simulateSteadyState {ternarynet} | R Documentation |
This function generates simulated steady state data from a given network.
simulateSteadyState(perturbationObj, tableObj, graphObj, degreeObj, wildtype=FALSE)
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. |
The function creates a steadyStateObj.
Matthew N. McCall and Anthony Almudevar
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.
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)