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 <- 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 1.8.1 Index]