WikiPathways enrichment using clusterProfiler and rWikiPathways. Use when analyzing gene lists against community-curated open-source pathways...
Reference examples tested with: clusterProfiler 4.18+, rWikiPathways 1.26+, org.Hs.eg.db 3.18+.
Before using code patterns, verify installed versions match. If versions differ:
packageVersion('<pkg>') then ?function_name to verify parametersIf code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
WikiPathways is a LIVE, monthly-updated database. enrichWP, gseWP, and gson_WP all download data.wikipathways.org/current/gmt/ at run time, so the SAME code returns DIFFERENT pathways and p-values months apart with no error. current/ is not a version. For a reproducible analysis pin a dated release with downloadPathwayArchive(date='YYYYMMDD', organism=, format='gmt') and report the date. All enrichWP/gseWP/downloadPathwayArchive calls require internet at run time.
"Which community-curated WikiPathways are enriched in my genes?" -> Test WikiPathways gene sets against a gene list (ORA) or a ranked vector (GSEA), pinning a dated GMT for reproducibility - because the live monthly database changes under identical code, and the WP GMT is Entrez-keyed so any other ID type silently overlaps nothing.
enrichWP(entrez, organism='Homo sapiens', universe=all_entrez)gseWP(named_decreasing_entrez_vector, organism='Homo sapiens')downloadPathwayArchive(date='YYYYMMDD', organism=, format='gmt') -> read.gmt -> split term -> enricher/GSEAScope: WikiPathways-specific enrichment - the data model, the current/-vs-dated GMT reproducibility pin, the Entrez-GMT requirement, the term-field split, PFOCR as a noisier complement, and the WP-vs-KEGG-vs-Reactome contrast. The ORA/GSEA method choice and hypergeometric/background theory -> the category README. The DE list and ranking statistic -> differential-expression/de-results. KEGG and Reactome -> kegg-pathways, reactome-pathways. Plot grammar -> enrichment-visualization.
WikiPathways is a wiki: anyone can create or edit a pathway, content is CC0, and there is NO formal journal-style peer review gating a pathway's publication (Pico 2008 PLoS Biol 6:e184; Martens 2021 NAR 49:D613). The collection is republished as a dated GMT archive every MONTH. Three properties every misuse forgets:
current/ is not a version. enrichWP, gseWP, and gson_WP all silently download data.wikipathways.org/current/gmt/ - the latest monthly release. Identical code two months apart returns different pathways and different p-values, with no error and no warning. Reproducibility is NOT a code freeze; it is a dated GMT: downloadPathwayArchive(date='20240310', organism='Homo sapiens', format='gmt'), read it, run enricher/GSEA on the pinned sets, and report the date in methods. gson_WP() freezes only within a session (it snapshots current/), not across time.
The WP GMT speaks Entrez, and the wrong ID type fails silently. The GMT is Entrez-keyed via BridgeDb. Passing SYMBOL or ENSEMBL yields near-zero overlap and an empty or misleading result with NO error - convert to Entrez upstream (bitr/OrgDb) before enrichWP. Likewise universe=NULL makes the background "all genes that happen to be in WP" - a small, biased set that inflates significance; pass the assayed/tested Entrez vector as universe.
A community pathway is a hypothesis someone drew, not a reviewed fact. The two things that make WP valuable (open CC0 license, anyone-can-edit curation that captures disease/drug pathways KEGG and Reactome lack, e.g. the COVID-19 Disease Map) are the same two things that make its quality heterogeneous. Many WP pathways are also imported from KEGG/Reactome, so "three databases agree" can be circular rather than independent. Treat each hit as a community claim - check getPathwayInfo(WPID) last-edit/curation before leaning on a single WP pathway for a key conclusion - and run WP as a COMPLEMENT to KEGG/Reactome, never a sole peer-reviewed source.
