create prior knowledge netwoek edges from the given vector data

prior_network {bnlearn}

R Documentation

create prior knowledge netwoek edges from the given vector data

Description

Usage

prior_network(TF, target.gene, regulation.type, confidence, evidence);

Arguments

a character vector of the transcript factor protein/rna id of each regulatory edge.

target.gene

a character vector of the target gene id of each regulatory edge.

regulation.type

a character vector of the regulation type of each regulatory edge, the value could be Unknown, Activator or Inhibitor.

confidence

a numeric vector of the confidence score of each regulatory edge, which should be a value in the range [0,1].

evidence

a character vector of the evidence source description of each regulatory edge.

Authors

biosystem

Value

a vector of the RegulatoryEdge regulatory edge data, all of the input vectors should be in the same size as the input TF vector, this generated edge collection can be used as the whitelist of the network structure learning via the bnlearn api, or be converted to a PriorNetwork object via the as.prior_net api.

clr value class

RegulatoryEdge

[Package bnlearn version 1.0.0.0 Index]