Shiny tools and the R environment

Tutorial contents · Applies to: 0.1.65

Shiny tools installs and starts complete third-party Shiny apps. R environment inspects R and manages additional packages. Installing a missing dependency does not require registering it as a separate app. The dedicated TidyMass R Shiny tutorial is a separate guide under TUTORIALS → R shiny.

Install and start a tool

  1. Open Shiny tools → Install a Shiny tool.
  2. Select GitHub, CRAN or Bioconductor and enter the repository or package.
  3. If known, enter R package name and Startup function; otherwise try automatic detection.
  4. Review the source, use the interface’s trust checkbox and click Install tool.
  5. Inspect View log, then use Open tool under Installed tools.

A repository name is not always its R package name. Do not enter a complete URL as the package name. These tools execute local R code and can have their own dependencies.

Back to installed tools returns to the list without necessarily stopping the process. Use Stop tool to release its resources.

Configure startup

Under Manage tool, select Auto-detect, Exported function, Package app_ui / app_server, or Shiny application folder as appropriate. Folder mode starts an app directory using shiny::runApp().

For an exported startup function, enter the function name alone, such as run_featuremap, not a call with parentheses or a namespace. runApp belongs to shiny; do not assume a third-party package exports it.

Install missing packages

Open R environment, identify the exact missing package, select the correct source and review the installation log. For example, org.Mm.eg.db is a Bioconductor package. Stop and restart the affected tool after installation.

Additional package libraries are managed separately from the app’s bundled library, and some tools have private dependency libraries. Check the actual loaded version when a package appears installed but the error persists. Installing from source can require system libraries or compilers; find the first substantive error rather than repeatedly reinstalling unrelated R packages.

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