ssgseaParam-class: 'ssgseaParam' class

In rcastelo/GSVA: Gene Set Variation Analysis for Microarray and RNA-Seq Data

ssgseaParam class

Description

Method-specific parameters for the ssGSEA method.

Objects of class ssgseaParam contain the parameters for running the ssGSEA method.

Usage

ssgseaParam(
  exprData,
  geneSets,
  assay = NA_character_,
  annotation = NA_character_,
  minSize = 1,
  maxSize = Inf,
  alpha = 0.25,
  normalize = TRUE
)

Arguments

exprData	The expression data. Must be one of the classes supported by GsvaExprData. Type help(GsvaExprData) to consult the available classes.
geneSets	The gene sets. Must be one of the classes supported by GsvaGeneSets.
assay	The name of the assay to use in case exprData is a multi-assay container, otherwise ignored. By default, the first assay is used.
annotation	The name of a Bioconductor annotation package for the gene identifiers occurring in the row names of the expression data matrix. This can be used to map gene identifiers occurring in the gene sets if those are provided in a GeneSetCollection. By default gene identifiers used in expression data matrix and gene sets are matched directly.
minSize	Minimum size of the resulting gene sets after gene identifier mapping. By default, the minimum size is 1.
maxSize	Maximum size of the resulting gene sets after gene identifier mapping. By default, the maximum size is Inf.
alpha	Numeric vector of length 1. The exponent defining the weight of the tail in the random walk performed by the ssGSEA (Barbie et al., 2009) method. The default value is 0.25 as described in the paper.
normalize	Logical vector of length 1; if TRUE runs the ssGSEA method from Barbie et al. (2009) normalizing the scores by the absolute difference between the minimum and the maximum, as described in their paper. Otherwise this last normalization step is skipped.

Details

In addition to the two common parameter slots inherited from ⁠[GsvaMethodParam]⁠, this class has slots for the two method-specific parameters of the ssGSEA method described below.

In addition to an expression data set and a collection of gene sets, ssGSEA takes two method-specific parameters as described below.

Value

A new ssgseaParam object.

Slots

alpha

Numeric vector of length 1. The exponent defining the weight of the tail in the random walk performed by the ssGSEA (Barbie et al., 2009) method.

normalize

Logical vector of length 1. If TRUE runs the ssGSEA method from Barbie et al. (2009) normalizing the scores by the absolute difference between the minimum and the maximum, as described in their paper. Otherwise this last normalization step is skipped.

References

Barbie, D.A. et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature, 462(5):108-112, 2009. DOI

See Also

GsvaExprData, GsvaGeneSets, GsvaMethodParam, plageParam, zscoreParam, gsvaParam

Examples

library(GSVA)
library(GSVAdata)

data(leukemia)
data(c2BroadSets)

## for simplicity, use only a subset of the sample data
ses <- leukemia_eset[1:1000, ]
gsc <- c2BroadSets[1:100]
sp1 <- ssgseaParam(ses, gsc)
sp1

rcastelo/GSVA documentation built on April 29, 2024, 11:26 a.m.