calculateFC {puma} | R Documentation

## Calculate differential expression between conditions using FC

### 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))
    #}

[Package puma version 3.29.1 Index]