justmmgMOS {puma}R Documentation

Compute mmgmos Directly from CEL Files

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 ReadAffy should look for cel files.
sampleNames a character vector of sample names to be used in the AffyBatch.
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 AffyBatch 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


[Package puma version 1.8.1 Index]