rewire_connections_to_node: Rewire connections to a node

In tgrimes/SeqNet: Generate RNA-Seq Data from Gene-Gene Association Networks

Description

Rewire connections to a node

Usage

rewire_connections_to_node(x, node, prob_rewire = 1, weights = NULL,
  alpha = 100, beta = 1, epsilon = 10^-5, run_checks = TRUE, ...)

Arguments

x	The 'network', 'network_module', or 'matrix' object to modify.
node	The node to rewire.
prob_rewire	A value between 0 and 1, inclusive. Each connection to 'node' will be rewired with probability equal to 'prob_rewire'. Note, the degree of 'node' is unchanged after this operation.
weights	(Optional) A vector of weights for each node. These are used in addition to the degree of each node when sampling nodes to rewire.
alpha	A positive value used to parameterize the Beta distribution.
beta	A positive value used to parameterize the Beta distribution.
epsilon	A small constant added to the sampling probability of each node.
run_checks	If TRUE and 'x' is a matrix, then it is checked that 'x' is an adjacency matrix. This catches the case where 'x' is a weighted matrix, in which case the weights are removed and a warning is given.
...	Additional arguments.

Value

The modified object.

Examples

# Create a random network with 10 nodes. 
nw <- random_network(10)
# Rewire connections to the first node.
nw_rewired <- rewire_connections_to_node(nw, 1)
# Plot the two networks for comparison
g <- plot(nw)
plot(nw_rewired, g) # Pass in g to mirror the layout.
# Or plot the differential network.
plot_network_diff(nw, nw_rewired, g)

tgrimes/SeqNet documentation built on Sept. 1, 2020, 7:50 a.m.