tni.bootstrap {RTN} | R Documentation

## Inference of consensus transcriptional networks.

### Description

This function takes a TNI object and returns the consensus transcriptional network.

### Usage

    tni.bootstrap(object, nBootstraps=100, consensus=95, parChunks=NULL, verbose=TRUE)

### Arguments

`object` | a processed object of class 'TNI' `TNI-class` evaluated by the method `tni.permutation`.
`nBootstraps` | a single integer or numeric value specifying the number of bootstraps for deriving a consensus between every TF-target association inferred in the mutual information analysis. If running in parallel, nBootstraps should be greater and multiple of parChunks.
`consensus` | a single integer or numeric value specifying the consensus fraction (in percentage) under which a TF-target association is accepted.
`parChunks` | an optional single integer value specifying the number of bootstrap chunks to be used in the parallel analysis.
`verbose` | a single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE)

### Value

a matrix in the slot "results" containing a reference transcriptional network, see 'tn.ref' option in `tni.get`.

### Author(s)

Mauro Castro

### See Also

`TNI-class`

### Examples

    data(tniData)

    ## Not run:

    # preprocessing
    rtni <- tni.constructor(expData=tniData$expData,
            regulatoryElements=c("PTTG1","E2F2","FOXM1","E2F3","RUNX2"),
            rowAnnotation=tniData$rowAnnotation)

    # linear version!
    rtni <- tni.permutation(rtni)
    rtni <- tni.bootstrap(rtni)

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

    ## End(Not run)

[Package RTN version 2.14.1 Index]