cnetplot 'Error in UseMethod("rescale")'

[Hofphi]

Hi,

I was trying to reproduce the following code:
library(DOSE)
data(geneList)
de <- names(geneList)[1:100]
x <- enrichDO(de)
x2 <- pairwise_termsim(x)
cnetplot(x2)

However, I am not able to generate the plot. I am getting this error message:
Error in UseMethod("rescale") : no applicable method for 'rescale' applied to an object of class "AsIs"

I can not figure out a solution. Any help would be appreciated.

---

Here is my session_Info():

R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.2 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0

locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=de_DE.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=de_DE.UTF-8
[6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=de_DE.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C

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

other attached packages:
[1] ggnewscale_0.4.9 enrichplot_1.14.2 scales_1.2.1 org.Hs.eg.db_3.14.0 AnnotationDbi_1.56.2 IRanges_2.28.0 S4Vectors_0.32.4
[8] Biobase_2.54.0 BiocGenerics_0.40.0 DOSE_3.20.1 clusterProfiler_4.2.2 dplyr_1.1.2 readxl_1.4.2

loaded via a namespace (and not attached):
[1] nlme_3.1-162 bitops_1.0-7 ggtree_3.2.1 bit64_4.0.5 RColorBrewer_1.1-3 httr_1.4.6
[7] GenomeInfoDb_1.30.1 tools_4.1.2 utf8_1.2.3 R6_2.5.1 lazyeval_0.2.2 DBI_1.1.3
[13] colorspace_2.1-0 withr_2.5.0 tidyselect_1.2.0 gridExtra_2.3 bit_4.0.5 compiler_4.1.2
[19] cli_3.6.1 scatterpie_0.2.0 labeling_0.4.2 shadowtext_0.1.2 stringr_1.5.0 digest_0.6.31
[25] yulab.utils_0.0.6 ggupset_0.3.0 XVector_0.34.0 pkgconfig_2.0.3 fastmap_1.1.1 rlang_1.1.1
[31] rstudioapi_0.14 RSQLite_2.3.1 gridGraphics_0.5-1 farver_2.1.1 generics_0.1.3 jsonlite_1.8.4
[37] BiocParallel_1.28.3 GOSemSim_2.20.0 RCurl_1.98-1.12 magrittr_2.0.3 ggplotify_0.1.0 GO.db_3.14.0
[43] GenomeInfoDbData_1.2.7 patchwork_1.1.2 Matrix_1.5-4.1 Rcpp_1.0.10 munsell_0.5.0 fansi_1.0.4
[49] ape_5.7-1 viridis_0.6.3 lifecycle_1.0.3 stringi_1.7.12 ggraph_2.1.0 MASS_7.3-60
[55] zlibbioc_1.40.0 plyr_1.8.8 qvalue_2.26.0 grid_4.1.2 blob_1.2.4 parallel_4.1.2
[61] ggrepel_0.9.3 DO.db_2.9 crayon_1.5.2 lattice_0.21-8 graphlayouts_1.0.0 Biostrings_2.62.0
[67] splines_4.1.2 KEGGREST_1.34.0 pillar_1.9.0 fgsea_1.20.0 igraph_1.4.3 reshape2_1.4.4
[73] fastmatch_1.1-3 glue_1.6.2 ggfun_0.0.9 downloader_0.4 BiocManager_1.30.20 data.table_1.14.8
[79] treeio_1.18.1 png_0.1-8 vctrs_0.6.2 tweenr_2.0.2 cellranger_1.1.0 gtable_0.3.3
[85] purrr_1.0.1 polyclip_1.10-4 tidyr_1.3.0 cachem_1.0.8 ggplot2_3.4.2 ggforce_0.4.1
[91] tidygraph_1.2.3 tidytree_0.4.2 viridisLite_0.4.2 tibble_3.2.1 aplot_0.1.10 memoise_2.0.1

[huerqiang]

Please use the lastest version of clusterProfiler and enrichplot.

