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,
  checkNA = c("auto", "yes", "no"),
  use = c("everything", "all.obs", "na.rm")
)

## S4 method for signature 'ssgseaParam'
anyNA(x, recursive = FALSE)

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.
checkNA	Character string specifying whether the input expression data should be checked for the presence of missing (NA) values. This must be one of the strings "auto" (default), "yes", or "no". The default value "auto" means that the software will perform that check only when the input expression data is provided as a base matrix, an ExpressionSet or a SummarizedExperiment object, while every other type of input expression data container (e.g., SingleCellExperiment, etc.) will not be checked. If checkNA="yes", then the input expression data will be checked for missing values irrespective of the object class of the data container, and if checkNA="no", then that check will not be performed.
use	Character string specifying a policy for dealing with missing values (NAs) in the input expression data argument exprData. It only applies when either checkNA="yes", or checkNA="auto" (see the checkNA parameter. The argument value must be one of the strings "everything" (default), "all.obs", or "na.rm". The policy of the default value "everything" consists of propagating NAs so that the resulting enrichment scores will be NA, whenever one or more of its contributing values is NA, giving a warning when that happens. When use="all.obs", the presence of NAs in the input expression data will produce an error. Finally, when use="na.rm", NA values in the input expression data will be removed from calculations, giving a warning when that happens, and giving an error if no values are left after removing the NA values.
x	An object of class ssgseaParam.
recursive	Not used with x being an object of class ssgseaParam.

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.

checkNA

Character string. One of the strings "auto" (default), "yes", or "no", which refer to whether the input expression data should be checked for the presence of missing (NA) values.

didCheckNA

Logical vector of length 1, indicating whether the input expression data was checked for the presence of missing (NA) values.

anyNA

Logical vector of length 1, indicating whether the input expression data contains missing (NA) values.

use

Character string. One of the strings "everything" (default), "all.obs", or "na.rm", which refer to three different policies to apply in the presence of missing values in the input expression data; see ssgseaParam.

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 July 10, 2024, 2:46 a.m.