Differential Expression with DESeq2

DESeq2 performs differential expression analysis by comparing gene counts between your experimental groups.

Prerequisites

Before running DESeq2:

• All samples must have completed Salmon quantification
• All samples must be assigned to groups (e.g., Control, Treatment)
• You must have a group named “Control” as the reference

Running DESeq2

1. Navigate to the Differential Expression step
2. Verify all prerequisites are met (the UI will guide you)
3. Click Run DESeq2

Output

DESeq2 produces:

• Results table — Log2 fold changes, p-values, and adjusted p-values for each gene
• Volcano plot — Visualize significance vs. fold change
• MA plot — Visualize mean expression vs. fold change
• Heatmap — Top differentially expressed genes across samples

Understanding Results

• Adjusted p-value < 0.05 — Statistically significant differential expression
• Log2 fold change > 0 — Upregulated in treatment vs. control
• Log2 fold change < 0 — Downregulated in treatment vs. control

Interactive Plots

All plots are interactive — hover over points to see gene names, click to view details in the gene report panel.