tni.graph: Compute a graph from TNI objects.

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

Description

Extract results from a TNI object and compute a graph.

Usage

tni.graph(object, tnet = "dpi", gtype="rmap", minRegulonSize=15, 
regulatoryElements=NULL, amapFilter="quantile", 
amapCutoff=NULL, ntop=NULL, ...)

Arguments

object	an object of class 'TNI' TNI-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", "amap", "mmap" and "mmapDetailed". The "rmap" option returns regulatory maps represented by TFs and targets (regulons); "amap" computes association maps among regulons (estimates the overlap using the Jaccard Coefficient); "mmap" and "mmapDetailed" return modulated maps derived from the tni.conditional function.
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.
regulatoryElements	an optional 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.
ntop	when gtype="mmapDetailed", ntop is an optional single integer value (>=1) specifying the number of TF's targets that should be used to compute the modulated map. The n targets is derived from the top ranked TF-target interations, as defined in the mutual information analysis used to construct the regulon set.
...	additional arguments passed to tni.graph function.

Value

an igraph object.

Author(s)

Mauro Castro

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, eps=0)

# get the regulatory map
g <- tni.graph(rtni, tnet="dpi", gtype="rmap", 
               regulatoryElements=c("PTTG1","E2F2","FOXM1"))

# option: plot the igraph object using RedeR
library(RedeR)
rdp <- RedPort()
calld(rdp)
addGraph(rdp,g)
addLegend.shape(rdp, g)
addLegend.color(rdp, g, type="edge")
relax(rdp, p1=20, p3=50, p4=50, p5=10, p8=50, ps=TRUE)
#...it should take some time to relax!

# get the association map
resetd(rdp)
g <- tni.graph(rtni, tnet="ref", gtype="amap")
addGraph(rdp,g)
addLegend.size(rdp, g)
addLegend.size(rdp, g, type="edge")


## End(Not run)

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