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https://github.com/jhk0530/shinyCyJS

cytoscape.js R binding library for shiny
https://github.com/jhk0530/shinyCyJS

cytoscape cytoscapejs r shiny

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cytoscape.js R binding library for shiny

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# shinyCyJS hexsticker

[![CRAN status badge](https://www.r-pkg.org/badges/version/shinyCyJS)](https://cran.r-project.org/web/packages/shinyCyJS/index.html)
[![shinyCyJS status badge](https://jhk0530.r-universe.dev/badges/shinyCyJS)](https://jhk0530.r-universe.dev/shinyCyJS)
[![Codecov test coverage](https://codecov.io/gh/jhk0530/shinyCyJS/graph/badge.svg)](https://app.codecov.io/gh/jhk0530/shinyCyJS)

shinyCyJS is R/Shiny Package to use cytoscape.js in R environment.

cytoscape.js is a great javascript library for visualize/analysis Graph theory ( network )
if you interested, please refer to this [Link](https://js.cytoscape.org/).

shinyCyJS is built with cytoscape.js version 3.12.0. (2019/11)

## How to install :

From CRAN (1.0.0)
``` r
install.packages('shinyCyJS')
```

From r-universe (1.2.0)
```r
install.packages(
"shinyCyJS",
repos = c("https://jhk0530.r-universe.dev", "https://cloud.r-project.org")
)
```

## Example :

bulid Graph with node 4 = A, B, C, D and edge = A-B, B-C, C-D, B-D

Code

``` r
library(shiny)
library(shinyCyJS)

ui <- function() {
fluidPage(
ShinyCyJSOutput(outputId = "cy")
)
}

server <- function(input, output, session) {
nodes <- data.frame(
id = c("A", "B", "C", "D"),
width = c(10, 20, 30, 40),
height = c(10, 20, 30, 40)
)

edges <- data.frame(
source = c("A", "B", "C", "D"),
target = c("B", "C", "D", "B")
)

nodes <- buildElems(nodes, type = "Node")
edges <- buildElems(edges, type = "Edge")

obj <- shinyCyJS(c(nodes, edges))
output$cy <- renderShinyCyJS(obj)
}

shinyApp(ui, server)
```

graph example

## Versions of Javascripts

see `inst/htmlwidgets/shinyCyJS.yaml`

## Used in

gatom package

netGO

GScluster

## Suggest or comment

Make issue on [here](https://github.com/jhk0530/shinyCyJS/issues)