AgentSkillsCN

bio-pathway-wikipathways

利用 clusterProfiler 和 rWikiPathways 对基因列表进行富集分析。当您需要根据社区共建的开源通路数据库对基因列表进行分析时,请使用此方法。该方法可对 30 多种物种开展过度富集分析与 GSEA。

SKILL.md
--- frontmatter
name: bio-pathway-wikipathways
description: WikiPathways enrichment using clusterProfiler and rWikiPathways. Use when analyzing gene lists against community-curated open-source pathways. Performs over-representation analysis and GSEA for 30+ species.
tool_type: r
primary_tool: clusterProfiler

WikiPathways Enrichment

Core Pattern - Over-Representation Analysis

r
library(clusterProfiler)
library(org.Hs.eg.db)

wp_result <- enrichWP(
    gene = entrez_ids,         # Character vector of Entrez IDs
    organism = 'Homo sapiens', # Full species name
    pvalueCutoff = 0.05,
    pAdjustMethod = 'BH'
)

head(as.data.frame(wp_result))

Prepare Gene List

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

gene_ids <- bitr(sig_genes, fromType = 'SYMBOL', toType = 'ENTREZID', OrgDb = org.Hs.eg.db)
entrez_ids <- gene_ids$ENTREZID

GSEA on WikiPathways

r
# Create ranked gene list
gene_list <- de_results$log2FoldChange
names(gene_list) <- de_results$entrez_id
gene_list <- sort(gene_list, decreasing = TRUE)

gsea_wp <- gseWP(
    geneList = gene_list,
    organism = 'Homo sapiens',
    pvalueCutoff = 0.05,
    pAdjustMethod = 'BH'
)

head(as.data.frame(gsea_wp))

With Background Universe

r
all_genes <- de_results$entrez_id

wp_result <- enrichWP(
    gene = entrez_ids,
    universe = all_genes,
    organism = 'Homo sapiens',
    pvalueCutoff = 0.05
)

Make Results Readable

r
# Convert Entrez IDs to gene symbols
wp_readable <- setReadable(wp_result, OrgDb = org.Hs.eg.db, keyType = 'ENTREZID')

Visualization

r
library(enrichplot)

# Dot plot
dotplot(wp_result, showCategory = 15)

# Bar plot
barplot(wp_result, showCategory = 15)

# Gene-concept network
cnetplot(wp_readable, categorySize = 'pvalue')

# Enrichment map
wp_result <- pairwise_termsim(wp_result)
emapplot(wp_result)

Using rWikiPathways Directly

r
library(rWikiPathways)

# List available organisms
listOrganisms()

# Get all pathways for an organism
human_pathways <- listPathways('Homo sapiens')

# Get pathway info
pathway_info <- getPathwayInfo('WP554')  # ACE Inhibitor Pathway

# Get genes in a pathway
pathway_genes <- getXrefList('WP554', 'H')  # HGNC symbols
pathway_entrez <- getXrefList('WP554', 'L')  # Entrez IDs

# Download pathway as GMT for custom analysis
downloadPathwayArchive(organism = 'Homo sapiens', format = 'gmt')

Custom GMT-Based Analysis

r
# Download WikiPathways GMT
library(rWikiPathways)
downloadPathwayArchive(organism = 'Homo sapiens', format = 'gmt', destpath = '.')

# Read GMT and run enrichment
wp_gmt <- read.gmt('wikipathways-Homo_sapiens.gmt')

wp_custom <- enricher(
    gene = entrez_ids,
    TERM2GENE = wp_gmt,
    pvalueCutoff = 0.05
)

Different Organisms

r
# Mouse
wp_mouse <- enrichWP(gene = mouse_entrez, organism = 'Mus musculus')

# Rat
wp_rat <- enrichWP(gene = rat_entrez, organism = 'Rattus norvegicus')

# Zebrafish
wp_zfish <- enrichWP(gene = zfish_entrez, organism = 'Danio rerio')

# List all available organisms
library(rWikiPathways)
listOrganisms()

Compare Clusters

r
gene_clusters <- list(
    upregulated = up_genes,
    downregulated = down_genes
)

compare_wp <- compareCluster(
    geneClusters = gene_clusters,
    fun = 'enrichWP',
    organism = 'Homo sapiens',
    pvalueCutoff = 0.05
)

dotplot(compare_wp)

Export Results

r
results_df <- as.data.frame(wp_result)
write.csv(results_df, 'wikipathways_enrichment.csv', row.names = FALSE)

Key Parameters

ParameterDefaultDescription
generequiredVector of Entrez IDs
organismrequiredFull species name
pvalueCutoff0.05P-value threshold
pAdjustMethodBHAdjustment method
universeNULLBackground genes
minGSSize10Min genes per pathway
maxGSSize500Max genes per pathway

Common Organisms

Common NameScientific Name
HumanHomo sapiens
MouseMus musculus
RatRattus norvegicus
ZebrafishDanio rerio
Fruit flyDrosophila melanogaster
C. elegansCaenorhabditis elegans
ArabidopsisArabidopsis thaliana
YeastSaccharomyces cerevisiae

WikiPathways vs Other Databases

FeatureWikiPathwaysKEGGReactome
CurationCommunityExpertPeer-reviewed
LicenseOpen (CC0)CommercialOpen
Species30+4000+7
FocusDisease, drugMetabolicSignaling
UpdatesContinuousOngoingQuarterly

Related Skills

  • go-enrichment - Gene Ontology enrichment
  • kegg-pathways - KEGG pathway enrichment
  • reactome-pathways - Reactome pathway enrichment
  • gsea - Gene Set Enrichment Analysis
  • enrichment-visualization - Visualization functions