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Preparation and Instructions for Bulk RNA-seq Tutorial

Yasin Kaymaz, Ph.D., Ege University, Bioengineering Dept. 2025-01-18

1st Winter School of Translational Immunology (TIWS)

Bioinformatics in Immunology sessions | DRY LAB 1 (Group C)

  • Day 2 (14:00 - 16:00) - Bulk RNAseq data analysis
  • Day 3 (14:00 - 16:00) - single-cell RNAseq data analysis
  • Day 4 (11:10 - 13:00) - single-cell RNAseq data analysis, cont.

Objective

This tutorial will guide students through a hands-on bulk RNA sequencing (RNA-seq) analysis using Google Colab and Python. Students will analyze gene expression data, perform normalization, PCA, sample correlation, and differential expression analysis using DESeq2.

Dataset

  • SRA Study ID: SRP428267

The publication titled “TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype and is associated with increased survival in cancer patients with high tumor macrophage content” investigates the role of Tumor Necrosis Factor-Related Apoptosis-Inducing Ligand (TRAIL) in macrophage polarization. The study demonstrates that TRAIL induces human macrophages to adopt a proinflammatory M1 phenotype. Furthermore, the research correlates high tumor macrophage content with improved survival rates in cancer patients, suggesting that TRAIL-mediated M1 polarization may contribute to anti-tumor immunity. Gunalp et al., 2023

  • Note: You will be able to download the processed gene counts matrix during the workshop.

Preparation Checklist

1. Google Account

Ensure you have an active Google account to access Google Colab. If you don’t have one, create a Google account.

2. Install Required Software (Optional)

While Google Colab eliminates the need for local installations, ensure your local machine has: - A modern browser (e.g., Chrome, Firefox, or Edge). - Stable internet connection.

3. Access the Tutorial Notebook

Download the tutorial notebook provided for this session: - File Name: Bulk_RNAseq_analysis_tutorial.ipynb - Download the file.

Session Instructions

Step 1: Open Google Colab

  1. Visit Google Colab.
  2. Sign in with your Google account.

Step 2: Upload the Notebook

  1. Click File > Upload Notebook.
  2. Upload the Bulk_RNAseq_analysis_tutorial.ipynb file from your local machine.

Step 3: Set Up the Environment

  1. Run the first cell in the notebook to install dependencies. This step will set up the required Python libraries and environment.

    !pip install pandas numpy seaborn matplotlib scikit-learn pydeseq2

  2. If additional libraries are required, follow the prompts in the notebook.

Step 4: Upload or Access Data

  • Option A: Use Preloaded Data
    • Follow the instructions in the notebook to use the sample data provided.
  • Option B: Use Your Own Data

    • Mount your Google Drive to access your datasets:

      from google.colab import drive
drive.mount('/content/drive')

Step 5: Execute the Cells

  1. Run each cell sequentially by clicking the play icon on the left of each cell.
  2. Ensure you read the accompanying instructions for each step.

Step 6: Troubleshooting

  • If any errors occur, check the error message for missing dependencies and install them.
  • Ensure that the runtime is set to Python 3 by navigating to Runtime > Change Runtime Type.

Tips for a Successful Hands-On Session

  • Save Your Progress: Periodically save your notebook by clicking File > Save a copy in Drive.
  • Ask Questions: Use the designated communication channel (e.g., Zoom chat or Slack) for real-time questions.
  • Follow Along: Ensure you’re running the cells in the correct order to avoid errors.

After the Session

Save Results

  1. Save any generated plots or data to your Google Drive or download them to your local machine.

    significant_genes.to_csv("significant_genes.csv", index=False)

Provide Feedback

Share your feedback on the session to help improve future tutorials.

Support

If you encounter issues before or during the session, contact the instructor for assistance.