tool.graph {Mergeomics} | R Documentation

## Convert an edge list to a graph representation

### Description

`tool.graph` translates an edge list including TAIL, HEAD and WEIGHT information into a graph representation-adapted data list. It also provides in-degree and out-degree statistics for nodes.

### Usage

    tool.graph(edges)

### Arguments

`edges` | a data frame with three columns TAIL, HEAD and WEIGHT

### Value

a datalist including following components:

`nodes` | N-element array of node names
`tails` | K-element array of node indices
`heads` | K-element array of node indices
`weights` | K-element array of edge weights
`tail2edge` | N-element list of adjacent edge indices
`head2edge` | N-element list of adjacent edge indices
`outstats` | N-row data frame of out-degree node statistics
`instats` | N-row data frame of in-degree node statistics
`stats` | N-row data frame of node statistics

### Author(s)

Ville-Petteri Makinen

### See Also

`tool.subgraph`

### Examples

    job.kda <- list()
    job.kda$label<-"HDLC"
    ## parent folder for results
    job.kda$folder<-"Results"
    ## Input a network
    ## columns: TAIL HEAD WEIGHT
    job.kda$netfile<-system.file("extdata","network.mouseliver.mouse.txt",
    package="Mergeomics")
    ## module file:
    job.kda$modfile<- system.file("extdata","mergedModules.txt",
    package="Mergeomics")
    ## "0" means we do not consider edge weights while 1 is opposite.
    job.kda$edgefactor<-0.0
    ## The searching depth for the KDA
    job.kda$depth<-1
    ## 0 means we do not consider the directions of the regulatory interactions
    ## while 1 is opposite.
    job.kda$direction <- 1
    job.kda$nperm <- 20 # the default value is 2000, use 20 for unit tests

    ## kda.start() process takes long time while seeking hubs in the given net
    ## Here, we used a very small subset of the module list (1st 10 mods
    ## from the original module file):
    moddata <- tool.read(job.kda$modfile)
    mod.names <- unique(moddata$MODULE)[1:min(length(unique(moddata$MODULE)),
    10)]
    moddata <- moddata[which(!is.na(match(moddata$MODULE, mod.names))),]
    ## save this to a temporary file and set its path as new job.kda$modfile:
    tool.save(moddata, "subsetof.supersets.txt")
    job.kda$modfile <- "subsetof.supersets.txt"

    job.kda <- kda.configure(job.kda)
    ## Import data for weighted key driver analysis:
    ## Import topology.
    edgdata <- kda.start.edges(job.kda)
    ## Create an indexed graph structure.
    job.kda$graph <- tool.graph(edgdata)

    ## Remove the temporary files used for the test:
    file.remove("subsetof.supersets.txt")

[Package Mergeomics version 1.10.0 Index]