• RNA-SEQ Insights
  • I PREFACE
  • 🌱 Welcome to the RNA-Seq Q&A Guide
    • 🌐 The CDI Learning Path
  • 📂 What kind of data will you be using in this guide?
  • II DATA PREPARATION
  • 1 How do you create a project data folder for storing RNA-Seq inputs and outputs?
    • 1.1 Explanation
    • 1.2 R Code
  • 2 How do you generate synthetic RNA-Seq counts and metadata using R?
    • 2.1 Explanation
    • 2.2 R Code
  • 3 How do you validate RNA-Seq input data before analysis using R?
    • 3.1 Explanation
    • 3.2 R Code
  • 4 How do you perform differential gene expression analysis using DESeq2 in R?
    • 4.1 Explanation
    • 4.2 R Code
  • 5 How do you create a volcano plot from DESeq2 results using R?
    • 5.1 Explanation
    • 5.2 R Code
  • 6 How do you create an MA plot from DESeq2 results using R?
    • 6.1 Explanation
    • 6.2 R Code
  • 7 How do you log-transform RNA-Seq counts for PCA or clustering using R?
    • 7.1 Explanation
    • 7.2 R Code
  • 8 How do you create a heatmap of top differentially expressed genes using R?
    • 8.1 Explanation
    • 8.2 R Code
  • 9 How do you visualize RNA-Seq samples using PCA in R?
    • 9.1 Explanation
    • 9.2 R Code
  • 10 How do you visualize the expression of a single gene across conditions using R?
    • 10.1 Explanation
    • 10.2 R Code
  • 11 How do you visualize the expression of two or more genes across conditions using R?
    • 11.1 Explanation
    • 11.2 R Code
  • Explore More Guides

🧬 RNA-Seq Data Science in R

🧬 RNA-Seq Data Science in R


Last updated: July 01, 2025