justmmgMOS: Compute mmgmos Directly from CEL Files

In puma: Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)

Description

This function converts CEL files into an exprReslt using mmgmos.

Usage

justmmgMOS(..., filenames=character(0),
          widget=getOption("BioC")$affy$use.widgets,
          compress=getOption("BioC")$affy$compress.cel,
          celfile.path=getwd(),
          sampleNames=NULL,
          phenoData=NULL,
          description=NULL,
          notes="",
          background=TRUE, gsnorm=c("median", "none", "mean", "meanlog"), savepar=FALSE, eps=1.0e-6)

just.mmgmos(..., filenames=character(0),
           phenoData=new("AnnotatedDataFrame"),
           description=NULL,
           notes="",
           compress=getOption("BioC")$affy$compress.cel,
           background=TRUE, gsnorm=c("median", "none", "mean", "meanlog"), savepar=FALSE, eps=1.0e-6)

Arguments

...	file names separated by comma.
filenames	file names in a character vector.
widget	a logical specifying if widgets should be used.
compress	are the CEL files compressed?
celfile.path	a character denoting the path where cel files locate.
sampleNames	a character vector of sample names to be used in the FeatureSet.
phenoData	an AnnotatedDataFrame object.
description	a MIAME object
notes	notes
background	Logical value. If TRUE, then perform background correction before applying mmgmos.
gsnorm	character. specifying the algorithm of global scaling normalisation.
savepar	Logical value. If TRUE, the the estimated parameters of the model are saved in file par\_mmgmos.txt and phi\_mmgmos.txt.
eps	Optimisation termination criteria.

Details

This method should require much less RAM than the conventional method of first creating an FeatureSet and then running mmgmos.

Note that this expression measure is given to you in log base 2 scale. This differs from most of the other expression measure methods.

The algorithms of global scaling normalisation can be one of "median", "none", "mean", "meanlog". "mean" and "meanlog" are mean-centered normalisation on raw scale and log scale respectively, and "median" is median-centered normalisation. "none" will result in no global scaling normalisation being applied.

Value

An exprReslt.

See Also

Related class exprReslt-class and related method mmgmos

puma documentation built on Nov. 8, 2020, 11:08 p.m.