random_module_structure: Create a random network structure for a module
In tgrimes/SeqNet: Generate RNA-Seq Data from Gene-Gene Association Networks

Description Usage Arguments Value Examples

A single, connected graph is created. The graph is initialized as a ring lattice, and edges are randomly rewired and/or removed. The procedure is similar to the Watts-Strogatz method, but the sampling of edges to modify can be based on the degree of each node.

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random_module_structure(size, prob_rewire = 1, prob_remove = 0.5,
  weights = NULL, neig_size = 3, alpha = 100, beta = 1,
  epsilon = 10^-5, ...)

`size`	The number of nodes to include in the graph.
`prob_rewire`	The probability of rewiring an edge.
`prob_remove`	The probability of removing an edge.
`weights`	(Optional) Weights used for sampling nodes. See ?rewire_connections_to_node and ?remove_connections_to_node for details.
`neig_size`	The neighborhood size within which the nodes of the ring lattice are connected. The initial degree of each node is 2 * 'neig_size', so long as 'size' >= (1 + 2 * 'neig_size')
`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.
`...`	Additional arguments are ignored.

An adjacency matrix representing the network structure.

# Create a random module structure (an adjacency matrix) for 10 nodes.
adj_mat <- random_module_structure(10)
# A network object can be created using this structure.
module <- create_module_from_adjacency_matrix(adj_mat)
nw <- create_network_from_modules(10, module)