Shiny Web Apps

Author

Thomas Girke

Published

March 24, 2026

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What is Shiny?

Shiny is an R-based environment for building interactive web applications for data analysis and exploration (“Shiny - Tutorial,” n.d.; Chang et al. 2023). Since most JavaScript code is autogenerated by the environment, basic R knowledge is sufficient for developing Shiny apps. They can be deployed on local computers or web servers including custom and cloud-based servers (e.g. AWS, GCP, shinyapp.io service). The basic structure of a Shiny app is an app.R script containing the following components:

Step 1. User interface

ui <- fluidPage()
  1. Server function
server <- function(input, output) {}
  1. Statement to run shiny app
shinyApp(ui = ui, server = server)

Alternatively, the ui and server functions can be organized in two script files, a ui.R and a server.R script, respectively.

Develop and test Shiny app locally

Open R and set session to parent directory (here myappdir) containing shiny script app.R, and the run it with the runApp() function. A sample app.R script for testing can be downloaded from here.

library(shiny)
dir.create("myappdir")
download.file("https://raw.githubusercontent.com/tgirke/GEN242/main/static/custom/scripts/app.R", "./myappdir/app.R")
runApp("myappdir") # To show code in app, add argument: display.mode="showcase"

This will open the app in a web browser.

Deploy on web server

This can be done on local or cloud systems. An easy solution is to get an account on shinyapps.io and then deploy Shiny apps there. For details, see here.

setwd("myappdir")
library(rsconnect)
deployApp()

Example Shiny app

The following Shiny app is hosted on shinyapps.io (here Instructor account) and embedded into the markdown (or html) source of this page using the following iframe syntax:

<iframe src="https://tgirke.shinyapps.io/diamonds/" style="border: none; width: 880px; height: 900px"></iframe>

Another example from Nick Harding using Shiny App: volcanoshiny

Additional examples

Learning Shiny

The Shiny section on the Rstudio site contains excellent tutorials. In addition, users may want to explore the example apps included in the shiny package. This can be done by loading the individual examples (see here) or saving the code to a user writable directory like this:

mydir <- system.file("examples", package="shiny")
dir.create('my_shiny_test_dir')
file.copy(mydir, "my_shiny_test_dir", recursive=TRUE)
setwd("my_shiny_test_dir/examples")
runApp("01_hello") # Runs first example app in directory 
dir() # Lists available Shiny examples (directories).

Resources to learn Shiny

Tutorial and books

Extension packages

Session Info

sessionInfo()
R version 4.5.1 (2025-06-13)
Platform: x86_64-pc-linux-gnu
Running under: Debian GNU/Linux 11 (bullseye)

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0 
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0  LAPACK version 3.9.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

time zone: America/Los_Angeles
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] fgsea_1.36.0  ggplot2_4.0.1

loaded via a namespace (and not attached):
 [1] Matrix_1.7-4        gtable_0.3.6        jsonlite_2.0.0      dplyr_1.1.4         compiler_4.5.1      tidyselect_1.2.1    Rcpp_1.1.0          parallel_4.5.1      dichromat_2.0-0.1   scales_1.4.0       
[11] BiocParallel_1.44.0 yaml_2.3.12         fastmap_1.2.0       lattice_0.22-7      R6_2.6.1            generics_0.1.4      knitr_1.51          htmlwidgets_1.6.4   tibble_3.3.0        pillar_1.11.1      
[21] RColorBrewer_1.1-3  rlang_1.1.6         fastmatch_1.1-6     xfun_0.55           S7_0.2.1            otel_0.2.0          cli_3.6.5           withr_3.0.2         magrittr_2.0.4      digest_0.6.39      
[31] grid_4.5.1          cowplot_1.2.0       lifecycle_1.0.4     vctrs_0.6.5         data.table_1.18.0   evaluate_1.0.5      glue_1.8.0          farver_2.1.2        codetools_0.2-20    rmarkdown_2.30     
[41] tools_4.5.1         pkgconfig_2.0.3     htmltools_0.5.9
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References

Chang, Winston, Joe Cheng, JJ Allaire, Carson Sievert, Barret Schloerke, Yihui Xie, Jeff Allen, Jonathan McPherson, Alan Dipert, and Barbara Borges. 2023. Shiny: Web Application Framework for r. https://shiny.rstudio.com/.
“Shiny - Tutorial.” n.d. https://shiny.rstudio.com/tutorial/. https://shiny.rstudio.com/tutorial/.