R: Compute regulon activity by calling GSEA2 (two-tailed Gene...

tni.gsea2 {RTN}

R Documentation

Compute regulon activity by calling GSEA2 (two-tailed Gene Set Enrichment Analysis) algorithm

Description

Uses GSEA2 algorithm to compute regulon activity for TNI-class objects.

Usage

tni.gsea2(object, minRegulonSize=15, doSizeFilter=FALSE, scale=FALSE, exponent=1, 
tnet="dpi", tfs=NULL, samples=NULL, features=NULL, refsamp=NULL, log=FALSE, 
alternative=c("two.sided", "less", "greater"), targetContribution=FALSE, 
additionalData=FALSE, verbose=TRUE)

Arguments

`object`	a preprocessed object of class 'TNI' `TNI-class`.
`minRegulonSize`	a single integer or numeric value specifying the minimum number of elements in a regulon. Regulons smaller than this number are removed from the analysis.
`doSizeFilter`	a logical value. If TRUE, negative and positive targets are independently verified by the 'minRegulonSize' argument.
`scale`	A logical value specifying if expression values should be centered and scaled across samples (when verbose=TRUE) or not (when verbose=FALSE).
`exponent`	a single integer or numeric value used in weighting phenotypes in GSEA (see 'gseaScores' function at HTSanalyzeR).
`tnet`	can take values of 'refnet', 'dpi' or 'cdt'. It refers to the version of the regulatory network that will be used for GSEA analysis.
`tfs`	an optional vector with transcription factor identifiers.
`samples`	an optional string vector containing the sample names for which will be computed the GSEA2.
`features`	a string vector containing features for feature selection.
`refsamp`	an optional string vector containing the names of the reference samples for differential expression calculations. If not provided, then the average of all samples will be used as reference.
`log`	a logical value. If TRUE, differential expression calculations will be computed in log space.
`alternative`	a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".
`targetContribution`	This argument is used for internal calls. A single logical value specifying to return the contribution of each target in enrichment scores (when verbose=TRUE) or not (when verbose=FALSE).
`additionalData`	This argument is used for internal calls. A single logical value specifying to return the additional data objects (when verbose=TRUE) or not (when verbose=FALSE).
`verbose`	a single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE).

Value

a list with enrichment scores for all samples in the TNI.

Author(s)

Mauro Castro

Examples


data(tniData)

## Not run: 

rtni <- tni.constructor(expData=tniData$expData, 
        regulatoryElements=c("PTTG1","E2F2","FOXM1","E2F3","RUNX2"), 
        rowAnnotation=tniData$rowAnnotation)
rtni <- tni.permutation(rtni)
rtni <- tni.bootstrap(rtni)
rtni <- tni.dpi.filter(rtni)

#run GSEA2 analysis pipeline
EScores <- tni.gsea2(rtni)

#parallel version with SNOW package!
library(snow)
options(cluster=snow::makeCluster(3, "SOCK"))
EScores <- tni.gsea2(rtni)
stopCluster(getOption("cluster"))


## End(Not run)

[Package RTN version 2.10.1 Index]