nem (version 2.46.0)

prune.graph: Prunes spurious edges in a phenotypic hierarchy

Description

A heuristic to prune spurious edges in a pehnotypic hierarchy

Usage

prune.graph(g,cutIN=NULL,cutOUT=NULL,quant=.95,verbose=TRUE)

Arguments

g

an adjacency matrix or a 'graphNEL' object

cutIN

minimum number of missing in-edges required to cut all in-edges. Default

cutOUT

minimum number of missing out-edges required to cut all out-edges

quant

if 'cutIN' or 'cutOUT' are not assigned, a quantile 'quant' of the distribution of missing in- or out-edges for all nodes is used

verbose

Default: TRUE

Value

graph

the pruned phenotypic hierarchy (a 'graphNEL' object)

removed

number of removed edges

missing.in

number of missing in-edges for each node

missing.out

number of missing out-edges for each node

Details

prune.graph provides a heuristic approach to prune surious edges. prune.graph compares the input graph to its transitive closure, and counts for each node how many incoming and outgoing edges are missing. If the number is bigger than a user-defined cutoff, all incoming (outgoing) edges are removed.

Examples

    # a transitively closed core with two spurious edges
    g <- matrix(0,5,5)
    g[1,2] <- 1
    g[2,c(3,4)] <- 1
    g[3,4] <- 1
    g[4,5] <- 1
    dimnames(g) <- list(LETTERS[1:5],LETTERS[1:5])
    g <- as(g,"graphNEL")
    
    # prune graph
    gP <- prune.graph(g)
    
    # plot
    if(require(Rgraphviz)){
      par(mfrow=c(1,2))    
      plot(g,main="two spurious edges")
      plot(gP$graph,main="pruned")
    }