VisuNet is an interactive tool for network visualization of complex rule-based classifiers. VisuNet can be applied to any classification problem and is commonly used with complex health-related decision tasks. The rule networks produced can clearly identify driving genes (metabolites, methylation sites, etc) and their expression levels.
VisuNet is implemented in R and uses the Shiny Gadgets attributes. The tool includes construction, filtration, visualization and customization of networks from rule-based models.
Installation
devtools::install_github("komorowskilab/VisuNet")
See the documentation.