tnetfit {ternarynet} | R Documentation |
This function fits a ternary network based on perturbation experiments.
tnetfit(steadyStateObj, perturbationObj, params=ternaryFitParameters(), xSeed=NA)
steadyStateObj |
a matrix of steady gene expression observations from a perturbation experiment. Rows are genes and columns are experiments. |
perturbationObj |
a matrix of perturbation experiments. Rows are genes and columns are experiments. |
params |
a ternaryFitParameters object |
xSeed |
an integer random seed. If NA, a random seed is generated. |
The function returns a ternaryFit object.
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.
ssObj <- matrix(c(1,1,1,0,1,1,0,0,1),nrow=3) pObj <- matrix(c(1,0,0,0,1,0,0,0,1),nrow=3) rownames(ssObj) <- rownames(pObj) <- colnames(ssObj) <- colnames(pObj) <- c("Gene1","Gene2","Gene3") tnfitObj <- tnetfit(ssObj, pObj)