Hi all,
I am using R package ReactomePA for enrichment analysis. But I am getting this type of error after reading each command perfectly also.
Error in x[seq_len(n)] : object of type 'S4' is not subsettable
Thanks!
Any help ?
> require(ReactomePA) > g = as.character(1:20) > x=enrichPathway(g) > x # # over-representation test # #...@organism human #...@ontology Reactome #...@keytype ENTREZID #...@gene chr [1:20] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" ... #...pvalues adjusted by 'BH' with cutoff <0.05 #...0 enriched terms found 'data.frame': 0 obs. of 9 variables: $ ID : chr $ Description: chr $ GeneRatio : chr $ BgRatio : chr $ pvalue : num $ p.adjust : num $ qvalue : num $ geneID : chr $ Count : int #...Citation Guangchuang Yu, Qing-Yu He. ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization. Molecular BioSystems 2016, 12(2):477-479
> #...0 enriched terms found
If you print the object, it will show you that there is not enriched term found.
> head(summary(x)) [1] ID Description GeneRatio BgRatio pvalue p.adjust [7] qvalue geneID Count <0 rows> (or 0-length row.names)
`head(summary(x))` also give you such information.
This is a valid result and the output object, x, also contains information of the data that is accessible.
> x@gene [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" [16] "16" "17" "18" "19" "20" > x@organism [1] "human"
> head(x) Error in x[seq_len(n)] : object of type 'S4' is not subsettable
You can't use `head(x)` to print subset of `S4` object if the method `[` is not defined for the object. This is why `head(x)` throw the following error (error exists no matter there have terms enriched or not).
OK, I think re-define `[` can save some typing. `[`, `[[`, `head` and `tail` methods will work for `enrichResult` and `gseaResult` object. I just commit it to github.
If you want to access `summary(x)[1,]`, you can use `x[1,]` or `x[1]`.
> require(ReactomePA)
Loading required package: ReactomePA
> data(geneList)
> gene = names(geneList)[1:200]
> x = enrichPathway(gene)
> x[1]
ID Description GeneRatio BgRatio pvalue p.adjust
1640170 1640170 Cell Cycle 49/114 497/6749 1.932903e-26 6.475225e-24
qvalue
1640170 5.167972e-24
geneID
1640170 8318/55143/55388/991/2305/9493/1062/4605/9133/10403/7153/23397/6241/11065/55355/220134/4751/79019/55839/890/983/54821/4085/9837/81930/81620/332/64151/9212/51659/1111/10112/6790/891/4174/9232/4001/4171/11004/993/990/5347/701/11130/79682/57405/2491/9700/5888
Count
1640170 49
> x[1:2]
ID Description GeneRatio BgRatio pvalue
1640170 1640170 Cell Cycle 49/114 497/6749 1.932903e-26
69278 69278 Cell Cycle, Mitotic 45/114 408/6749 3.891472e-26
p.adjust qvalue
1640170 6.475225e-24 5.167972e-24
69278 6.518216e-24 5.202284e-24
geneID
1640170 8318/55143/55388/991/2305/9493/1062/4605/9133/10403/7153/23397/6241/11065/55355/220134/4751/79019/55839/890/983/54821/4085/9837/81930/81620/332/64151/9212/51659/1111/10112/6790/891/4174/9232/4001/4171/11004/993/990/5347/701/11130/79682/57405/2491/9700/5888
69278 8318/55143/55388/991/2305/9493/1062/4605/9133/10403/7153/23397/6241/11065/220134/4751/79019/55839/890/983/54821/4085/9837/81930/81620/332/64151/9212/51659/10112/6790/891/4174/9232/4171/11004/993/990/5347/701/11130/79682/57405/2491/9700
Count
1640170 49
69278 45
If you want to print the `head(summary(x))` or `tail(summary(x))` in your R console, you can use `head(x)` or `tail(x)`.
