separation: Separation

In NetSci: Calculates Basic Network Measures Commonly Used in Network Medicine

Separation

Description

Calculates the separation of two set of targets on a network. Often used to measure separation of disease modules in a interactome. Separation is calculated as in Menche, J. et al (2015) <doi:10.1126/science.1257601>.

Usage

separation(G, ST)

Arguments

G	The original graph (often an interactome).
ST	Set-Target data. It is a data.frame with two columns. ID and Target.

Value

the separation and distance of modules.

Examples

require(magrittr)
set.seed(12)
x = data.frame(n1 = sample(LETTERS[1:5]),
               n2 =  sample(LETTERS[1:20]))

D1 = data.frame(gene = c("H", "I", "S", "N", "A"), disease = "D1")
D2 = data.frame(gene = c("E", "C",  "R" , "J", "Q", "O"), disease = "D2")
D3 = data.frame(gene = c("E", "G", "T", "P"), disease = "D3")
D4 = data.frame(gene = c("A", "B", "E"), disease = "D4")

Diseases = rbind(D1, D2, D3, D4)
Diseases %<>% dplyr::select(disease, gene)
g = igraph::graph_from_data_frame(x, directed = FALSE)
g = igraph::simplify(g)

separation(G = g, ST = Diseases)

NetSci documentation built on July 4, 2022, 1:05 a.m.