setupPBN: Generate a random TPBN and a timeseries simulated from it.

In davidkwca/inferTPBN: Infer Threshold PBNs from Timeseries Data.

Description

Creates a network with the desired characteristics and simulates a list of timeseries from it which can be used to test the network inference algorithm against.

Usage

setupPBN(n = 20, k = 5, p = 0.01, inputProbabilities = c(0.5, 0.4, 0.1),
  topology = "homogeneous", gamma = 2.5, num.timepoints = 10,
  num.experiments = 20, seed = 111, verbal = FALSE)

Arguments

n	Size of the network.
k	The number of inputs per regulatory function for each gene, if homogeneous topology is used.
p	The probability of a perturbation.
inputProbabilities	Probabilities for creating one, two, three, ... regulatory functions for a gene.
topology	The topology to be used. Can be "homogeneous" or "scale_free".
gamma	The exponent for the power law if topology = "scale_free".
num.timepoints	The number of time points per timeseries generated.
num.experiments	The number of timeseries to generate.
seed	The random seed to use.

Value

A list containing the generated network and a list of timeseries simulated from it.

See Also

transformNetwork simulateNetwork

Examples

setupPBN(n=5, k=3, topology="scale_free", gamma=2.5)

davidkwca/inferTPBN documentation built on May 9, 2019, 12:53 p.m.