mmgmos: Multi-chip modified gamma Model for Oligonucleotide Signal

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

View source: R/mmgmos.R

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

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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

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if(FALSE){
## 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")
#}
}

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