In mpatel-cai/chariot2: What the Package Does (One Line, Title Case)

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(chariot2)
library(tidyverse)
library(cli)

This package creates a properly formatted output from the OMOP Vocabularies for consumption by the DiagrammeR package.

# Fetch from Postgres  
version_key = get_version_key()
omop_relationships <-
  fetch_omop(version_key = version_key)
omop_relationships@data

Make nodes and edges and add attributes.

nodes_and_edges <- 
  create_nodes_and_edges(omop_relationships = omop_relationships)

# Add Tooltip 
nodes_and_edges <- 
  add_tooltip(nodes_and_edges = nodes_and_edges)

# Customize Nodes Attributes  
nodes_and_edges <-
  map_node_attributes(nodes_and_edges)

# Customize Edge Attributes
nodes_and_edges <-
  map_edge_attributes(nodes_and_edges)

# Construct Final Graph
final_graph <-
  construct_graph(nodes_and_edges)

library(DiagrammeR)

final_graph$graph %>%
  select_nodes(type == "Component") %>%
  transform_to_subgraph_ws() %>%
  render_graph(width = 250,
               height = 250)

component_graph <- 
final_graph$graph %>%
  select_nodes(type == "Component") %>%
  trav_out() %>%
  transform_to_subgraph_ws() 

render_graph(component_graph,
             width = 1000,
             height = 1000)

component_graph_legend <- 
  create_legend(component_graph)

component_graph_legend[[1]]

final_graph$graph %>%
  select_nodes(type == "Component") %>%
  trav_in() %>%
  transform_to_subgraph_ws() %>%
  render_graph(
             width = 1500,
             height = 1500)

hemonc_graph <- 
final_graph$graph %>%
  select_nodes(vocabulary_id == "HemOnc") %>%
  trav_out_edge() %>%
  transform_to_subgraph_ws() 

render_graph(hemonc_graph,
             width = 1500,
             height = 1500)

create_legend(hemonc_graph) %>%
  pluck(1)

final_graph$graph %>%
  select_nodes(vocabulary_id == "HemOnc") %>%
  trav_out_edge() %>%
  select_nodes(vocabulary_id == "HemOnc") %>%
  transform_to_subgraph_ws() %>%
  render_graph(width = 1500,
               height = 1500)

final_graph$graph %>%
  select_nodes(vocabulary_id == "HemOnc") %>%
  trav_out_edge(rel == "Subsumes") %>%
  transform_to_subgraph_ws() %>%
  render_graph(width = 750,
               height = 750)