Treeplot displaying incorrect simplified terms if nCluster is increased

[TJonCooper]

If nCluster is set to = 5 (as default), treeplot behaves as expected:

However, if nCluster is increased to 10 or higher, treeplot now misassigns both the cluster colour and the simplified label:

Notice how, for example, the group containing 'hemostasis, blood coagulation, platelet activation' etc. is blue in font colour, but has been assigned to the purple cluster.

This happens with any data - including the example datasets included in clusterProfiler.

R version 4.1.3 (2022-03-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

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

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

other attached packages:
[1] enrichplot_1.15.3     org.Hs.eg.db_3.13.0   AnnotationDbi_1.56.2  IRanges_2.28.0        S4Vectors_0.32.3      Biobase_2.54.0       
[7] BiocGenerics_0.40.0   clusterProfiler_4.3.3

loaded via a namespace (and not attached):
 [1] nlme_3.1-155           bitops_1.0-7           ggtree_3.2.1           bit64_4.0.5            RColorBrewer_1.1-2     httr_1.4.2            
 [7] GenomeInfoDb_1.30.1    tools_4.1.3            utf8_1.2.2             R6_2.5.1               lazyeval_0.2.2         DBI_1.1.2             
[13] colorspace_2.0-3       tidyselect_1.1.2       gridExtra_2.3          bit_4.0.4              compiler_4.1.3         cli_3.2.0             
[19] scatterpie_0.1.7       labeling_0.4.2         shadowtext_0.1.1       scales_1.1.1           yulab.utils_0.0.4      stringr_1.4.0         
[25] digest_0.6.29          DOSE_3.20.1            XVector_0.34.0         pkgconfig_2.0.3        fastmap_1.1.0          rlang_1.0.2           
[31] rstudioapi_0.13        RSQLite_2.2.10         gridGraphics_0.5-1     generics_0.1.2         farver_2.1.0           jsonlite_1.8.0        
[37] BiocParallel_1.28.3    GOSemSim_2.20.0        dplyr_1.0.8            RCurl_1.98-1.6         magrittr_2.0.2         ggplotify_0.1.0       
[43] GO.db_3.14.0           GenomeInfoDbData_1.2.7 patchwork_1.1.1        Matrix_1.4-0           Rcpp_1.0.8.3           munsell_0.5.0         
[49] fansi_1.0.2            ggnewscale_0.4.6       ape_5.6-2              viridis_0.6.2          lifecycle_1.0.1        stringi_1.7.6         
[55] ggraph_2.0.5           MASS_7.3-55            zlibbioc_1.40.0        plyr_1.8.6             qvalue_2.26.0          grid_4.1.3            
[61] blob_1.2.2             parallel_4.1.3         ggrepel_0.9.1          DO.db_2.9              crayon_1.5.0           lattice_0.20-45       
[67] graphlayouts_0.8.0     Biostrings_2.62.0      splines_4.1.3          KEGGREST_1.34.0        pillar_1.7.0           fgsea_1.20.0          
[73] igraph_1.2.11          reshape2_1.4.4         fastmatch_1.1-3        glue_1.6.2             ggfun_0.0.5            downloader_0.4        
[79] data.table_1.14.2      treeio_1.18.1          png_0.1-7              vctrs_0.3.8            tweenr_1.0.2           gtable_0.3.0          
[85] purrr_0.3.4            polyclip_1.10-0        tidyr_1.2.0            assertthat_0.2.1       cachem_1.0.6           ggplot2_3.3.5         
[91] ggforce_0.3.3          tidygraph_1.2.0        tidytree_0.3.9         viridisLite_0.4.0      tibble_3.1.6           aplot_0.1.2           
[97] memoise_2.0.1          ellipsis_0.3.2      

[SDU-LST]

I have the same problem!!!!

[CyrusWang57]

Same issue is not fixed...