/WGCNA_tutorial

A step-by-step tutorial for Weighted correlation network analysis (WGCNA)

This R script is to demonstrate Weighted Correlation Network Analysis (WGCNA) using R.

This is the repository of the files and R script needed for the tutorial in the Youtube Channel (Liquid Brain, https://www.youtube.com/c/LiquidBrain), the topics it covers are including:

  1. What data you need for WGCNA
  2. How to perform network construction and module detection
  3. How to export the network files for visualization in Cytoscape
  4. Correlate the modules with external trait (discrete type)
  5. Correlate the modules with external trait (continuous type)
  6. Further investigation on particular module-trait relationship
  7. Visualization (e.g. scatterplot, bubble plot)
  8. Summary of the whole WGCNA analysis

References:

  1. The original tutorial provided by the creators (Peter Langfelder and Steve Horvath) https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/
  2. A nice Nature Plants paper by Yu et al. https://www.nature.com/articles/s41477-021-00897-y (Check their "data availability" section for the link to the github R script)