MaGIC Gene Set Enrichment Tool

Welcome to the Gene Set Enrichment Tool by the Molecular and Genomics Informatics Core (MaGIC).

How to Use This Tool

  1. Navigate to the Data Input tab. Upload your DESeq2 results table, or click 'Load Demo Data' to explore with a built-in synthetic dataset.
  2. Configure your analysis. Select your organism, gene ID type, and analysis mode (ORA or GSEA).
  3. Submit your data. The Enrichment Analysis tab will become visible once data is successfully loaded.
  4. Select a pathway database and run the analysis. Choose from GO, KEGG, Reactome, or MSigDB Hallmark, adjust parameters, and click 'Run Enrichment Analysis'.
  5. Explore and download results. View dot plots, bar plots, enrichment maps, gene-concept networks, and more. Download results as CSV or plots as PDF/PNG.

Over-Representation Analysis (ORA)

ORA tests whether a pre-defined set of genes (e.g., your significant DEGs) overlaps with known gene sets more than expected by chance. It uses a hypergeometric test (Fisher's exact test). You supply a gene list (typically filtered by padj and log2FC cutoffs) and a background (all measured genes).

Gene Set Enrichment Analysis (GSEA)

GSEA takes a ranked list of all genes (not just significant ones) and tests whether genes in a given set tend to cluster toward the top or bottom of the ranking. It is more sensitive than ORA because it uses the full distribution of changes, not a hard cutoff.

Required Input Data

Upload a DESeq2-style differential expression results table (CSV or TSV) with the following columns:

  • Gene identifier column: Gene symbols (e.g., TP53), Ensembl IDs (e.g., ENSG00000141510), or Entrez IDs (e.g., 7157)
  • log2FoldChange: Log2 fold change between conditions
  • pvalue: Raw p-value from the statistical test
  • padj: Adjusted p-value (Benjamini-Hochberg)
  • baseMean: (Optional) Mean normalized count across all samples 
gene_symbol, baseMean,   log2FoldChange, pvalue,    padj
TP53,        1245.32,   2.15,           1.3e-08,   5.6e-07
BRCA1,       876.41,   -1.82,           3.1e-06,   9.2e-05

Input Data

Use pre-loaded synthetic DESeq2 results to explore the tool's features.

Demo dataset: ~5000 human genes with realistic fold-change and p-value distributions (Homo sapiens, SYMBOL IDs).

Database Selection
ORA Filters
GSEA Parameters
Text Sizes