ReactomePA / Reactome: Extraction of genes within a term
1
@martinbusch-15897
Last seen 4.5 years ago
Hi all,
Currently I use the ReactomePA package for functional/athway analysis and I get a couple of significantly enriched terms in my data. However, I am wondering which particular genes from my data are represented in these terms - is there an elegant way to extract the gene ids/names of all genes in a reactome term? E.g. I find the term “M Phase” in my analysis with a low adjusted p value and a high gene ratio. Now I would like to know which genes of my input are part of that particular term and contributed to that result. Is there any way to extract these genes from the term? Any help is highly appreciated, thank you in advance for your help!
Best,
Martin
pathways
reactomepa
functional annotation
• 2.6k views
@guangchuang-yu-5419
Last seen 24 days ago
China/Guangzhou/Southern Medical Univer…
You can access such information using geneInCategory function.
> require (ReactomePA)
Loading required package: ReactomePA
ReactomePA v1.24.0 For help: https://guangchuangyu.github.io/ReactomePA
If you use ReactomePA in published research, please cite:
Guangchuang Yu, Qing-Yu He. ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization. Molecular BioSystems 2016, 12(2):477-479
> data(geneList, package="DOSE")
> x = enrichPathway(names(geneList)[1:100])
> x
#
# over-representation test
#
#...@organism human
#...@ontology Reactome
#...@keytype ENTREZID
#...@gene chr [1:100] "4312" "8318" "10874" "55143" "55388" "991" "6280" "2305" ...
#...pvalues adjusted by 'BH' with cutoff <0.05
#...73 enriched terms found
'data.frame': 73 obs. of 9 variables:
$ ID : chr "R-HSA-68877" "R-HSA-69620" "R-HSA-2500257" "R-HSA-69618" ...
$ Description: chr "Mitotic Prometaphase" "Cell Cycle Checkpoints" "Resolution of Sister Chromatid Cohesion" "Mitotic Spindle Checkpoint" ...
$ GeneRatio : chr "17/80" "19/80" "14/80" "13/80" ...
$ BgRatio : chr "199/10561" "293/10561" "126/10561" "112/10561" ...
$ pvalue : num 8.59e-14 3.71e-13 4.41e-13 1.84e-12 5.70e-12 ...
$ p.adjust : num 2.10e-11 3.58e-11 3.58e-11 1.12e-10 2.32e-10 ...
$ qvalue : num 1.43e-11 2.44e-11 2.44e-11 7.63e-11 1.58e-10 ...
$ geneID : chr "55143/991/1062/9133/10403/23397/220134/4751/79019/55839/983/54821/4085/81930/332/64151/9212" "8318/55143/55388/991/1062/9133/10403/11065/220134/79019/55839/890/983/54821/4085/81930/332/9212/1111" "55143/991/1062/9133/10403/220134/79019/55839/983/54821/4085/81930/332/9212" "55143/991/1062/10403/11065/220134/79019/55839/54821/4085/81930/332/9212" ...
$ Count : int 17 19 14 13 12 12 20 12 13 13 ...
#...Citation
Guangchuang Yu, Qing-Yu He. ReactomePA: an R/Bioconductor package for
reactome pathway analysis and visualization. Molecular BioSystems
2016, 12(2):477-479
> geneInCategory(x)[["R-HSA-68877"]]
[1] "55143" "991" "1062" "9133" "10403" "23397" "220134" "4751"
[9] "79019" "55839" "983" "54821" "4085" "81930" "332" "64151"
[17] "9212"
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Thank you for your swift reply, that works perfectly fine. Since I am quite new to R, I am a bit confused with the data format of
Using
geneInCategory(x)[]I can extract all categories, but is it somehow possible to extract only a subset, e.g. those with p< 0.05 ? Thanks for your help!
Thanks a lot for your help!