# ~~ Methods for Function npGSEAPlot ~~

### 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

1 | ```
npGSEAPlot(object)
``` |

### Arguments

`object` |
An object of type |

### 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

1 2 3 4 5 6 7 | ```
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)
``` |