8 WikiPathways analysis
WikiPathways is a continuously updated pathway database curated by a community of researchers and pathway enthusiasts. WikiPathways produces monthly releases of gmt files for supported organisms at data.wikipathways.org. The clusterProfiler package (Yu et al. 2012) supports enrichment analysis (either ORA or GSEA) for WikiPathways using the enrichWP() and gseWP() functions. These functions will automatically download and parse latest WikiPathways GMT file for selected organism.
Supported organisms can be listed by:
## [1] "Sus scrofa" "Saccharomyces cerevisiae"
## [3] "Rattus norvegicus" "Populus trichocarpa"
## [5] "Pan troglodytes" "Oryza sativa"
## [7] "Mus musculus" "Homo sapiens"
## [9] "Gallus gallus" "Equus caballus"
## [11] "Drosophila melanogaster" "Danio rerio"
## [13] "Canis familiaris" "Caenorhabditis elegans"
## [15] "Bos taurus" "Arabidopsis thaliana"
## [17] "Anopheles gambiae"8.1 WikiPathways over-representation analysis
data(geneList, package="DOSE")
gene <- names(geneList)[abs(geneList) > 2]
enrichWP(gene, organism = "Homo sapiens") ## #
## # over-representation test
## #
## #...@organism Homo sapiens
## #...@ontology WikiPathways
## #...@keytype ENTREZID
## #...@gene chr [1:207] "4312" "8318" "10874" "55143" "55388" "991" "6280" "2305" ...
## #...pvalues adjusted by 'BH' with cutoff <0.05
## #...8 enriched terms found
## 'data.frame': 8 obs. of 9 variables:
## $ ID : chr "WP2446" "WP2361" "WP179" "WP3942" ...
## $ Description: chr "Retinoblastoma gene in cancer" "Gastric cancer network 1" "Cell cycle" "PPAR signaling pathway" ...
## $ GeneRatio : chr "11/108" "6/108" "10/108" "7/108" ...
## $ BgRatio : chr "88/7858" "29/7858" "122/7858" "67/7858" ...
## $ pvalue : num 2.61e-08 2.15e-06 6.03e-06 3.36e-05 5.41e-05 ...
## $ p.adjust : num 6.46e-06 2.66e-04 4.97e-04 2.08e-03 2.67e-03 ...
## $ qvalue : num 5.83e-06 2.40e-04 4.49e-04 1.88e-03 2.41e-03 ...
## $ geneID : chr "8318/9133/7153/6241/890/983/81620/7272/1111/891/24137" "4605/7153/11065/22974/6286/6790" "8318/991/9133/890/983/7272/1111/891/4174/9232" "4312/9415/9370/5105/2167/3158/5346" ...
## $ Count : int 11 6 10 7 4 7 8 10
## #...Citation
## T Wu, E Hu, S Xu, M Chen, P Guo, Z Dai, T Feng, L Zhou, W Tang, L Zhan, X Fu, S Liu, X Bo, and G Yu.
## clusterProfiler 4.0: A universal enrichment tool for interpreting omics data.
## The Innovation. 2021, 2(3):1001418.2 WikiPathways gene set enrichment analysis
gseWP(geneList, organism = "Homo sapiens")## #
## # Gene Set Enrichment Analysis
## #
## #...@organism Homo sapiens
## #...@setType WikiPathways
## #...@keytype ENTREZID
## #...@geneList Named num [1:12495] 4.57 4.51 4.42 4.14 3.88 ...
## - attr(*, "names")= chr [1:12495] "4312" "8318" "10874" "55143" ...
## #...nPerm
## #...pvalues adjusted by 'BH' with cutoff <0.05
## #...64 enriched terms found
## 'data.frame': 64 obs. of 11 variables:
## $ ID : chr "WP2446" "WP466" "WP179" "WP45" ...
## $ Description : chr "Retinoblastoma gene in cancer" "DNA replication" "Cell cycle" "G1 to S cell cycle control" ...
## $ setSize : int 84 42 111 62 201 23 102 41 76 61 ...
## $ enrichmentScore: num 0.731 0.792 0.663 0.665 0.46 ...
## $ NES : num 2.86 2.78 2.76 2.5 2.05 ...
## $ pvalue : num 1.00e-10 1.00e-10 1.00e-10 1.11e-09 2.52e-09 ...
## $ p.adjust : num 1.93e-08 1.93e-08 1.93e-08 1.60e-07 2.91e-07 ...
## $ qvalues : num 1.62e-08 1.62e-08 1.62e-08 1.35e-07 2.46e-07 ...
## $ rank : num 1333 1002 1234 1111 1326 ...
## $ leading_edge : chr "tags=51%, list=11%, signal=46%" "tags=55%, list=8%, signal=51%" "tags=40%, list=10%, signal=36%" "tags=42%, list=9%, signal=38%" ...
## $ core_enrichment: chr "8318/9133/7153/6241/890/983/81620/7272/1111/891/24137/993/898/4998/10733/9134/4175/4173/6502/5984/994/7298/3015"| __truncated__ "8318/55388/81620/4174/4171/990/23594/4998/4175/4173/10926/5984/5111/51053/8317/5427/23649/4176/5982/5557/5558/4172/5424" "8318/991/9133/890/983/7272/1111/891/4174/9232/4171/993/990/5347/9700/898/23594/4998/9134/4175/4173/10926/6502/9"| __truncated__ "8318/983/891/4174/4171/993/898/23594/4998/9134/4175/4173/4609/5111/1869/1029/5427/23649/4176/5557/1871/1031/101"| __truncated__ ...
## #...Citation
## T Wu, E Hu, S Xu, M Chen, P Guo, Z Dai, T Feng, L Zhou, W Tang, L Zhan, X Fu, S Liu, X Bo, and G Yu.
## clusterProfiler 4.0: A universal enrichment tool for interpreting omics data.
## The Innovation. 2021, 2(3):100141If your input gene ID type is not Entrez gene ID, you can use the bitr() function to convert gene ID. If you want to convert the gene IDs in output result to gene symbols, you can use the setReadable() function.