tni.area3: Compute regulon activity by calling aREA (analytic Rank-based...

In RTN: RTN: Reconstruction of Transcriptional regulatory Networks and analysis of regulons

Description

Uses aREA 3-tail algorithm to compute regulon activity for TNI-class objects.

Usage

tni.area3(object, minRegulonSize=15, sizeFilterMethod="posORneg", scale=FALSE, tnet="dpi", 
regulatoryElements=NULL, samples=NULL, features=NULL, refsamp=NULL, log=FALSE, verbose=TRUE, 
doSizeFilter=NULL)

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.
sizeFilterMethod	a single character value specifying the use of the 'minRegulonSize' argument, which is applyed to regulon's positive and negative targets. Options: "posANDneg", "posORneg", "posPLUSneg". For "posANDneg", the number of both positive and negative targets should be > 'minRegulonSize'; for "posORneg", the number of either positive or negative targets should be > 'minRegulonSize'; and for "posPLUSneg", the number of all targets should be > 'minRegulonSize'.
scale	A logical value specifying if expression values should be centered and scaled across samples (when verbose=TRUE) or not (when verbose=FALSE).
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.
regulatoryElements	an optional vector with transcription factor identifiers.
samples	an optional string vector containing the sample names for which will be computed regulon activity.
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.
verbose	a single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE).
doSizeFilter	a logical value. If TRUE, negative and positive targets are independently verified by the 'minRegulonSize' argument.

Value

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

References

Alvarez et al. Functional characterization of somatic mutations in cancer using network-based inference of protein activity. Nature Genetics, 48(8):838-847, 2016.

See Also

TNI-class aREA

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 aREA algorithm
rtni <- tni.area3(rtni)

#get results
regulonActivity <- tni.get(rtni, what = "regulonActivity")



## End(Not run)

RTN documentation built on Nov. 12, 2020, 2:02 a.m.