Version Compatibility

Reference examples tested with: R stats (base), clusterProfiler 4.10+

Before using code patterns, verify installed versions match. If versions differ:

• R: packageVersion('<pkg>') then ?function_name to verify parameters

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

KEGG Pathway Enrichment

Core Pattern

Goal: Identify KEGG metabolic and signaling pathways over-represented in a gene list.

Approach: Test for enrichment using the hypergeometric test via clusterProfiler enrichKEGG against the KEGG online database.

"Find enriched KEGG pathways in my gene list" → Test whether KEGG pathway gene sets are over-represented among significant genes.

library(clusterProfiler)

kk <- enrichKEGG(
    gene = gene_list,           # Character vector of gene IDs
    organism = 'hsa',           # KEGG organism code
    pvalueCutoff = 0.05,
    pAdjustMethod = 'BH'
)

Prepare Gene List

Goal: Extract significant Entrez gene IDs from DE results in the format required by enrichKEGG.

Approach: Filter by significance thresholds and convert gene symbols to Entrez IDs (KEGG requires NCBI Entrez).

library(org.Hs.eg.db)

de_results <- read.csv('de_results.csv')
sig_genes <- de_results$gene_id[de_results$padj < 0.05 & abs(de_results$log2FoldChange) > 1]

# KEGG requires NCBI Entrez gene IDs (kegg, ncbi-geneid)
gene_ids <- bitr(sig_genes, fromType = 'SYMBOL', toType = 'ENTREZID', OrgDb = org.Hs.eg.db)
gene_list <- gene_ids$ENTREZID

KEGG ID Conversion

Goal: Convert between KEGG-specific identifiers and other gene ID formats.

Approach: Use bitr_kegg to map between kegg, ncbi-geneid, ncbi-proteinid, and uniprot ID types.