tnetpost: Ternary Network Posterior Sampling

In ternarynet: Ternary Network Estimation

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)

ternarynet documentation built on Nov. 8, 2020, 7 p.m.