Mergeomics (version 1.0.0)

tool.subgraph.search: Search neighborhoods for given nodes

Description

tool.subgraph.search looks for both upstream and downstream neighborhoods of given seed node list for a given depth, gets the directed edge information among seed nodes and their neighbors, obtains statistics (degrees and strengths) for seed nodes.

Usage

tool.subgraph.search(graph, seeds, depth, direction)

Arguments

graph

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

seeds

seed nodes' indices

depth

the maximum number of links to connect neighbors

direction

sets the directionality: use a negative value for dowstream, positive for upstream or zero for undirected

Value

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

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 neighbors.
res <- tool.subgraph.search(job.kda$graph, ranks, depth, direction)