Hello!
I work with a Nothobranchius furzeri transcriptome data and want to do the GO enriched pathway analysis using the clusterProfiler R package. I started with the command 'searchkeggorganism'. The documentation (https://www.rdocumentation.org/packages/clusterProfiler/versions/3.0.4/topics/searchkeggorganism) says that this function searches directly in the KEGG catalogue (https://www.genome.jp/kegg/catalog/org_list.html), where Nothobranchius furzeri is present and has a code 'nfu'. However,
search_kegg_organism('nfu', by='kegg_code')
didn't work. The output was:
> search_kegg_organism('nfu', by='kegg_code')
[1] kegg_code scientific_name common_name
<0 rows> (or 0-length row.names)
I tried it with other species, and found out that it finds many organisms (e.g. 'mmu', 'dre'), and doesn't find many other organisms (e.g. 'malb', 'els').
What can I do about it? And does it mean that the package will not work with my species in general?
I would really appreciate if you could help me.
As it is advised, I am attaching the sessionInfo() output:
sessionInfo() R version 3.6.2 (2019-12-12) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 18362)
Matrix products: default
locale: [1] LCCOLLATE=EnglishBelgium.1252 LCCTYPE=EnglishBelgium.1252 LCMONETARY=EnglishBelgium.1252 [4] LCNUMERIC=C LCTIME=English_Belgium.1252
attached base packages: [1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] clusterProfiler3.14.3 rtracklayer1.46.0 GenomicRanges1.38.0 GenomeInfoDb1.22.0
[5] IRanges2.20.2 S4Vectors0.24.3 BiocGenerics0.32.0 goseq1.38.0
[9] geneLenDataBase1.22.0 BiasedUrn1.07
loaded via a namespace (and not attached):
[1] nlme3.1-142 bitops1.0-6 matrixStats0.55.0
[4] enrichplot1.6.1 bit640.9-7 RColorBrewer1.1-2
[7] progress1.2.2 httr1.4.1 tools3.6.2
[10] R62.4.1 DBI1.1.0 lazyeval0.2.2
[13] mgcv1.8-31 colorspace1.4-1 tidyselect1.0.0
[16] gridExtra2.3 prettyunits1.1.1 bit1.1-15.1
[19] curl4.3 compiler3.6.2 Biobase2.46.0
[22] xml21.2.2 DelayedArray0.12.2 triebeard0.3.0
[25] scales1.1.0 ggridges0.5.2 askpass1.1
[28] rappdirs0.3.1 stringr1.4.0 digest0.6.23
[31] Rsamtools2.2.1 DOSE3.12.0 XVector0.26.0
[34] pkgconfig2.0.3 dbplyr1.4.2 rlang0.4.3
[37] rstudioapi0.10 RSQLite2.2.0 gridGraphics0.4-1
[40] farver2.0.3 jsonlite1.6 BiocParallel1.20.1
[43] GOSemSim2.12.0 dplyr0.8.4 RCurl1.98-1.1
[46] magrittr1.5 ggplotify0.0.4 GO.db3.10.0
[49] GenomeInfoDbData1.2.2 Matrix1.2-18 Rcpp1.0.3
[52] munsell0.5.0 viridis0.5.1 lifecycle0.1.0
[55] stringi1.4.5 ggraph2.0.0 MASS7.3-51.5
[58] SummarizedExperiment1.16.1 zlibbioc1.32.0 plyr1.8.5
[61] qvalue2.18.0 BiocFileCache1.10.2 grid3.6.2
[64] blob1.2.1 ggrepel0.8.1 DO.db2.9
[67] crayon1.3.4 lattice0.20-38 cowplot1.0.0
[70] graphlayouts0.5.0 Biostrings2.54.0 splines3.6.2
[73] GenomicFeatures1.38.1 hms0.5.3 pillar1.4.3
[76] fgsea1.12.0 igraph1.2.4.2 reshape21.4.3
[79] biomaRt2.42.0 fastmatch1.1-0 XML3.99-0.3
[82] glue1.3.1 BiocManager1.30.10 data.table1.12.8
[85] urltools1.7.3 tweenr1.0.1 vctrs0.2.2
[88] polyclip1.10-0 gtable0.3.0 openssl1.4.1
[91] purrr0.3.3 tidyr1.0.2 assertthat0.2.1
[94] ggplot23.2.1 ggforce0.3.1 europepmc0.3
[97] tidygraph1.1.2 viridisLite0.3.0 tibble2.1.3
[100] rvcheck0.1.7 GenomicAlignments1.22.1 AnnotationDbi1.48.0
[103] memoise_1.1.0
Cross-posted: https://www.biostars.org/p/419692/