justmgMOS {puma} | R Documentation

## Compute mgmos Directly from CEL Files

### Description

This function converts CEL files into an `exprReslt` using mgmos.

### Usage

    justmgMOS(..., 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.mgmos(..., 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 mgmos.
`gsnorm` | character. specifying the algorithm of global scaling normalisation.
`savepar` | Logical value. If `TRUE`, then the estimated parameters of the model are saved in file par_mgmos.txt and phi_mgmos.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 `mgmos`.

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 `mgmos`

[Package puma version 1.8.1 Index]