Chapter 10: Pathway Annotation & Functional Over-Representation: DAVID, Reactome, KEGG & iLINCS

1. Over-Representation Analysis (ORA) & Hypergeometric Testing

Identifying a list of 500 differentially expressed genes is only the beginning. Biomedical insight requires contextualizing these genes into biological pathways, molecular functions, and cellular compartments. Over-Representation Analysis evaluates whether a predefined biological pathway contains statistically more DEGs than would be expected by random chance.

The probability of observing \(k\) or more pathway genes in an experimental list of \(n\) DEGs from a genome of \(N\) total genes containing \(M\) pathway members is calculated via the Hypergeometric Distribution / Fisher's Exact Test:

$$P(X \ge k) = \sum_{i=k}^{\min(n, M)} \frac{\binom{M}{i} \binom{N - M}{n - i}}{\binom{N}{n}}$$

2. Curated Biomedical Knowledgebases

3. Automated Pathway Annotation Script with clusterProfiler & ReactomePA

library(clusterProfiler)
library(org.Hs.eg.db) # Human gene annotation database
library(ReactomePA)

# 1. Extract Upregulated Genes and Convert Ensembl to Entrez IDs
sig_up_genes <- res_df %>%
    filter(Call == "UP") %>%
    pull(Gene_Symbol)

# Convert Gene Identifiers to Entrez IDs (Required by KEGG and Reactome)
entrez_ids <- bitr(
    sig_up_genes,
    fromType = "ENSEMBL",
    toType = "ENTREZID",
    OrgDb = org.Hs.eg.db
)$ENTREZID

# 2. Gene Ontology Biological Process (GO-BP) Over-Representation Analysis
go_bp <- enrichGO(
    gene = entrez_ids,
    OrgDb = org.Hs.eg.db,
    ont = "BP",
    pAdjustMethod = "BH",
    pvalueCutoff = 0.05,
    qvalueCutoff = 0.05,
    readable = TRUE
)

# 3. Reactome Pathway Enrichment
reactome_res <- enrichPathway(
    gene = entrez_ids,
    pvalueCutoff = 0.05,
    readable = TRUE
)

# 4. Visualization of Enriched Pathways
cat("Top 5 Enriched Reactome Pathways:\n")
head(as.data.frame(reactome_res)[, c("Description", "GeneRatio", "p.adjust")], 5)

# Dotplot of Enriched Biological Processes
dotplot(go_bp, showCategory = 15, title = "Top 15 Enriched GO Biological Processes")