ssgseaParam-class: 'ssgseaParam' class

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

ssgseaParam class

Description

S4 class for ssGSEA method parameter objects.

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

Usage

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

ssgseaParam(
  exprData,
  geneSets,
  assay = NA_character_,
  annotation = NULL,
  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

x	An object of class ssgseaParam.
recursive	Not used with x being an object of class ssgseaParam.
exprData	The expression data set. Must be one of the classes supported by GsvaExprData. For a list of these classes, see its help page using help(GsvaExprData).
geneSets	The gene sets. Must be one of the classes supported by GsvaGeneSets. For a list of these classes, see its help page using help(GsvaGeneSets).
assay	Character vector of length 1. 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	An object of class GeneIdentifierType from package GSEABase describing the gene identifiers used as the row names of the expression data set. See GeneIdentifierType for help on available gene identifier types and how to construct them. This information can be used to map gene identifiers occurring in the gene sets. If the default value NULL is provided, an attempt will be made to extract the gene identifier type from the expression data set provided as exprData (by calling gsvaAnnotation on it). If still not successful, the NullIdentifier() will be used as the gene identifier type, gene identifier mapping will be disabled and gene identifiers used in expression data set and gene sets can only be matched directly.
minSize	Numeric vector of length 1. Minimum size of the resulting gene sets after gene identifier mapping. By default, the minimum size is 1.
maxSize	Numeric vector of length 1. 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 final normalization step is skipped.
checkNA	Character vector of length 1 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 vector of length 1 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 score 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.

Details

In addition to the common parameter slots inherited from ⁠[GsvaMethodParam]⁠, this class has slots for the two method-specific parameters of the ssGSEA method described below as well as four more slots for implementing a missing value policy.

In addition to a number of parameters shared with all methods implemented by package GSVA, ssGSEA takes two method-specific parameters as well as two more parameters for implementing a missing value policy. All of these parameters are described in detail 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 final normalization step is skipped.

checkNA

Character vector of length 1. 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 vector of length 1. 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 Dec. 17, 2024, 4:51 p.m.