Question

enrichGO returning NA

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scanchi • 0

@scanchi-14313

Last seen 6.2 years ago

When I run the enrichGO function on a set of DEG, I am getting NA in the 'Description' column for a few GO term ID's. How could I rectify this error ? Or is there a way to skip NA terms when using dotplot for visualization ?

head(condition.control_dge)
ENTREZID  SYMBOL
    6536  SLC6A9
    4601    MXI1
    3799   KIF5B
    4286    MITF
    9509 ADAMTS2
   22834  ZNF652

condition.control_ego=enrichGO(condition.control_dge$ENTREZID,'org.Hs.eg.db', ont="BP",pvalueCutoff=0.05,qvalueCutoff=0.05,pAdjustMethod="BH")

head(condition.control_ego)

`ID`	`Description`	`GeneRatio`	`BgRatio`	`pvalue`	`p.adjust`	`qvalue`
`GO:0051650`	`establishment of vesicle localization`	`153/6595`	`251/17381`	`9.23E-14`	`5.62E-10`	`4.67E-10`
`GO:0051648`	`vesicle localization`	`159/6595`	`265/17381`	`2.05E-13`	`6.23E-10`	`5.17E-10`
`GO:0051656`	`establishment of organelle localization`	`243/6595`	`450/17381`	`1.90E-12`	`3.85E-09`	`3.20E-09`
`GO:0042063`	`gliogenesis`	`150/6595`	`254/17381`	`5.60E-12`	`6.99E-09`	`5.81E-09`
`GO:0006914`	`autophagy`	`250/6595`	`470/17381`	`7.57E-12`	`6.99E-09`	`5.81E-09`
`GO:0061919`	`NA`	`250/6595`	`470/17381`	`7.57E-12`	`6.99E-09`	`5.81E-09`

The GO term with NA returns a non empty result when querying with GO.db

       GOID                                   TERM
 GO:0061919   process utilizing autophagic mechanism

sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS release 6.6 (Final)

Matrix products: default
BLAS: /projects/builder-group/jpg/R-bioconductor/lib64/R/lib/libRblas.so
LAPACK: /projects/builder-group/jpg/R-bioconductor/lib64/R/lib/libRlapack.so
locale:
[1] C
attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets
[8] methods   base
other attached packages:
 [1] GO.db_3.5.0           org.Hs.eg.db_3.5.0    BiocInstaller_1.28.0
 [4] AnnotationDbi_1.40.0  IRanges_2.12.0        S4Vectors_0.16.0
 [7] Biobase_2.38.0        BiocGenerics_0.24.0   clusterProfiler_3.6.0
[10] DOSE_3.4.0            edgeR_3.20.3          limma_3.34.5

clusterprofiler org.hs.eg.db • 1.8k views

ADD COMMENT • link updated 6.4 years ago by Guangchuang Yu ★ 1.2k • written 6.4 years ago by scanchi • 0

score 0 · Answer 1 · 2017-12-28

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Entering edit mode

Guangchuang Yu ★ 1.2k

@guangchuang-yu-5419

Last seen 6 days ago

China/Guangzhou/Southern Medical Univer…

r$> clusterProfiler::go2term('GO:0061919')
       go_id                                   Term
1 GO:0061919 process utilizing autophagic mechanism

r$> bitr('GO:0006914', fromType = "GO", toType='ENTREZID', OrgDb='org.Hs.eg.db') -> id
'select()' returned 1:many mapping between keys and columns

r$> x = enrichGO(id$ENTREZID, OrgDb = 'org.Hs.eg.db', ont='BP')

r$> head(x[, 1:2], 3)
                   ID                            Description
GO:0006914 GO:0006914                              autophagy
GO:0061919 GO:0061919 process utilizing autophagic mechanism
GO:0010506 GO:0010506                regulation of autophagy

I can't reproduce your issue. Can you the guide and present a reproducible example?

ADD COMMENT • link 6.4 years ago Guangchuang Yu ★ 1.2k

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Entering edit mode

Thank you for the quick response. Here is the minimal list and code that can reproduce the problem albeit in a different GO term. I apologize for the long list.

