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Functional Enrichment Workshop

Making sense of gene and proteins lists with functional enrichment analysis

16 WebGestaltR

WebGestaltR is the R version of the web application WebGestalt, “WEB-based GEne SeT AnaLysis Toolkit”.

This tool (both the web and R versions) has many features and advantages:

  • Simple to run
  • Runs ORA, GSEA, and NTA (network topology analysis)
  • Natively supports 12 organisms
  • Can be used for novel species (we will do this in the final session)
  • Supports many namespaces (n = 73 for human)
  • Does not require namespace conversion between the databases like clusterProfiler does (it converts to Entrez behind the scenes), and even allows different namespaces between query gene list and ORA background gene list
  • Supports many databases/gene sets (n = 70 for human) including ‘nonredundant’ versions of GO
  • Supports metabolomics, with 15 different ID types, described in Elizarraras et al 2024
  • Can run query against multiple databases simultaneously by providing database names as a list to the enrichment function
  • Has term redundancy filters including 3 custom non-redundant GO databases and two clustering algorithms
  • Saves all results files to disk when running, no need to save individual files manually
  • Creates interactive HTML reports with various plots and filter options and with term links to external databases
  • Supports multi-threading, parallelisation, and batch processing of multiple queries

16.1 Activity overview

  1. Explore the organisms, databases/gene sets and namespaces supported natively
  2. Run ORA over pathway databases and explore the interactive HTML output
  3. Run GSEA over the WebGestalt GO noRedundant and full database and compare the results

 

➤ Go back to your RStudio interface and clear your environment by selecting Session → Quit session → Dont save → Start new session

➤ Open the WebGestaltR.Rmd notebook by clicking on it in the Files pane

You could also open the file by selecting File → Open file, or use the keyboard shortcut ctrl + o.

Instructions for the analysis will continue from the R notebook.

 

16.2 End of activity summary

  • We have reviewed the organisms and databases that are natively supported by this easy to use tool
  • We have run both ORA and GSEA and explored the interactive HTML results summary
  • We have touched on the redundancy filters available within this tool, for GO as well as two external algorithms applied automatically to any enrichment performed
  • In the next session, we will use WebGestaltR for novel species FEA