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NetBID_shiny

NetBIDshiny: NetBID2 Shiny app for online hidden driver analysis and interactive visualization

Online tutorial and documentation of NetBIDshiny.

Get started now View it on GitHub

Overview

NetBIDshiny is an R Shiny application, it provides interactive online hidden driver analysis and online visualization tools for further analysis of drivers obtained from NetBID2.

NetBID2 is the upgraded second version of NetBID, which is a data-driven systems biology algorithm, using network-based Bayesian inference approach to find drivers from transcriptomics, proteomics and phosphoproteomics data. The NetBID2 R package can be found at NetBID2, and online tutorial can be found at NetBID2 tutorial.

Getting started

Dependencies

R, version >= 3.6.0

NetBID2, version >= 0.1.2

Quick start: install R package (NetBIDshiny)

  • install the R package from github
library(devtools)
library(BiocManager)
library(NetBID2)
# set repos, for R version 3.6.0, Bioconductor version 3.9
local({
  r <- getOption("repos")
  r["CRAN"] <- "https://cran.rstudio.com/"
  r["BioCsoft"] <- "https://bioconductor.org/packages/3.9/bioc"
  r["BioCann"] <- "https://bioconductor.org/packages/3.9/data/annotation"
  r["BioCexp"] <- "https://bioconductor.org/packages/3.9/data/experiment"
  options(repos = r)
})
install_github("jyyulab/NetBID_shiny",ref='master') 
# set repos, for R version 4.0, Bioconductor version 3.12
local({
  r <- getOption("repos")
  r["CRAN"] <- "https://cran.rstudio.com/"
  r["BioCsoft"] <- "https://bioconductor.org/packages/3.12/bioc"
  r["BioCann"] <- "https://bioconductor.org/packages/3.12/data/annotation"
  r["BioCexp"] <- "https://bioconductor.org/packages/3.12/data/experiment"
  options(repos = r)
})
install_github("jyyulab/NetBID_shiny",ref='master') 

install.packages('NetBIDshiny_0.1.0.tar.gz',repos=NULL)
  • Initiate the NetBIDShiny web app

Call NetBIDshiny.runner() to initiate the app for hidden driver identification and NetBIDshiny.viewer() to initiate the app for result visualization.

library(NetBIDshiny)
NetBIDshiny.runner()
NetBIDshiny.viewer()

Then open a browser and enter local url address (e.g., http://127.0.0.1:XXXX).

For the NetBIDshiny.viewer(), the user can input the RData path when calling the function and the server will automatically load the corresponding dataset. If left set to NULL, the demo dataset will be loaded.

NetBIDshiny.viewer(load_data_path = system.file('demo1','driver/DATA/analysis.par.Step.ms-tab.RData',package = "NetBID2"))

NetBIDshiny manual

The manual for all of the NetBID2 functions is linked here NetBIDshiny_0.1.0.pdf.

Tutorial dataset

We have chosen the following two datasets as the tutorial dataset:

  1. The human MB (medulloblastoma) demo dataset from the GEO database as in NetBID2: GSE116028, with network files generated by using the same dataset.

  2. The mouse BPD (bronchopulmonary dysplasia) demo dataset from the GEO database GSE25286, with network files generated by using normal lung tissue from GTEx (human).

Please see Tutorial for runner for the hidden driver estimation and Tutorial for viewer for result visualization.

Online server

The public online version of NetBIDshiny can be found here NetBIDshiny_runner and NetBIDshiny_viewer.

The online server contains network files pre-generated by SJARACNe for transcriptome datasets from the TCGA, TARGET and GTEx databases and numerous demo datasets for result visualization.

For a detailed description of usage, please see Tutorial for online server.

About the project

For a detailed description of the NetBID algorithm, please see our lab page View Yu Lab@St. Jude. Contact information: Email: xinran.dong@stjude.org or xinran.dong@foxmail.com

License

Distributed by an MIT license.