grow_DD: Grow a Duplication and Divergence Network

In langendorfr/netcom: NETwork COMparison Inference

Grow a Duplication and Divergence Network

Description

Grows an already existing network by adding a node according to the Duplication and Divergence mechanism. Nodes can only attach to previously grown nodes.

Usage

grow_DD(
  matrix,
  x,
  divergence,
  link = 0,
  connected = FALSE,
  retcon = FALSE,
  directed = TRUE
)

Arguments

matrix	Existing network to experience growth.
x	The ID of the node to be grown.
divergence	Probability that the new node loses edges associated with the node it duplicates. Needs to be between zero and one.
link	Probability that the new node attaches to the node it duplicates. Defaults to 0.
connected	Binary argument determining if the newly grown node has to be connected to the existing network. Defaults to FALSE, to prevent rare computational slow-downs when it is unlikely to create a connected network. Defaults to FALSE.
retcon	Binary variable determining if already existing nodes can attach to new nodes. Defaults to FALSE.
directed	Binary variable determining if the network is directed, resulting in off-diagonal asymmetry in the adjacency matrix. Defaults to TRUE.

Details

Different from Duplication & Mutation models in that edges can only be lost.

Value

An adjacency matrix.

References

Ispolatov, I., Krapivsky, P. L., & Yuryev, A. (2005). Duplication-divergence model of protein interaction network. Physical review E, 71(6), 061911.

Examples

# Import netcom
library(netcom)

size <- 10
existing_network <- matrix(sample(c(0,1), size = size^2, replace = TRUE), nrow = size, ncol = size)
new_network_prep <- matrix(0, nrow = size + 1, ncol = size + 1)
new_network_prep[1:size, 1:size] = existing_network
new_network <- grow_DD(matrix = new_network_prep, x = size + 1, divergence = 0.5)

langendorfr/netcom documentation built on July 23, 2022, 5:19 p.m.