dput(condition.control_dge_subset)
structure(list(ENTREZID = c("10051", "10052", "100526820", "100527963",
"10056", "10057", "10059", "1006", "100628315", "100652929",
"10066", "1007", "10072", "10073", "10076", "100775104", "10079",
"1008", "100846978", "10085", "10086", "100862662", "100862671",
"100874047", "100874058", "100874198", "100874251", "100885776",
"100885848", "100887750", "1009", "10093", "10094", "10095",
"10097", "10098", "100996251", "100996385", "100996571", "100996717",
"10102", "10106", "101060200", "101060684", "10109", "10116",
"1012", "10120", "10121", "10123", "10125", "10126", "10128",
"10129", "10131", "10140", "101410534", "10142", "10146", "10147",
"10149", "10152", "10154", "10156", "10159", "1016", "10163",
"10169", "1017", "10174", "10175", "10179", "10180", "10181",
"10188", "10189", "1019", "10190", "101926892", "101926964",
"101927111", "101927150", "101927151", "101927257", "101927314",
"101927356", "101927487", "101927532", "101927550", "101927580",
"101927599", "101927692", "101927745", "101927751", "101927768",
"101927832", "101927924", "101927973", "101928053", "101928069",
"101928079"), SYMBOL = c("SMC4", "GJC1", "CAHM", "PMF1-BGLAP",
"FARSB", "ABCC5", "DNM1L", "CDH8", "DNM3OS", "LINC02078", "SCAMP2",
"CDH9", "DPP3", "SNUPN", "PTPRU", "KLHL7-AS1", "ATP9A", "CDH10",
"LINC00506", "EDIL3", "HHLA1", "ALDH1L1-AS2", "TMEM265", "LINC00499",
"COX10-AS1", "SHANK2-AS1", "KIRREL3-AS2", "UGDH-AS1", "PTGES3L",
"MRPS31P5", "CDH11", "ARPC4", "ARPC3", "ARPC1B", "ACTR2", "TSPAN5",
"LOC100996251", "LOC100996385", "CYYR1-AS1", "LOC100996717",
"TSFM", "CTDSP2", "ZNF891", "NBPF26", "ARPC2", "FEM1B", "CDH13",
"ACTR1B", "ACTR1A", "ARL4C", "RASGRP1", "DNAL4", "LRPPRC", "FRY",
"TRAP1", "TOB1", "DLGAP1-AS4", "AKAP9", "G3BP1", "SUGP2", "ADGRG2",
"ABI2", "PLXNC1", "RASA4", "ATP6AP2", "CDH18", "WASF2", "SERF2",
"CDK2", "SORBS3", "CNIH1", "RBM7", "RBM6", "RBM5", "TNK2", "ALYREF",
"CDK4", "TXNDC9", "LOC101926892", "LOC101926964", "SUCLG2-AS1",
"L3MBTL4-AS1", "LOC101927151", "LOC101927257", "LOC101927314",
"LOC101927356", "LINC01609", "LINC01736", "LOC101927550", "LINC02141",
"ZNF529-AS1", "LOC101927692", "LOC101927745", "LOC101927751",
"HDAC2-AS2", "PAQR9-AS1", "LINC01856", "LINC01695", "LOC101928053",
"LOC101928069", "SLC44A3-AS1")), .Names = c("ENTREZID", "SYMBOL"
), row.names = c(NA, -101L), class = "data.frame")

ADD REPLY • link 6.4 years ago scanchi • 0

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Entering edit mode

##The code with the error.
condition.control_dge_subset_ego=enrichGO(condition.control_dge_subset$ENTREZID,
'org.Hs.eg.db',ont="BP",pvalueCutoff=0.05,pAdjustMethod="BH")
head(condition.control_dge_subset_ego)

                 ID                                          Description
GO:0034314 GO:0034314             Arp2/3 complex-mediated actin nucleation
GO:0045010 GO:0045010                                     actin nucleation
GO:0030838 GO:0030838 positive regulation of actin filament polymerization
GO:0110053 GO:0110053                                                 <NA>
GO:0032970 GO:0032970           regulation of actin filament-based process
GO:0051258 GO:0051258                               protein polymerization
           GeneRatio   BgRatio       pvalue     p.adjust       qvalue
GO:0034314      6/57  36/17381 1.712962e-09 1.733517e-06 1.548878e-06
GO:0045010      6/57  48/17381 1.047071e-08 5.298179e-06 4.733863e-06
GO:0030838      6/57  91/17381 5.103713e-07 1.721653e-04 1.538277e-04
GO:0110053      8/57 234/17381 8.964054e-07 2.267906e-04 2.026348e-04
GO:0032970      9/57 338/17381 1.414596e-06 2.350575e-04 2.100212e-04
GO:0051258      8/57 249/17381 1.429376e-06 2.350575e-04 2.100212e-04

