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.

1 | ```
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

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)
sigmaSq(res)
``` |

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