dksClassify {dualKS} | R Documentation |
Kolmogorov-Smirnov rank sum scoring will be used to assign
one or more samples to one of two or more classes based on
previously defined gene signatures (see dksTrain
).
dksClassify(eset, classifier, rescale=FALSE, method="kort")
eset |
An ExpressionSet or matrix containing the gene
expression data for the samples to be classified. |
classifier |
An DKSClassifier produced by
dksSelectGenes describing the gene expression
signature for each class. |
rescale |
If TRUE, scores for each class will be mean centered and normalized to remove arbitrary differences in scale and baseline value between signatures for different classes. |
method |
Two methods are supported. The 'kort' method returns the maximum of the running sum. The 'yang' method returns the sum of the maximum and the minimum of the running sum, thereby penalizing classes that are highly enriched in a subset of genes of a given signature, but highly down regulated in another subset of that same signature. |
An object of class DKSPredicted
containing the
class to which each sample in the eset
was assigned as
well as other information. This object has its own summary
and show
functions useful for displaying this information
in a user friendly format.
Eric J. Kort, Yarong Yang
dksTrain
, dksSelectGenes
,
dksClassify
, DKSGeneScores
, DKSPredicted
,
DKSClassifier
data("dks") tr <- dksTrain(eset, 1, "up") cl <- dksSelectGenes(tr, 100) pr <- dksClassify(eset, cl,rescale=FALSE) summary(pr, pData(eset)[,1]) show(pr) plot(pr, actual=pData(eset)[,1])