Chapter 1 Overview

Here we will describe how to build a Shiny app for sequencing data using the code base described in Predicting “pain genes”: multi-modal data integration using probabilistic classifiers and interaction networks (Zhao et al).

A working example of this app is hosted at https://livedataoxford.shinyapps.io/drg-directory/ and the code base is provided at https://github.com/aliibarry/omics-database.

A previous version of https://livedataoxford.shinyapps.io/drg-directory/ was first published in Barry et al. 2023 but was updated here to reflect a more developer-friendly code base along with addition features (eg. network integration).

1.1 Shiny

If you are completely new to Shiny, we recommend working through some short tutorials first, just to wrap your head around the structure https://shiny.rstudio.com/tutorial/written-tutorial/lesson1/.

1.2 Workflow

  1. Data processing (2)
  • Prepare tables (count, differential analysis, column data)
  • Compile into a .RData or .db
  1. User interface (3)
  • Write descriptions for each dataset and save them in .\des\*
  • encouraged select appropriate plots and add descriptions
  • encouraged choose title + logo
  • optional customize aesthetic
  1. Server (4)
  • Create a description dataframe des_df for the datasets included
  • Specify directory storing your data
  • optional customize figure aesthetic by modifying provided functions
  • optional build your own functions (and link to the UI)
  1. Deploy (5)
  • Deploy your app using rsconnect::deployApp()

Happy building!

This work is licensed under a Creative Commons Attribution 4.0 International License.