knockouts {bnlearn} R Documentation

run the in silico gene knockout experiment on the given network model

Description

Usage

knockouts(bnlearn, geneNames);

Arguments

bnlearn

the trained network model object, which could be created by the bnlearn api or the GEARS::new. [as InsilicoPerturbationExperiment]

geneNames

a character vector of the gene id for run the knockout experiment, one @T:SMRUCC.genomics.Analysis.BNLearn.Intervention.InterventionResult

Details

the behavior of this function is determined by the strict option of the input network model: an error will be thrown when the target gene is missing from the network model in the strict mode, otherwise the wildtype expression data will be returned as the result with the Undefined flag marked as TRUE.

Authors

biosystem

Value

a vector of the InterventionResult perturbation result: the WildtypeMeans is the wildtype expression value of each gene, the MutantMeans is the expression value of each gene after the gene has been knocked out, and the FoldChanges, PercentChanges, ZScores and IsSignificant data is the differential analysis result of the perturbation.

clr value class

Examples

[Package bnlearn version 1.0.0.0 Index]