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
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)) }