tna.mra {RTN}R Documentation

Master Regulator Analysis (MRA) over a list of regulons.

Description

This function takes a TNA object and returns the results of the RMA analysis over a list of regulons from a transcriptional network (with multiple hypothesis testing corrections).

Usage

tna.mra(object, pValueCutoff=0.05, pAdjustMethod="BH", minRegulonSize=15, tnet="dpi", verbose=TRUE)

Arguments

object

a preprocessed object of class 'TNA' TNA-class.

pValueCutoff

a single numeric value specifying the cutoff for p-values considered significant.

pAdjustMethod

a single character value specifying the p-value adjustment method to be used (see 'p.adjust' for details).

minRegulonSize

a single integer or numeric value specifying the minimum number of elements in a regulon that must map to elements of the gene universe. Gene sets with fewer than this number are removed from the analysis.

tnet

a single character value specifying which transcriptional network should to used to compute the MRA analysis. Options: "dpi" and "ref".

verbose

a single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE).

Value

a data frame in the slot "results", see 'rma' option in tna.get.

Author(s)

Mauro Castro

See Also

TNA-class

Examples


data(dt4rtn)

# select 5 regulatoryElements for a quick demonstration!
tfs4test <- dt4rtn$tfs[c("PTTG1","E2F2","FOXM1","E2F3","RUNX2")]

## Not run: 

rtni <- tni.constructor(expData=dt4rtn$gexp, regulatoryElements=tfs4test, 
        rowAnnotation=dt4rtn$gexpIDs)
rtni<-tni.permutation(rtni)
rtni<-tni.bootstrap(rtni)
rtni<-tni.dpi.filter(rtni)
rtna<-tni2tna.preprocess(rtni, phenotype=dt4rtn$pheno, hits=dt4rtn$hits, phenoIDs=dt4rtn$phenoIDs)

#run MRA analysis pipeline
rtna <- tna.mra(rtna)

#get results
tna.get(rtna,what="mra")


## End(Not run)

[Package RTN version 2.6.3 Index]