> head(x, 2)
ID Description GeneRatio BgRatio
1640170 1640170 Cell Cycle 49/114 497/6749
69278 69278 Cell Cycle, Mitotic 45/114 408/6749
pvalue p.adjust qvalue
1640170 1.932903e-26 6.475225e-24 5.167972e-24
69278 3.891472e-26 6.518216e-24 5.202284e-24
geneID
1640170 8318/55143/55388/991/2305/9493/1062/4605/9133/10403/7153/23397/6241/11065/55355/220134/4751/79019/55839/890/983/54821/4085/9837/81930/81620/332/64151/9212/51659/1111/10112/6790/891/4174/9232/4001/4171/11004/993/990/5347/701/11130/79682/57405/2491/9700/5888
69278 8318/55143/55388/991/2305/9493/1062/4605/9133/10403/7153/23397/6241/11065/220134/4751/79019/55839/890/983/54821/4085/9837/81930/81620/332/64151/9212/51659/10112/6790/891/4174/9232/4171/11004/993/990/5347/701/11130/79682/57405/2491/9700
Count
1640170 49
69278 45
> tail(x, 2)
ID Description GeneRatio BgRatio pvalue
418594 418594 G alpha (i) signalling events 9/114 203/6749 0.007158604
73886 73886 Chromosome Maintenance 5/114 75/6749 0.008498797
p.adjust qvalue geneID
418594 0.03931364 0.03137680 10874/3627/10563/6373/4283/2921/6364/9568/3576
73886 0.04592092 0.03665016 55355/79019/55839/79682/2491
Count
418594 9
73886 5
The input genes that belong to specific term can be accessed via `[[`.
> x[2]
ID Description GeneRatio BgRatio pvalue p.adjust
69278 69278 Cell Cycle, Mitotic 45/114 408/6749 3.891472e-26 6.518216e-24
qvalue
69278 5.202284e-24
geneID
69278 8318/55143/55388/991/2305/9493/1062/4605/9133/10403/7153/23397/6241/11065/220134/4751/79019/55839/890/983/54821/4085/9837/81930/81620/332/64151/9212/51659/10112/6790/891/4174/9232/4171/11004/993/990/5347/701/11130/79682/57405/2491/9700
Count
69278 45
> x[[x[2]$ID]]
[1] "8318" "55143" "55388" "991" "2305" "9493" "1062" "4605"
[9] "9133" "10403" "7153" "23397" "6241" "11065" "220134" "4751"
[17] "79019" "55839" "890" "983" "54821" "4085" "9837" "81930"
[25] "81620" "332" "64151" "9212" "51659" "10112" "6790" "891"
[33] "4174" "9232" "4171" "11004" "993" "990" "5347" "701"
[41] "11130" "79682" "57405" "2491" "9700"
>
These new features will be available in next release (expected Oct. 2016).
Dear Guangchuang Yu,
Thanks a lot for replying. But I am still not getting the effective results.
It will be really helpful. If can put more light on it. I am using ReactomePA package.
Here is my code which I am using:
library(ReactomePA)
df =read.table("GO_Chip-seq.txt")
> head(df)
ensembl_gene_id entrezgene name_1006 mgi_symbol
1 ENSMUSG00000000365 30054 cytoplasm Rnf17
2 ENSMUSG00000000365 30054 nucleus Rnf17
3 ENSMUSG00000000365 30054 protein binding Rnf17
4 ENSMUSG00000000365 30054 zinc ion binding Rnf17
5 ENSMUSG00000000365 30054 spermatid development Rnf17
6 ENSMUSG00000000365 30054 protein homodimerization activity Rnf17
f=df[,(“entrezgene")]
v <- na.omit(f)
g=unique(v)
l=as.character(g)
x <- enrichPathway(gene=g,organism="mouse",pvalueCutoff=0.05, readable=T)
As Martin said, please include a reproducible example.
Please EDIT YOUR QUESTION to include a reproducible example. For instance, when I try your code I get
> x[seq_len(n)]
Error: object 'x' not foundbecause obviously in my session R doesn't know what
xornis!