| Source / function | Citation | Mechanism / role | When |
|---|---|---|---|
WikiPathways ORA (enrichWP) |
Pico 2008 PLoS Biol 6:e184; Martens 2021 NAR 49:D613; Wu 2021 Innovation 2:100141 | hypergeometric test vs the WP GMT (delegates to enricher); downloads current/ |
a thresholded gene LIST against community pathways |
WikiPathways GSEA (gseWP) |
Agrawal 2024 NAR 52:D679; Wu 2021 Innovation 2:100141 | running-sum FCS over a ranked vector (delegates to GSEA); downloads current/ |
all genes ranked, no arbitrary cutoff |
rWikiPathways (query/download) |
Slenter/Hanspers/Pico, Bioconductor | API client: listOrganisms, listPathways, getPathwayInfo, getXrefList, findPathwaysByText, downloadPathwayArchive |
inspect pathways, fetch genes, pin a dated GMT |
Dated GMT + enricher/GSEA |
Wu 2021 Innovation 2:100141 | run enrichment on a pinned, parsed GMT, bypassing auto-download | the REPRODUCIBLE pattern; report the date |
| PFOCR (Pathway Figure OCR) | Hanspers 2020 Genome Biol 21:273; Shin 2023 BMC Genomics 24:713 | machine-OCR'd gene sets from published figures; larger + noisier, no edges | high-recall disease/process coverage as a complement; NOT what enrichWP queries |
| KEGG / Reactome (siblings) | -> kegg-pathways, reactome-pathways | metabolic/signaling maps (live) / curated reactions (local) | the primary databases WP complements |
| Scenario | Recommended | Why |
|---|---|---|
| Quick exploratory ORA, reproducibility not yet needed | enrichWP(entrez, organism, universe=all_entrez) |
fastest path; log that it used the current/ release |
| Publication / reproducible analysis | downloadPathwayArchive(date='YYYYMMDD', organism, format='gmt') -> read -> split -> enricher/GSEA |
the dated GMT is the only cross-time pin; report the date |
| All genes carry a DE statistic, cutoff would be arbitrary | gseWP (see the category README for the ORA/GSEA choice) |
ranked FCS uses the full list, no cutoff |
| Pre-selected list (module, screen hits, GWAS loci) | enrichWP ORA |
no ranking available |
| Disease / drug pathways missing from KEGG/Reactome | WP as a complement, run alongside KEGG/Reactome | community content is genuinely additive where it exists |
| Maximum gene/process coverage, noise tolerable | PFOCR (separate resource), not enrichWP |
figure-OCR sets are higher-recall, lower-precision |
| Non-model but WP-supported species (zebrafish, fly, worm, Arabidopsis) | enrichWP(entrez, '<scientific name>'), verify via get_wp_organisms() |
WP covers ~30+ species |
| Compare up- vs down-regulated | compareCluster(geneClusters=list(up=..,down=..), fun='enrichWP', organism=) |
one model, faceted dotplot |
| Genes are SYMBOL/ENSEMBL | convert to Entrez first (bitr) |
the WP GMT is Entrez-keyed; other types overlap nothing |
Goal: Find WikiPathways over-represented in a thresholded gene list, against a defensible background.
Approach: Convert significant genes to Entrez, pass the tested-gene set as universe, run enrichWP, then make the result readable. enrichWP downloads the current/ GMT - acceptable for exploration, but pin a date for anything reportable.
library(clusterProfiler)
library(org.Hs.eg.db)
# enrichWP downloads the current/ WP GMT over the network; symbols/Ensembl must be Entrez first
sig <- bitr(sig_symbols, fromType='SYMBOL', toType='ENTREZID', OrgDb=org.Hs.eg.db)$ENTREZID
all_entrez <- bitr(tested_symbols, fromType='SYMBOL', toType='ENTREZID', OrgDb=org.Hs.eg.db)$ENTREZID
wp <- enrichWP(gene=sig, organism='Homo sapiens', universe=all_entrez,
pvalueCutoff=0.05, pAdjustMethod='BH', minGSSize=10, maxGSSize=500, qvalueCutoff=0.2)
wp <- setReadable(wp, OrgDb=org.Hs.eg.db, keyType='ENTREZID') # geneID column -> symbols
as.data.frame(wp) # ID=WPID, Description, GeneRatio, BgRatio, p.adjust, qvalue, Count
Goal: Find WikiPathways whose genes shift coordinately across the full ranking, with no cutoff.
Approach: Build a NAMED Entrez vector sorted DECREASING by the ranking metric, fix the permutation seed, then run gseWP. There is no universe argument - FCS uses the whole ranked list.
gl <- sort(setNames(de$log2FoldChange, de$entrez), decreasing=TRUE) # named, decreasing, Entrez names
set.seed(123) # fix permutation reproducibility
wp_gsea <- gseWP(geneList=gl, organism='Homo sapiens',
pvalueCutoff=0.05, pAdjustMethod='BH', minGSSize=10, maxGSSize=500)
as.data.frame(wp_gsea) # NES, p.adjust, core_enrichment (the leading edge)
Goal: Make a WP analysis reproducible across re-runs by pinning a dated release instead of pulling current/.
Approach: Download a dated GMT (pass format='gmt' - the default is gpml), split the compound name%version%wpid%org term field into TERM2GENE/TERM2NAME, run enricher/GSEA on the pinned sets, and report the date in methods.
library(rWikiPathways)
library(tidyr)
# downloadPathwayArchive needs an organism to actually download a file (organism=NULL opens the index)
gmt <- downloadPathwayArchive(date='20240310', organism='Homo sapiens', format='gmt', destpath=tempdir())
wp2gene <- read.gmt(file.path(tempdir(), gmt))
wp2gene <- separate(wp2gene, term, c('name','version','wpid','org'), sep='%') # term is a %-joined compound
t2g <- wp2gene[, c('wpid','gene')] # TERM2GENE
t2n <- wp2gene[, c('wpid','name')] # TERM2NAME
wp_pinned <- enricher(sig, universe=all_entrez, TERM2GENE=t2g, TERM2NAME=t2n) # report date='20240310'
gson_WP(organism) returns a GSON snapshot object, but it still pulls current/ - it freezes a session, NOT a chosen historical date. Only the dated downloadPathwayArchive GMT survives a re-run months later.
