mmgmos {puma} | R Documentation

## Multi-chip modified gamma Model for Oligonucleotide Signal

### Description

This function converts an object of class `FeatureSet` into an object of class `exprReslt` using the Multi-chip modified gamma Model for Oligonucleotide Signal (multi-mgMOS). This function obtains confidence of measures, standard deviation and 5, 25, 50, 75 and 95 percentiles, as well as the estimated expression levels.

### Usage

    mmgmos(
    	object
    ,	background=FALSE
    ,	replaceZeroIntensities=TRUE
    ,	gsnorm=c("median", "none", "mean", "meanlog")
    ,	savepar=FALSE
    ,	eps=1.0e-6
    ,	addConstant = 0
    )

### Arguments

`object` | an object of `FeatureSet`
`background` | Logical value. If `TRUE`, perform background correction before applying mmgmos.
`replaceZeroIntensities` | Logical value. If `TRUE`, replace 0 intensities with 1 before applying mmgmos.
`gsnorm` | character. specifying the algorithm of global scaling normalisation.
`savepar` | Logical value. If `TRUE` the estimated parameters of the model are saved in file par\_mmgmos.txt and phi\_mmgmos.txt.
`eps` | Optimisation termination criteria.
`addConstant` | numeric. This is an experimental feature and should not generally be changed from the default value.

### Details

The obtained expression measures are in log base 2 scale.

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.

There are 2*n+2 columns in file par\_mmgmos.txt, n is the number of chips. The first n columns are 'alpha' values for n chips, the next n columns are 'a' values for n chips, column 2*n+1 is 'c' values and the final column is values for 'd'. The file phi\_mmgmos.txt keeps the final optimal value of 'phi'.

### Value

An object of class `exprReslt`.

### Author(s)

Xuejun Liu, Magnus Rattray, Marta Milo, Neil D. Lawrence

### References

Liu,X., Milo,M., Lawrence,N.D. and Rattray,M. (2005) A tractable probabilistic model for Affymetrix probe-level analysis across multiple chips, Bioinformatics 21: 3637-3644.

Milo,M., Niranjan,M., Holley,M.C., Rattray,M. and Lawrence,N.D. (2004) A probabilistic approach for summarising oligonucleotide gene expression data, technical report available upon request.

Milo,M., Fazeli,A., Niranjan,M. and Lawrence,N.D. (2003) A probabilistic model for the extractioin of expression levels from oligonucleotide arrays, Biochemical Society Transactions, 31: 1510-1512.

Peter Spellucci. DONLP2 code and accompanying documentation. Electronically available via http://plato.la.asu.edu/donlp2.html

### See Also

Related class `exprReslt-class` and related method `mgmos`

### Examples

    ## Code commented out to speed up checks
    ## load example data from package affydata
    # if (require(pumadata)&&require(puma)){
    #  data(oligo.estrogen)
    ## use method mmgMOS to calculate the expression levels and related confidence
    ## of the measures for the example data
     # eset<-mmgmos(oligo.estrogen,gsnorm="none")
    #}

[Package puma version 3.26.0 Index]