ADD REPLY • link 6.4 years ago scanchi • 0

score 0 · Answer 2 · 2017-12-28

0

Entering edit mode

Guangchuang Yu ★ 1.2k

@guangchuang-yu-5419

Last seen 6 days ago

China/Guangzhou/Southern Medical Univer…

> ENTREZID = c("10051", "10052", "100526820", "100527963",
+ "10056", "10057", "10059", "1006", "100628315", "100652929",
+ "10066", "1007", "10072", "10073", "10076", "100775104", "10079",
+ "1008", "100846978", "10085", "10086", "100862662", "100862671",
+ "100874047", "100874058", "100874198", "100874251", "100885776",
+ "100885848", "100887750", "1009", "10093", "10094", "10095",
+ "10097", "10098", "100996251", "100996385", "100996571", "100996717",
+ "10102", "10106", "101060200", "101060684", "10109", "10116",
+ "1012", "10120", "10121", "10123", "10125", "10126", "10128",
+ "10129", "10131", "10140", "101410534", "10142", "10146", "10147",
+ "10149", "10152", "10154", "10156", "10159", "1016", "10163",
+ "10169", "1017", "10174", "10175", "10179", "10180", "10181",
+ "10188", "10189", "1019", "10190", "101926892", "101926964",
+ "101927111", "101927150", "101927151", "101927257", "101927314",
+ "101927356", "101927487", "101927532", "101927550", "101927580",
+ "101927599", "101927692", "101927745", "101927751", "101927768",
+ "101927832", "101927924", "101927973", "101928053", "101928069",
+ "101928079")
> x = enrichGO(ENTREZID, OrgDb = 'org.Hs.eg.db', ont='BP')
> x$Description %>% is.na %>% sum
[1] 0

still can't reproduce your issue.

ADD COMMENT • link 6.4 years ago Guangchuang Yu ★ 1.2k

0

Entering edit mode

I am not sure what I could be doing wrong. I have not had any issues previously working with this package. The only difference between the last time and present is that I updated the bioconductor packages to the current version (3.6.0). Is there a way to remove the 'NA' terms when plotting with dotplot? Or to remove rows with NA in the 'enrichResult' object ? Here is the entire sessionInfo if it helps.

sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS release 6.6 (Final)

Matrix products: default
BLAS: /projects/builder-group/jpg/R-bioconductor/lib64/R/lib/libRblas.so
LAPACK: /projects/builder-group/jpg/R-bioconductor/lib64/R/lib/libRlapack.so

locale:
[1] C

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets
[8] methods   base

other attached packages:
 [1] edgeR_3.20.3          limma_3.34.5          clusterProfiler_3.6.0
 [4] DOSE_3.4.0            org.Hs.eg.db_3.5.0    AnnotationDbi_1.40.0
 [7] IRanges_2.12.0        S4Vectors_0.16.0      Biobase_2.38.0
[10] BiocGenerics_0.24.0

loaded via a namespace (and not attached):
 [1] bitops_1.0-6               matrixStats_0.52.2
 [3] bit64_0.9-7                RColorBrewer_1.1-2
 [5] httr_1.3.1                 GenomeInfoDb_1.14.0
 [7] tools_3.4.0                backports_1.1.2
 [9] R6_2.2.2                   rpart_4.1-11
[11] Hmisc_4.0-3                DBI_0.7
[13] lazyeval_0.2.1             colorspace_1.3-2
[15] nnet_7.3-12                graphite_1.24.1
[17] gridExtra_2.3              DESeq2_1.18.1
[19] compiler_3.4.0             bit_1.1-12
[21] graph_1.56.0               htmlTable_1.11.0
[23] DelayedArray_0.4.1         scales_0.5.0
[25] checkmate_1.8.5            genefilter_1.60.0
[27] rappdirs_0.3.1             stringr_1.2.0
[29] digest_0.6.13              foreign_0.8-69
[31] XVector_0.18.0             base64enc_0.1-3
[33] pkgconfig_2.0.1            htmltools_0.3.6
[35] htmlwidgets_0.9            rlang_0.1.6
[37] rstudioapi_0.7             RSQLite_2.0
[39] bindr_0.1                  BiocParallel_1.12.0
[41] acepack_1.4.1              GOSemSim_2.4.0
[43] dplyr_0.7.4                RCurl_1.95-4.9
[45] magrittr_1.5               GO.db_3.5.0
[47] GenomeInfoDbData_1.0.0     Formula_1.2-2
[49] Matrix_1.2-12              Rcpp_0.12.14
[51] munsell_0.4.3              stringi_1.1.6
[53] SummarizedExperiment_1.8.1 zlibbioc_1.24.0
[55] plyr_1.8.4                 qvalue_2.10.0
[57] grid_3.4.0                 blob_1.1.0
[59] DO.db_2.9                  lattice_0.20-35
[61] splines_3.4.0              annotate_1.56.1
[63] locfit_1.5-9.1             knitr_1.17
[65] pillar_1.0.1               fgsea_1.4.0
[67] igraph_1.1.2               GenomicRanges_1.30.1
[69] geneplotter_1.56.0         reshape2_1.4.3
[71] fastmatch_1.1-0            XML_3.98-1.9
[73] glue_1.2.0                 latticeExtra_0.6-28
[75] data.table_1.10.4-3        gtable_0.2.0
[77] purrr_0.2.4                tidyr_0.7.2
[79] assertthat_0.2.0           ggplot2_2.2.1
[81] ReactomePA_1.22.0          xtable_1.8-2
[83] reactome.db_1.62.0         survival_2.41-3
[85] tibble_1.4.1               rvcheck_0.0.9
[87] memoise_1.1.0              bindrcpp_0.2
[89] cluster_2.0.6

ADD REPLY • link 6.4 years ago scanchi • 0