library(rWikiPathways)
listOrganisms() # supported species (full scientific names; ~30+)
listPathways('Homo sapiens') # all WPIDs + names for a species
getPathwayInfo('WP554') # metadata incl. last-edit; check before trusting a single hit
getXrefList('WP554', 'L') # genes by BridgeDb system code: 'L'=Entrez, 'H'=HGNC, 'En'=Ensembl
findPathwaysByText('cancer') # text search (searchPathways() is NOT a current function)
wp_mouse <- enrichWP(gene=mouse_entrez, organism='Mus musculus')
wp_zfish <- enrichWP(gene=zfish_entrez, organism='Danio rerio')
# verify the exact organism string before running:
get_wp_organisms() # plural accessor; the string must match exactly
Trigger: running enrichWP/gseWP/gson_WP without downloadPathwayArchive(date=). Mechanism: all three download data.wikipathways.org/current/, the latest monthly release. Symptom: the same script returns different pathways/p-values months apart, with no error. Fix: pin a dated GMT, run enricher/GSEA on it, and report the date.
Trigger: passing SYMBOL/ENSEMBL IDs to enrichWP/gseWP. Mechanism: the WP GMT is Entrez-keyed via BridgeDb, so non-Entrez IDs overlap nothing. Symptom: an empty or near-empty result, NO error. Fix: bitr to ENTREZID first; confirm the conversion rate before trusting the result.
Trigger: universe=NULL (the default). Mechanism: enricher then uses "all genes in the WP GMT" as background - a small, biased set, not the assayed genes. Symptom: implausibly strong p-values for tissue-specific or off-target pathways. Fix: pass the tested-gene Entrez vector as universe.
Trigger: treating gson_WP() as "the snapshot" for a reproducible analysis. Mechanism: it snapshots current/ into an object - it freezes a session, not a historical date. Symptom: a re-run months later gives a different snapshot. Fix: use the dated downloadPathwayArchive GMT for cross-time reproducibility.
Trigger: read.gmt on a WP GMT without splitting the term. Mechanism: the set-name field is a compound name%version%wpid%org joined by %. Symptom: WPIDs and clean names are buried in one column; TERM2GENE/TERM2NAME are wrong. Fix: separate(., term, c('name','version','wpid','org'), sep='%') (or use read.gmt.wp).
Trigger: calling searchPathways('cancer', 'Homo sapiens'). Mechanism: it is not a current rWikiPathways function. Symptom: an error. Fix: findPathwaysByText() / findPathwayIdsByText().
Trigger: downloadPathwayArchive(date=, organism=) without format='gmt'. Mechanism: format defaults to gpml, which read.gmt cannot read. Symptom: a GPML file or a parse error. Fix: pass format='gmt'.
| Threshold | Source | Rationale |
|---|---|---|
pvalueCutoff=0.05 |
enricher/GSEA default |
filters on p.adjust (BH) by default; standard FDR gate |
qvalueCutoff=0.2 |
clusterProfiler enricher default |
secondary q-value gate on ORA |
pAdjustMethod='BH' |
clusterProfiler default | Benjamini-Hochberg FDR; not Bonferroni (too conservative for gene-set screens) |
minGSSize=10 |
enricher/GSEA default |
drop tiny WP pathways that overfit; many WP specialist sets fall below this and are never tested |
maxGSSize=500 |
enricher/GSEA default |
drop overly broad sets that always "enrich" |
set.seed(123) for gseWP |
reproducibility convention | permutation p-values drift across runs without a fixed seed (any fixed seed works) |
Pin date='YYYYMMDD' |
Martens 2021 NAR 49:D613 | WP republishes monthly; current/ is not a version, so report the dated release |
| Error / symptom | Cause | Solution |
|---|---|---|
enrichWP returns 0 terms |
passed SYMBOL/ENSEMBL not Entrez | bitr to ENTREZID first |
| Implausibly significant pathways | universe=NULL (all-WP-genes background) |
pass the tested-gene Entrez vector as universe |
| Different results each run | unpinned current/ release |
downloadPathwayArchive(date=, format='gmt'); report the date |
searchPathways error |
function removed | use findPathwaysByText() |
read.gmt term column is a %-compound |
term field not split | separate(., term, c('name','version','wpid','org'), sep='%') |
downloadPathwayArchive opens a browser / downloads nothing |
organism=NULL |
name the organism to actually download a file |
| GPML where a GMT was expected | format defaulted to gpml |
pass format='gmt' |
gseWP error about vector names |
geneList not named or not sorted decreasing | build a named Entrez vector, sort(decreasing=TRUE) |