Below attached is the link to part of the file:
https://www.dropbox.com/s/wvp1lmvpprvkutm/file.txt?dl=0
After that I used the code :
library(ReactomePA)
df =read.table(“file.txt")
f=df[,(“entrezgene")]
v <- na.omit(f)
g=unique(v)
l=as.character(g)
x <- enrichPathway(gene=l,organism="mouse",pvalueCutoff=0.05, readable=T)
Here is what I get:
> x # # over-representation test # #...@organism mouse #...@ontology Reactome #...@keytype ENTREZID #...@gene chr [1:7] "30054" "237898" "217026" "12833" "27364" "22158" ... #...pvalues adjusted by 'BH' with cutoff <0.05 #...11 enriched terms found 'data.frame': 11 obs. of 9 variables: $ ID : chr "5991850" "5992181" "5992212" "5991298" ... $ Description: chr "NCAM1 interactions" "Assembly of collagen fibrils and other multimeric structures" "Collagen biosynthesis and modifying enzymes" "NCAM signaling for neurite out-growth" ... $ GeneRatio : chr "1/2" "1/2" "1/2" "1/2" ... $ BgRatio : chr "34/7109" "40/7109" "58/7109" "59/7109" ... $ pvalue : num 0.00954 0.01122 0.01625 0.01653 0.01681 ... $ p.adjust : num 0.0378 0.0378 0.0378 0.0378 0.0378 ... $ qvalue : num 0.00795 0.00795 0.00795 0.00795 0.00795 ... $ geneID : chr "Col6a1" "Col6a1" "Col6a1" "Col6a1" ... $ Count : int 1 1 1 1 1 1 1 1 1 1 ... #...Citation Guangchuang Yu, Qing-Yu He. ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization. Molecular BioSystems 2016, 12(2):477-479
Make sure you are using the latest release version of ReactomePA, see <https://guangchuangyu.github.io/2016/07/how-to-bug-author/>.
I am using ReactomePA version 1.16.2 as mentioned in bioconductor
summary:
> sessionInfo()
R version 3.3.0 (2016-05-03)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.10.5 (Yosemite)
locale:
[1] C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] devtools_1.12.0 ReactomePA_1.16.2 DOSE_2.10.3
loaded via a namespace (and not attached):
[1] graph_1.50.0 igraph_1.0.1 Rcpp_0.12.5
[4] AnnotationDbi_1.34.3 magrittr_1.5 rappdirs_0.3.1
[7] BiocGenerics_0.18.0 splines_3.3.0 IRanges_2.6.0
[10] munsell_0.4.3 colorspace_1.2-6 stringr_1.0.0
[13] plyr_1.8.3 tools_3.3.0 parallel_3.3.0
[16] grid_3.3.0 Biobase_2.32.0 gtable_0.2.0
[19] DBI_0.4-1 withr_1.0.2 reactome.db_1.55.0
[22] digest_0.6.9 GOSemSim_1.30.2 DO.db_2.9
[25] reshape2_1.4.1 ggplot2_2.1.0 S4Vectors_0.10.1
[28] memoise_1.0.0 qvalue_2.4.2 RSQLite_1.0.0
[31] stringi_1.1.1 GO.db_3.3.0 scales_0.4.0
[34] stats4_3.3.0 graphite_1.18.0
>
Sorry, I can't reproduce your issue.
> require(ReactomePA)
> packageVersion('ReactomePA')
[1] ‘1.16.2’
> l
[1] "30054" "237898" "217026" "12833" "27364" "22158" "244668"
> x <- enrichPathway(gene=l,organism="mouse",pvalueCutoff=0.05, readable=T)
> head(summary(x), 2)
ID Description
5991850 5991850 NCAM1 interactions
5992181 5992181 Assembly of collagen fibrils and other multimeric structures
GeneRatio BgRatio pvalue p.adjust qvalue geneID Count
5991850 1/2 34/7109 0.009543135 0.03776629 0.007950799 Col6a1 1
5992181 1/2 40/7109 0.011222469 0.03776629 0.007950799 Col6a1 1
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version 2.3.6
Please EDIT YOUR QUESTION to include a reproducible example. For instance, when I try your code I get
because obviously in my session R doesn't know what
xornis!Here is the part of code with head of (l):
x <- enrichPathway(gene=l,organism="mouse",pvalueCutoff=0.05, readable=T)
head(l)
[1] "30054" "237898" "217026" "12833" "27364" "22158"
> head(x)
Error in x[seq_len(n)] : object of type 'S4' is not subsettable
head(summary(x))
[1] ID Description GeneRatio BgRatio pvalue p.adjust
[7] qvalue Count
<0 rows> (or 0-length row.names)
see https://github.com/GuangchuangYu/clusterProfiler/wiki/FAQ#no-term-enriched
From the (excellent and pretty!) vignette, it looks like you mean
head(summary(x)), and I guess from GuanghuangYu's answer there are no enriched results.For what it's worth, you can discover the class and methods available on 'x' with
which might help identify what operations you can perform.