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Differential Network Analysis in R
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Differential Network Analysis in R

Examine your omics datasets in the prior knowledge context.

Follow the steps as indicated in interactive menu.

For the help overlay the mouse over the info button or go to Quick help section.

Large knowledge networks of Arabidopsis thaliana and Solanum tuberosum immune signalling are provided.


Run DiNAR from GitHub

install R-3.x.y or higher :



sudo apt-get install r-base
sudo apt-get install r-base-dev
sudo apt-get -y install libcurl4-gnutls-dev
sudo apt-get -y install libssl-dev
sudo apt-get install libv8-dev

open R and paste to console


if (!require("devtools")) install.packages("devtools")
if (!require('Rcpp')) install.packages('Rcpp')

shiny:::runGitHub("DiNAR", "NIB-SI", subdir = "DiNARscripts/")


install.packages("devtools", lib="~/R/lib")

shiny:::runGitHub("DiNAR", "NIB-SI", subdir = "DiNARscripts/")

*Note: this will install/load libraries: (V8), igraph, colourpicker, plotly, ggplot2, calibrate, stringi, magrittr, yaml, animatoR, stringr, wordcloud2, shinyjs, shinydashboard, shinyBS, colorspace, knitr, markdown, Rcpp, dplyr, rdrop2, fBasics, shinyIncubator, shinysky, downloader, visNetwork, htmltools, htmlwidgets, intergraph, network, ndtv, shinyFiles and pryr

Run DiNAR from shinyapps

🍏 (Basic - Performance Boost; Instance Size: 8GB; Max Worker Processes: 10; Max Connections per Worker: 1; Max Instances: 3)

Other options

  1. download zip and run locally in RStudio:
  2. download zip and deploy:
  3. download zip and


Additional Data Files

Code References

Create PDF animation

  1. in animatedPlotAB.R uncomment lines: 48, 49, 50, 51, 52 and 306
  2. install LaTeX (e.g.
  3. install animate Package
  4. copy to working directory and run LaTeX template document: CreatePDFanimation.tex

Create gif

  1. in animatedPlotAB.R uncomment few lines below # To generate .pdf animation comment
  2. replace myfilename = paste0("SampleGraph", length(list.files(subDir))+1, '.pdf') with myfilename = paste0("SampleGraph", formatC(length(list.files(subDir))+1, width=4, flag="0"), '.png')
  3. add few lines of code before newplot to save all produced images in .png format; e.g.
png(paste0(myfilepath, '/', myfilename), 
     width = 1500, height = 1200, 
     units = "px", pointsize = 12)
  1. add at the end of the function
  2. run short python2 script containing the following code (take care of dependencies!):
import imageio
import os
with imageio.get_writer('./my.gif', mode='I') as writer:
    for filename in sorted(os.listdir("./images/")): # images == myfilepath == where .png images of interest are
        image = imageio.imread(filename)

Find more information at: and

sub apps

Ath GSE56094 experimental data analysis



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