tool.subgraph.stats: Calculate node degrees and strengths

In Mergeomics: Integrative network analysis of omics data

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)

Mergeomics documentation built on Nov. 8, 2020, 6:58 p.m.