stir_DM: Stirs a Duplication and Mutation Network

In langendorfr/netcom: NETwork COMparison Inference

Stirs a Duplication and Mutation Network

Description

Stirs an already existing network by rewiring a node according to the Duplication and Mutation mechanism.

Usage

stir_DM(
  matrix,
  x,
  divergence,
  mutation,
  directed = TRUE,
  link = 0,
  force_connected = FALSE
)

Arguments

matrix	Existing network to experience growth.
x	The ID of the node to be rewired (stirred).
divergence	Probability that the new node loses edges associated with the node it duplicates. Needs to be between zero and one.
mutation	Probability that the new node gains edges not associated with the node it duplicates. Needs to be between zero and one.
directed	Binary variable determining if the network is directed, resulting in off-diagonal asymmetry in the adjacency matrix.
link	Probability that the new node attaches to the node it duplicates. Defaults to 0.
force_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.

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 <- stir_DM(matrix = new_network_prep, x = size + 1, divergence = 0.5, mutation = 0.21)

langendorfr/netcom documentation built on July 19, 2024, 11:22 p.m.