[guidohooiveld]

> library(DOSE)
> library(clusterProfiler)
> library(enrichplot)
> library(GOSemSim)
> 
> data(geneList)
> de <- names(geneList)[1:100]
> x <- enrichDO(de)
> x2 <- pairwise_termsim(x)
> cnetplot(x2)
> 

> sessionInfo()
R version 4.3.0 (2023-04-21 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: Europe/Amsterdam
tzcode source: internal

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

other attached packages:
[1] GOSemSim_2.26.1       enrichplot_1.20.0     clusterProfiler_4.8.2
[4] DOSE_3.26.1          

loaded via a namespace (and not attached):
  [1] DBI_1.1.3               bitops_1.0-7            gson_0.1.0             
  [4] shadowtext_0.1.2        gridExtra_2.3           rlang_1.1.1            
  [7] magrittr_2.0.3          compiler_4.3.0          RSQLite_2.3.1          
 [10] png_0.1-8               vctrs_0.6.3             reshape2_1.4.4         
 [13] stringr_1.5.0           pkgconfig_2.0.3         crayon_1.5.2           
 [16] fastmap_1.1.1           XVector_0.40.0          labeling_0.4.2         
 [19] ggraph_2.1.0            utf8_1.2.3              HDO.db_0.99.1          
 [22] purrr_1.0.2             bit_4.0.5               zlibbioc_1.46.0        
 [25] cachem_1.0.8            aplot_0.2.0             GenomeInfoDb_1.36.1    
 [28] jsonlite_1.8.7          blob_1.2.4              BiocParallel_1.34.2    
 [31] tweenr_2.0.2            parallel_4.3.0          R6_2.5.1               
 [34] stringi_1.7.12          RColorBrewer_1.1-3      Rcpp_1.0.11            
 [37] downloader_0.4          IRanges_2.34.1          Matrix_1.6-1           
 [40] splines_4.3.0           igraph_1.5.1            tidyselect_1.2.0       
 [43] qvalue_2.32.0           viridis_0.6.4           codetools_0.2-19       
 [46] lattice_0.21-8          tibble_3.2.1            plyr_1.8.8             
 [49] Biobase_2.60.0          treeio_1.24.3           withr_2.5.0            
 [52] KEGGREST_1.40.0         gridGraphics_0.5-1      scatterpie_0.2.1       
 [55] polyclip_1.10-4         Biostrings_2.68.1       pillar_1.9.0           
 [58] ggtree_3.8.2            stats4_4.3.0            ggfun_0.1.2            
 [61] generics_0.1.3          RCurl_1.98-1.12         S4Vectors_0.38.1       
 [64] ggplot2_3.4.3           munsell_0.5.0           scales_1.2.1           
 [67] tidytree_0.4.5          glue_1.6.2              lazyeval_0.2.2         
 [70] tools_4.3.0             data.table_1.14.8       fgsea_1.26.0           
 [73] graphlayouts_1.0.0      fastmatch_1.1-3         tidygraph_1.2.3        
 [76] cowplot_1.1.1           grid_4.3.0              tidyr_1.3.0            
 [79] ape_5.7-1               AnnotationDbi_1.62.2    colorspace_2.1-0       
 [82] nlme_3.1-163            GenomeInfoDbData_1.2.10 patchwork_1.1.3        
 [85] ggforce_0.4.1           cli_3.6.1               fansi_1.0.4            
 [88] viridisLite_0.4.2       dplyr_1.1.2             gtable_0.3.3           
 [91] yulab.utils_0.0.7       digest_0.6.33           BiocGenerics_0.46.0    
 [94] ggrepel_0.9.3           ggplotify_0.1.2         farver_2.1.1           
 [97] memoise_2.0.1           lifecycle_1.0.3         httr_1.4.7             
[100] GO.db_3.17.0            bit64_4.0.5             MASS_7.3-60            
>