| sigmaSq-methods {npGSEA} | R Documentation |
sigmaSq ~~This function returns the corresponding variance of the statistic (linear or quadratic) from the npGSEA analysis
for a given GeneSet,
or a list of these variances for a given GeneSetCollection.
This method is applicable for all three approximation methods.
sigmaSq(object)
object |
An object of type |
signature(object = "npGSEAResultNorm")Returns the variance
of the linear statistic for a npGSEAResultNorm object
signature(object = "npGSEAResultBeta")Returns the variance
of the linear statistic for a npGSEAResultBeta object
signature(object = "npGSEAResultChiSq")Returns the variance
of the quadratic statistic for a npGSEAResultChiSq object
signature(object = "npGSEAResultNormCollection")Returns a list
of the variances of the linear statistics for a npGSEAResultNormCollection
objects (1 for each set)
signature(object = "npGSEAResultBetaCollection")Returns a list of
the variances of the linear statistics for a npGSEAResultBetaCollection
objects (1 for each set)
signature(object = "npGSEAResultChiSqCollection")Returns a list of
the variances of the linear statistics for a npGSEAResultChiSqCollection
objects (1 for each set)
Jessica L. Larson
npGSEAResultNorm-class
set.seed(15)
yFactor <- as.factor( c(rep("treated", 5), rep("control", 5)) )
xData <- matrix(data=rnorm(length(letters)*10) ,nrow=length(letters), ncol=10)
rownames(xData) <- letters
geneSetABC15 <- GeneSet(geneIds=letters[1:15], setName="setABC15")
res <- npGSEA(x = xData, y = yFactor, set = geneSetABC15)
sigmaSq(res)