simulateSteadyState {ternarynet} | R Documentation

## Simulate Steady State Data

### 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)

[Package ternarynet version 1.36.0 Index]