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puma (version 3.14.0)

pumaPCA: PUMA Principal Components Analysis

Description

This function carries out principal components analysis (PCA), taking into account not only the expression levels of genes, but also the variability in these expression levels.

The various other pumaPCA... functions are called during the execution of pumaPCA

Usage

pumaPCA( eset , latentDim  =  if(dim(exprs(eset))[2] <= 3="" 1000="" 3)="" dim(exprs(eset))[[2]]-1="" else="" ,="" samplesize="if(dim(exprs(eset))[1]" <="1000)" dim(exprs(eset))[[1]]="" ##="" set="" to="" integer="" or="" false="" for="" all="" initpca="TRUE" initialise="" parameters="" with="" pca="" randomorder="FALSE" update="" in="" random="" order="" optimmethod="BFGS" ?optim="" details="" of="" methods="" stoppingcriterion="deltaW" can="" also="" be="" "deltal"="" tol="1e-3" stop="" when="" delta="" this="" stepchecks="FALSE" check="" likelihood="" after="" each="" update?="" iterationnumbers="TRUE" show="" iteration="" numbers?="" showupdates="FALSE" values="" showtimings="FALSE" timings="" showplot="FALSE" projection="" plot="" maxiters="500" number="" em="" iterations.="" transposedata="FALSE" transpose="" eset="" matrices?="" returnexpectations="FALSE" returndata="FALSE" returnfeedback="FALSE" pumanormalize="TRUE" )<="" div="">

Arguments

eset
An object of class ExpressionSet.
latentDim
An integer specifying the number of latent dimensions (kind of like the number of principal components).
sampleSize
An integer specifying the number of probesets to sample (default is 1000), or FALSE, meaning use all the data.
initPCA
A boolean indicating whether to initialise using standard PCA (the default, and generally quicker and recommended).
randomOrder
A boolean indicating whether the parameters should be updated in a random order (this is generally not recommended, and the default is FALSE).
optimMethod
See ?optim for details of methods.
stoppingCriterion
If set to "deltaW" will stop when W changes by less than tol. If "deltaL" will stop when L (lambda) changes by less than tol.
tol
Tolerance value for stoppingCriterion.
stepChecks
Boolean. Check likelihood after each update?
iterationNumbers
Boolean. Show iteration numbers?
showUpdates
Boolean. Show values after each update?
showTimings
Boolean. Show timings after each update?
showPlot
Boolean. Show projection plot after each update?
maxIters
Integer. Maximum number of EM iterations.
transposeData
Boolean. Transpose eset matrices?
returnExpectations
Boolean. Return expectation values?
returnData
Boolean. Return expectation data?
returnFeedback
Boolean. Return feedback on progress of optimisation?
pumaNormalize
Boolean. Normalise data prior to running algorithm (recommended)?

Value

An object of class pumaPCARes

See Also

Related methods pumaDE, createDesignMatrix and createContrastMatrix

Examples

Run this code
	#	Next 4 lines commented out to save time in package checks, and saved version used
    # if (require(affydata)) {
	#	data(Dilution)
	#	eset_mmgmos <- mmgmos(Dilution)
	# }
	data(eset_mmgmos)

	pumapca_mmgmos <- pumaPCA(eset_mmgmos)
	plot(pumapca_mmgmos)

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