# separation: Separation In NetSci: Calculates Basic Network Measures Commonly Used in Network Medicine

 separation R Documentation

## 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.