Gene Co-expression Network Workshop

This repository contains the materials for a workshop on Gene Co-expression Networks, with a focus on the implementation and exploration of the Weighted Gene Co-expression Network Analysis (WGCNA) methodology.

Workshop Overview

The workshop is based on a subset of the Chlamydomonas reinhardtii transcriptome under salt stress conditions. The main goal is to explore this transcriptome dataset, apply WGCNA concepts, and investigate how different parameters affect the construction and interpretation of gene co-expression networks.

Repository Structure

• data/
  Contains raw count data, example network files, and other datasets used in the workshop.

  • data_example1_net_edges.txt: Example network edges file.
  • data_example2_network.csv: Example network file from different tool.
  • rawData.csv: Raw count matrix.
  • proteome_uniprot.csv: Protein annotation file.
  • coldata.csv: Sample metadata.

• docs/
  Contains course notes, slides, syllabus, a list of useful tools, and report instructions.

  • notes_Co-expressionNetwork.md: Workshop notes.
  • Syllabus_Co-expressionNetwork.md: Workshop syllabus.
  • ToolLists_Co-expressionNetwork.md: List of tools and resources.
  • Co-expressionNetwork_WorkshopContent.pdf: Workshop slides.
  • WGCNA_workshop_report_instructions.md: Instructions for preparing your research report.
  • Figures/: Figures and images used in the workshop.

• code/
  Contains all R scripts and code used for the workshop exercises and analyses.

  • WGCNA_script1.R: Main WGCNA analysis script.
  • WGCNA_script2.R: Additional WGCNA analysis script.
  • data_example2_net_edges.txt: Example network edges for exercises.
  • data_example2_net_nodes.txt: Example network nodes for exercises.

Workshop Report Instructions

Please refer to docs/WGCNA_workshop_report_instructions.md for detailed guidelines on preparing your research report for this workshop.

Getting Started

1. Clone or download (zip and unzip) this repository.
2. To use the scripts, first open the workshop.Rproj file located in the root folder. This will ensure the correct working directory is set.
3. Follow the scripts in the code/ directory and refer to the notes in docs/ for guidance. The scripts include details on the necessary R packages to install.

About the Example Dataset

The example dataset is a subset of the C. reinhardtii transcriptome under salt stress. Participants will explore this dataset, apply WGCNA, and learn how to adjust parameters to construct and interpret gene co-expression networks.

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For questions or suggestions, please open an issue or contact the workshop organizers.