCelSet': normalizeQuantile((this, path=NULL, name="normQuantile", subsetToUpdate=NULL, typesToUpdate=NULL, xTarget=NULL, subsetToAvg=subsetToUpdate, typesToAvg=typesToUpdate, ..., verbose=FALSE))
Arguments
- path
- The path where to save the normalized data files. If
NULL, a default name is used. - name
- The name of the normalized data set, which will also be part of the default path.
- subsetToUpdate
- The probes to be updated. If
NULL, all probes are updated. - typesToUpdate
- Types of probes to be updated.
- xTarget
- A
numericvector. The empirical distribution to which all arrays should be normalized to. - subsetToAvg
- The probes to calculate average empirical distribution over. If a single
numericin (0,1), then this fraction of all probes will be used. IfNULL, all probes are considered. - 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. - ...
- Additional arguments passed to
normalizeQuantile(). - verbose
- See
Verbose.
See Also
normalizeQuantileRank.numeric For more information see AffymetrixCelSet.
Documentation reproduced from package aroma.affymetrix, version 2.9.0. License: LGPL (>= 2.1)
