Combines Strongly Connected Components into single nodes

Description

SCCgraph is used to identify all nodes which are not distinguishable given the data.

Usage

SCCgraph(x,name=TRUE,nlength=20)

Arguments

Details

A graph inferred by either nem or nemModelSelection may have cycles if some phenotypic profiles are not distinguishable. The function SCCgraph identifies cycles in the graph (the strongly conneced components) and summarizes them in a single node. The resulting graph is then acyclic.

Value

Author(s)

Florian Markowetz, Holger Froehlich

See Also

nem, transitive.reduction

Examples

   data("BoutrosRNAi2002")
   D   <- BoutrosRNAiDiscrete[,9:16]
   res <- nem(D,control=set.default.parameters(unique(colnames(D)), para=c(.13,.05)))
   # 
   sccg <- SCCgraph(res$graph,name=TRUE)
   #
   par(mfrow=c(1,2))
   if(require(Rgraphviz)){
    plot.nem(res, main="inferred from data")      
    plot(sccg$graph, main="condensed (rel,key)")
    }

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(nem)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/nem/SCCgraph.Rd_%03d_medium.png", width=480, height=480)
> ### Name: SCCgraph
> ### Title: Combines Strongly Connected Components into single nodes
> ### Aliases: SCCgraph
> ### Keywords: graphs
> 
> ### ** Examples
> 
>    data("BoutrosRNAi2002")
>    D   <- BoutrosRNAiDiscrete[,9:16]
>    res <- nem(D,control=set.default.parameters(unique(colnames(D)), para=c(.13,.05)))
Greedy hillclimber for 4 S-genes (lambda = 0 )...

>    # 
>    sccg <- SCCgraph(res$graph,name=TRUE)
>    #
>    par(mfrow=c(1,2))
>    if(require(Rgraphviz)){
+     plot.nem(res, main="inferred from data")      
+     plot(sccg$graph, main="condensed (rel,key)")
+     }
Loading required package: Rgraphviz
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: grid
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>