tool.subgraph.stats {Mergeomics} | R Documentation

## Calculate node degrees and strengths

### Description

`tool.subgraph.stats` graph statistics (degrees and strengths) of the seed nodes obtained from their neighborhoods.

### Usage

    tool.subgraph.stats(frame, edgemap, heads, weights)

### Arguments

`frame` | a data frame including following components:
    RANK: indices of neighboring nodes (including seeds)
    LEVEL: number of edges away from seed
    STRENG: sum of adjacent edge weights within neighborhood
    DEGREE: number of adjacent edges within neighborhood
`edgemap` | list of adjacent edge information for detected neighborhoods of seed nodes. `edgemap` can belong to either tails or heads.
`heads` | list of either head (destination) or tail (source) nodes for neighborhoods of the seed nodes
`weights` | weights of the edges in the entire graph

### Value

a data list including seed nodes neighborhood information with following components:

`RANK` | indices of neighboring nodes (including seeds)
`LEVEL` | number of edges away from seed
`STRENG` | sum of adjacent edge weights within neighborhood
`DEGREE` | number of adjacent edges within neighborhood

### Author(s)

Ville-Petteri Makinen

### Examples

    data(job_kda_analyze)
    depth <- 1
    direction <- 0
    ## Take one or multiple center nodes (seeds) to search the neighborhoods:
    ## e.g. take the first node in the graph as the seed, find its neighborhood:
    center.node = job.kda$graph$nodes[1]
    ## Convert center node (seed) names to indices:
    nodes <- job.kda$graph$nodes
    ranks <- match(center.node, nodes)
    ranks <- ranks[which(ranks > 0)]
    ## we already know that rank is 1, since we took the first node in the graph
    ## as an example:
    ranks <- as.integer(ranks)
    ## Find edges to adjacent nodes. (both up- and down-stream searches)
    visited <- ranks
    levels <- 0*ranks
    for(i in 1:depth) {
    ## Find edges to adjacent nodes.
    foundT <- tool.subgraph.find(ranks, job.kda$graph$tail2edge,
    job.kda$graph$heads, visited)
    foundH <- tool.subgraph.find(ranks, job.kda$graph$head2edge,
    job.kda$graph$tails, visited)
    ## Expand neighborhood for the further depths of the neighborhood search
    ranks <- unique(c(foundT, foundH))
    visited <- c(visited, ranks)
    levels <- c(levels, (0*ranks + i)) ## level shows the depth
    if(length(ranks) < 1) break
    }
    ## Calculate node degrees and strengths.
    res <- data.frame(RANK=visited, LEVEL=levels, DEGREE=0,
    STRENG=0.0, stringsAsFactors=FALSE)
    res <- tool.subgraph.stats(res, job.kda$graph$tail2edge,
    job.kda$graph$heads, job.kda$graph$weights)
    res <- tool.subgraph.stats(res, job.kda$graph$head2edge,
    job.kda$graph$tails, job.kda$graph$weights)

[Package Mergeomics version 1.18.0 Index]