Compute a graph from TNA objects.

Description

Extract results from a TNA object and compute a graph.

Usage

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tna.graph(object, tnet = "dpi", gtype="rmap", minRegulonSize=15, tfs=NULL, 
amapFilter="quantile", amapCutoff=NULL, ...)

Arguments

object

an object of class 'TNA' TNA-class.

tnet

a single character value specifying which network information should be used to compute the graph. Options: "ref" and "dpi".

gtype

a single character value specifying the graph type. Options: "rmap" and "amap". The "rmap" option returns regulatory maps represented by TFs and targets (regulons) and "amap" computes association maps among regulons (estimates the overlap using the Jaccard Coefficient).

minRegulonSize

a single integer or numeric value specifying the minimum number of elements in a regulon. Regulons with fewer than this number are removed from the graph.

tfs

a vector with transcription factor identifiers.

amapFilter

a single character value specifying which method should be used to filter association maps (only when gtype="amap"). Options: "phyper","quantile" and "custom".

amapCutoff

a single numeric value (>=0 and <=1) specifying the cutoff for the association map filter. When amapFilter="phyper", amapCutoff corresponds to a pvalue cutoff; when amapFilter="quantile", amapCutoff corresponds to a quantile threshold; and when amapFilter="custom", amapCutoff is a JC threshold.

...

additional arguments passed to tna.graph function.

Value

a graph object.

Author(s)

Mauro Castro

Examples

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data(dt4rtn)

tfs4test<-c("PTTG1","E2F2","FOXM1","E2F3","RUNX2")
rtni <- new("TNI", gexp=dt4rtn$gexp, transcriptionFactors=dt4rtn$tfs[tfs4test])

## Not run: 

rtni<-tni.preprocess(rtni,gexpIDs=dt4rtn$gexpIDs)
rtni<-tni.permutation(rtni)
rtni<-tni.bootstrap(rtni)
rtni<-tni.dpi.filter(rtni, eps=0.05)

#run MRA analysis pipeline
rtna<-tni2tna.preprocess(rtni, phenotype=dt4rtn$pheno, hits=dt4rtn$hits, phenoIDs=dt4rtn$phenoIDs)
rtna <- tna.mra(rtna)

# compute regulatory maps
g<-tna.graph(rtna, tnet="dpi", gtype="rmap", tfs=tfs4test)

# option: plot the igraph object using RedeR
#library(RedeR)
#rdp<-RedPort()
#calld(rdp)
#addGraph(rdp,g)
#relax(rdp,p1=50,p5=20)

# compute association maps
g<-tna.graph(rtna, tnet="ref", gtype="amap", tfs=tfs4test)


## End(Not run)

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