PMmmgmos: Multi-chip modified gamma Model for Oligonucleotide Signal...
In puma: Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)

Description Usage Arguments Details Value Author(s) References See Also Examples

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

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

`object`	an object of `FeatureSet`
`background`	Logical value. If `TRUE`, perform background correction before applying PMmmgmos.
`replaceZeroIntensities`	Logical value. If `TRUE`, replace 0 intensities with 1 before applying PMmmgmos.
`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\_pmmmgmos.txt
`eps`	Optimisation termination criteria.
`addConstant`	numeric. This is an experimental feature and should not generally be changed from the default value.

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 n+2 columns in file par\_pmmmgmos.txt, n is the number of chips. The first n columns are 'alpha' values for n chips, column n+1 is 'c' values and the final column is values for 'd'.

An object of class exprReslt.

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

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

Related class exprReslt-class and related method mgmos

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