Binference: Bayesian network inference

In saezlab/CNORfeeder: Integration of CellNOptR to add missing links

Bayesian network inference

Description

This function uses data (CNOlist) to infer a Bayesian network using the catnet package.

Usage

Binference(CNOlist, mode="AIC", tempCheckOrders=10,
            maxIter=100, filename="BAYESIAN")

Arguments

CNOlist	a CNOlist structure, as produced by makeCNOlist
mode	a character, optimization network selection criterion such as "AIC" and "BIC", to be used in cnSearchSA
tempCheckOrders	an integer, the number of iteration, orders to be searched, with constant temperature, to be used in cnSearchSA
maxIter	an integer, the total number of iterations, thus orders, to be processed, to be used in cnSearchSA
filename	name of the sif file saved, default BAYESIAN

Details

This function transforms the data in a format compatible with catnet package, infers the network using the Stochastic Network Search as implemented in catnet (see cnSearchSA), computes the consensus model of the models returned by cnSearchSA considering only links that have a frequency of appearence greater than 0.1 and returns the model in the sif format.

Value

sif	the inferred data-driven network in sif format

Author(s)

F.Eduati

See Also

mapDDN2model

Examples

## Not run: 
data(CNOlistDREAM,package="CellNOptR")
DDN<-Binference(CNOlistDREAM, tempCheckOrders=10, maxIter=100,
                filename="BAYESIAN")


## End(Not run)

saezlab/CNORfeeder documentation built on Feb. 14, 2023, 3:23 p.m.