In komorowskilab/VisuNet: An interactive tool for network visualization of rule-based models in R

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VisuNet is an interactive tool for structural analysis 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. VisuNet is available on GitHub.

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Rule network construction

A rule network is constructed from sets of IF-THEN rules. In the network, nodes are conjuncts of rules, ie. features, and edges connect nodes with corresponding conjuncts in rules.

The rule network resulting from a rule

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Installation

library(VisuNet)

devtools::install_github("komorowskilab/VisuNet")

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Example

This example uses gene expression data for young males with autism and control(@RN1). The rule-based classifier was created using R.ROSETTA [see @RN2].

require(VisuNet)

#Sample rule set for a classifier of young males with autism and control
#'Line by line' data type
autcon_ruleset

#Run VisuNet
#Remember to click DONE once you finish working on VisuNet
vis_out <- visunet(autcon_ruleset, type = 'L')

vis_out <- readRDS('data/visunet_out.RDS')
visNetwork(nodes = vis_out$nodes, edges = vis_out$edges, width = '100%') %>% 
  visLayout(randomSeed = 123) %>%
  visInteraction(hover = TRUE, navigationButtons = TRUE) %>%
  visOptions(selectedBy = list(variable = "group" , multiple = TRUE, main = "Select by decision", style = 'width: 200px; height: 30px;
                                                                padding-left: 80px;
                               font-size: 15px;
                               color: black;
                               border:none;
                               outline:none;'))

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Network legend

The rule network legend

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References

komorowskilab/VisuNet documentation built on Feb. 18, 2022, 8:16 p.m.