calculateFC: Calculate differential expression between conditions using FC

In puma: Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)

Description

Automatically creates design and contrast matrices if not specified. This function is useful for comparing fold change results with those of other differential expression (DE) methods such as pumaDE.

Usage

calculateFC(
	eset
,	design.matrix = createDesignMatrix(eset)
,	contrast.matrix = createContrastMatrix(eset)
)

Arguments

eset	An object of class ExpressionSet
design.matrix	A design matrix
contrast.matrix	A contrast matrix

Details

The eset argument must be supplied, and must be a valid ExpressionSet object. Design and contrast matrices can be supplied, but if not, default matrices will be used. These should usually be sufficient for most analyses.

Value

An object of class DEResult.

Author(s)

Richard D. Pearson

See Also

Related methods pumaDE, calculateLimma, calculateTtest, createDesignMatrix and createContrastMatrix and class DEResult

Examples

#if (require(affydata)) {
#	data(Dilution)
#	eset_rma <- affy:::rma(Dilution)
#	#	Next line used so eset_rma only has information about the liver factor
#	#	The scanner factor will thus be ignored, and the two arrays of each level
#	#	of the liver factor will be treated as replicates
#	pData(eset_rma) <- pData(eset_rma)[,1, drop=FALSE]
#	FCRes <- calculateFC(eset_rma)
#	topGeneIDs(FCRes,numberOfGenes=6)
#	plotErrorBars(eset_rma, topGenes(FCRes))
#}

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