tni.area3 {RTN} | R Documentation

## Compute regulon activity by calling aREA (analytic Rank-based Enrichment Analysis) algorithm

### 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)

[Package RTN version 2.18.0 Index]