📂 What kind of data will you be using in this guide?

This guide uses realistic synthetic RNA-Seq data that mimics biological experiments with two conditions (e.g., Positive vs. Negative). The dataset includes:

• 🧬 A gene expression count matrix with 1000 genes and 14 samples
  
• 📑 A sample metadata file defining experimental groups
  
• 📈 Precomputed differential expression results using DESeq2

The synthetic design allows full control over expression patterns while producing biologically meaningful visualizations like PCA, volcano plots, MA plots, and heatmaps. It’s perfect for reproducible learning — no downloads or cloud access required.

✅ Once you’ve mastered the methods here, you’ll be ready to plug in your own raw or processed RNA-Seq data and apply the same analysis flow confidently.