sigmaSq-methods: ~~ Methods for Function 'sigmaSq' ~~

In npGSEA: Permutation approximation methods for gene set enrichment analysis (non-permutation GSEA)

Description

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.

Usage

sigmaSq(object)

Arguments

object

An object of type npGSEAResultNorm, npGSEAResultBeta, npGSEAResultChiSq, npGSEAResultNormCollection, npGSEAResultBetaCollection, or npGSEAResultChiSqCollection

Methods

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)

Author(s)

Jessica L. Larson

See Also

npGSEAResultNorm-class

Examples

    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)

npGSEA documentation built on Nov. 8, 2020, 6:49 p.m.