| calculateFC {puma} | R Documentation |
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.
calculateFC(
eset
, design.matrix = createDesignMatrix(eset)
, contrast.matrix = createContrastMatrix(eset)
)
eset |
An object of class ExpressionSet |
design.matrix |
A design matrix |
contrast.matrix |
A contrast matrix |
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.
An object of class DEResult.
Richard D. Pearson
Related methods pumaDE, calculateLimma, calculateTtest, createDesignMatrix and createContrastMatrix and class DEResult
data(affybatch.example)
varLabels(affybatch.example) <- c("level")
pData(affybatch.example) <- data.frame("level"=c("twenty","twenty","ten")
, "batch"=c("A","B","A"), row.names=rownames(pData(affybatch.example)))
eset_rma <- rma(affybatch.example)
FCRes <- calculateFC(eset_rma)
topGeneIDs(FCRes,numberOfGenes=6)
plotErrorBars(eset_rma, topGenes(FCRes))