simulateSteadyState: Simulate Steady State Data

In ternarynet: Ternary Network Estimation

Description

This function generates simulated steady state data from a given network.

Usage

simulateSteadyState(perturbationObj, tableObj, graphObj, degreeObj, wildtype=FALSE)

Arguments

perturbationObj	a matrix of perturbation experiments. Rows are genes and columns are experiments.
tableObj	a matrix containing the transition function tables
graphObj	a matrix containing the parents of each node
degreeObj	a vector containing the in-degree of each node
wildtype	if TRUE, the preturbations are assumed to be transient; if FALSE, the perturbations are assumed to be persistent.

Value

The function creates a steadyStateObj.

Author(s)

Matthew N. McCall and Anthony Almudevar

See Also

Almudevar A, McCall MN, McMurray H, Land H (2011). Fitting Boolean Networks from Steady State Perturbation Data, Statistical Applications in Genetics and Molecular Biology, 10(1): Article 47.

Examples

pObj <- matrix(c(1,0,0,0,1,0,0,0,1),nrow=3)
degreeObj <- c(0,1,1)
graphObj <- matrix(nrow=1,ncol=3)
graphObj[1,1] <- 0
graphObj[1,2] <- 1
graphObj[1,3] <- 2
tableObj <- matrix(nrow=3,ncol=3)
tableObj[,1] <- rep(0,3)
tableObj[,2] <- c(-1,0,1)
tableObj[,3] <- c(-1,0,1)
ssObj <- simulateSteadyState(pObj, tableObj, graphObj, degreeObj)

ternarynet documentation built on Nov. 8, 2020, 7 p.m.