tnetpost {ternarynet} | R Documentation

## Ternary Network Posterior Sampling

### Description

This function samples from the posterior density of a ternary network based on perturbation experiments.

### Usage

    tnetpost(tfit, mdelta=as.integer(10000), msample=as.integer(2000), temperatureScale=1.0, xSeed=NA)

### Arguments

`tfit` | a ternaryFit object
`mdelta` | number of transitions between samples
`msample` | number of samples
`temperatureScale` | the final temperature is multipled by this value for sampling
`xSeed` | an integer random seed. If NA, a random seed is generated.

### Value

The function returns a ternaryPost 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)
    tnpostObj <- tnetpost(tnfitObj, mdelta=10, msample=10)

[Package ternarynet version 1.36.0 Index]