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

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

Description

This function plots the reference distribution and the corresponding scaled statistic (Z, Beta, or Chi-sq) from the npGSEA analysis for a given GeneSet. This method is applicable for all three approximation methods.

Usage

    npGSEAPlot(object)

Arguments

object

An object of type npGSEAResultNorm, npGSEAResultBeta, or npGSEAResultChiSq

Methods

signature(object = "npGSEAResultNorm")

Plots the Z-statistic for a npGSEAResultNorm object and the standard normal distribution

signature(object = "npGSEAResultBeta")

Plots the beta statistic for a npGSEAResultBeta object and the corresponding reference beta distribution (with alpha and beta calculated from npGSEA).

signature(object = "npGSEAResultChiSq")

Plots the beta statistic for a npGSEAResultChiSq object and the corresponding reference chi-squared distribution (with degrees of freedom calculated from npGSEA).

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)
    ##npGSEAPlot (res)

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