tni.graph {RTN} | R Documentation

## Compute a graph from TNI objects.

### Description

Extract results from a TNI object and compute a graph.

### Usage

    tni.graph(object, tnet = "dpi", gtype="rmap", minRegulonSize=15, tfs=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.
`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.
`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

a graph object.

### Author(s)

Mauro Castro

### 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, eps=0)

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

    # 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!

    # compute association maps
    resetd(rdp)
    g <- tni.graph(rtni, tnet="ref", gtype="amap", tfs=tfs4test)
    addGraph(rdp,g)
    addLegend.size(rdp,g)
    addLegend.size(rdp,g,type="edge")

    ## End(Not run)

[Package RTN version 2.6.3 Index]