calculateLimma {puma} | R Documentation |
Runs a default analysis using the limma package. Automatically creates design and contrast matrices if not specified. This function is useful for comparing limma results with those of pumaDE
.
calculateLimma( eset , design.matrix = createDesignMatrix(eset) , contrast.matrix = createContrastMatrix(eset) , direction="either" )
eset |
An object of class ExpressionSet |
design.matrix |
A design matrix |
contrast.matrix |
A contrast matrix |
direction |
A string ("either", "up" or "down") |
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.
A list with two elements. The first element (p
) is a matrix of p-values. Each column represent one contrast. Within each column the p-values are ordered. The second element (genes
) is a matrix of row numbers, which can be used to map p-values back to probe sets.
Richard D. Pearson
Related methods pumaDE
, createDesignMatrix
and createContrastMatrix
library(puma) data(affybatch.example) 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) limmaRes <- calculateLimma(eset_rma) limmaRes$p[1:6] plotErrorBars(eset_rma, limmaRes$genes[1])