6 Gene Functional Enrichment Analysis

This report covers functional enrichment analysis of differentially expressed genes from Escherichia coli K-12 MG1655 after saccharin treatment (Dedios et al., 2025).

We apply two complementary approaches:

  • ORA (Over-Representation Analysis) using mulea — tests whether significant DE genes are enriched in KEGG pathways more than expected by chance, with empirical FDR correction
  • GSEA (Gene Set Enrichment Analysis) using fgsea — uses the full ranked gene list to detect coordinated pathway-level shifts, including subtle changes below the significance threshold

Both analyses use KEGG pathway gene sets retrieved via KEGGREST for E. coli K-12 MG1655.

6.0.1 Why two packages?

mulea provides excellent empirical FDR correction for ORA but its built-in GSEA function does not compute NES (Normalised Enrichment Scores). fgsea is the gold standard for preranked GSEA with proper NES and permutation-based p-values. Using the best tool for each task gives the most reliable results.

6.0.2 Why KEGG?

The original Dedios 2025 paper used KEGG pathway analysis for E. coli MG1655, making this the biologically appropriate and directly comparable gene set database.

6.0.3 Load Libraries

library(tidyverse)
library(mulea)
library(fgsea)
library(KEGGREST)
library(knitr)
library(kableExtra)
library(DT)
library(plotly)