tnetfit {ternarynet} | R Documentation

## Ternary Network Fitting

### Description

This function fits a ternary network based on perturbation experiments.

### Usage

    tnetfit(steadyStateObj, perturbationObj, params=ternaryFitParameters(),
    xSeed=NA)

### Arguments

`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.

### Value

The function returns a ternaryFit object.

### 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

    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)

[Package ternarynet version 1.36.0 Index]