compareCluster dotplot: how to modify the genesets order

[luciechanvillard]

Hello,

I am using the compareCluster function of clusterProfiler to do GSEA, and I then plot the results with the dotplot function of enrichplot.

While most of the parameters of the dotplot remain the same if you input a gseaResult or a compareClusterResult, the arguments "groupBy" and "decreasing" do not exist and the argument "by" does not seem to work.

In the following example I am trying to order the genesets by the NES value.

dotplot(
  result_gsea_mitocarta,
  x = "NES",
  color = "p.adjust",
  showCategory = 8,
  split = "Cluster",
  font.size = 12,
  title = "",
  by = "NES",
  size = "Count",
  includeAll = TRUE,
  label_format = 30
) +
  facet_grid(. ~ Cluster) +
  geom_vline(xintercept = 0, linetype = "dotted", color = "#444444", size = 1) +
  scale_x_continuous(limit = c(-3.5, 3.5), breaks = seq(-4, 4, 1))


sessionInfo( )
R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale:
[1] LC_COLLATE=French_Switzerland.utf8  LC_CTYPE=French_Switzerland.utf8    LC_MONETARY=French_Switzerland.utf8 LC_NUMERIC=C                       
[5] LC_TIME=French_Switzerland.utf8    

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

other attached packages:
 [1] RColorBrewer_1.1-3     Rtsne_0.17             umap_0.2.10.0          plotly_4.10.4          factoextra_1.0.7       FactoMineR_2.10        EnhancedVolcano_1.16.0
 [8] ggrepel_0.9.5          msigdbr_7.5.1          org.Hs.eg.db_3.16.0    AnnotationDbi_1.60.2   IRanges_2.32.0         S4Vectors_0.36.2       clusterProfiler_4.6.2 
[15] pheatmap_1.0.12        ggforce_0.4.2          tidytree_0.4.6         lubridate_1.9.3        forcats_1.0.0          stringr_1.5.1          purrr_1.0.1           
[22] readr_2.1.5            tidyr_1.3.1            tibble_3.2.1           tidyverse_2.0.0        readxl_1.4.3           CellChat_2.1.2         Biobase_2.58.0        
[29] BiocGenerics_0.44.0    ggplot2_3.5.0.9000     igraph_2.0.2           dplyr_1.1.4           

loaded via a namespace (and not attached):
  [1] estimability_1.4.1     R.methodsS3_1.8.2      coda_0.19-4.1          bit64_4.0.5            R.utils_2.12.3         irlba_2.3.5.1          styler_1.10.2         
  [8] data.table_1.14.8      KEGGREST_1.38.0        RCurl_1.98-1.12        doParallel_1.0.17      generics_0.1.3         snow_0.4-4             callr_3.7.5           
 [15] cowplot_1.1.3          usethis_2.2.3          RSQLite_2.3.1          shadowtext_0.1.3       future_1.33.1          bit_4.0.5              tzdb_0.4.0            
 [22] enrichplot_1.23.1.992  httpuv_1.6.14          viridis_0.6.5          hms_1.1.3              jquerylib_0.1.4        babelgene_22.9         promises_1.2.1        
 [29] fansi_1.0.3            DBI_1.2.2              htmlwidgets_1.6.4      ellipsis_0.3.2         RSpectra_0.16-1        ggnewscale_0.4.10      ggpubr_0.6.0          
 [36] backports_1.4.1        gridBase_0.4-7         vctrs_0.6.4            ggalluvial_0.12.5      remotes_2.4.2.1        abind_1.4-5            cachem_1.0.8          
 [43] withr_3.0.0            HDO.db_0.99.1          presto_1.0.0           emmeans_1.10.0         sna_2.7-2              treeio_1.22.0          svglite_2.1.3         
 [50] cluster_2.1.6          DOSE_3.24.2            ape_5.7-1              lazyeval_0.2.2         crayon_1.5.2           labeling_0.4.3         pkgconfig_2.0.3       
 [57] tweenr_2.0.3           GenomeInfoDb_1.34.9    nlme_3.1-164           pkgload_1.3.4          devtools_2.4.5         rlang_1.1.3            globals_0.16.2        
 [64] lifecycle_1.0.4        miniUI_0.1.1.1         downloader_0.4         registry_0.5-1         cellranger_1.1.0       polyclip_1.10-6        matrixStats_1.2.0     
 [71] rngtools_1.5.2         Matrix_1.6-3           aplot_0.2.2            carData_3.0-5          GlobalOptions_0.1.2    processx_3.8.3         png_0.1-8             
 [78] viridisLite_0.4.2      rjson_0.2.21           bitops_1.0-7           R.oo_1.26.0            gson_0.1.0             ggnetwork_0.5.13       Biostrings_2.66.0     
 [85] blob_1.2.4             shape_1.4.6.1          multcompView_0.1-9     qvalue_2.30.0          parallelly_1.37.1      R.cache_0.16.0         rstatix_0.7.2         
 [92] gridGraphics_0.5-1     ggsignif_0.6.4         scales_1.3.0           leaps_3.1              memoise_2.0.1          magrittr_2.0.3         plyr_1.8.9            
 [99] zlibbioc_1.44.0        compiler_4.2.2         scatterpie_0.2.1       clue_0.3-65            cli_3.6.0              XVector_0.38.0         urlchecker_1.0.1      
[106] listenv_0.9.1          patchwork_1.2.0        pbapply_1.7-2          ps_1.7.6               MASS_7.3-60.0.1        tidyselect_1.2.0       stringi_1.8.2         
[113] GOSemSim_2.24.0        askpass_1.2.0          grid_4.2.2             sass_0.4.8             fastmatch_1.1-4        tools_4.2.2            timechange_0.3.0      
[120] future.apply_1.11.1    parallel_4.2.2         circlize_0.4.16        rstudioapi_0.15.0      foreach_1.5.2          gridExtra_2.3          scatterplot3d_0.3-44  
[127] farver_2.1.1           ggraph_2.2.0           digest_0.6.34          FNN_1.1.4              shiny_1.8.0            Rcpp_1.0.11            car_3.1-2             
[134] broom_1.0.5            later_1.3.2            httr_1.4.7             ComplexHeatmap_2.15.4  colorspace_2.1-0       fs_1.6.3               reticulate_1.35.0     
[141] splines_4.2.2          yulab.utils_0.1.4      graphlayouts_1.1.0     ggplotify_0.1.2        sessioninfo_1.2.2      systemfonts_1.0.5      xtable_1.8-4          
[148] jsonlite_1.8.8         ggtree_3.6.2           tidygraph_1.3.1        flashClust_1.01-2      ggfun_0.1.4            R6_2.5.1               profvis_0.3.8         
[155] pillar_1.9.0           htmltools_0.5.7        mime_0.12              NMF_0.27               DT_0.32                glue_1.6.2             fastmap_1.1.1         
[162] BiocParallel_1.32.6    BiocNeighbors_1.16.0   codetools_0.2-19       fgsea_1.24.0           mvtnorm_1.2-4          pkgbuild_1.4.3         utf8_1.2.2            
[169] lattice_0.20-45        bslib_0.6.1            network_1.18.2         curl_5.2.1             GO.db_3.16.0           openssl_2.1.1          statnet.common_4.9.0  
[176] desc_1.4.3             munsell_0.5.0          GetoptLong_1.0.5       GenomeInfoDbData_1.2.9 iterators_1.0.14       reshape2_1.4.4         gtable_0.3.4    

And I get the the following plot:

Any idea on how to change the order of the genesets?

Thanks a lot for the help

Lucie

[guidohooiveld]

Cross-posted: https://support.bioconductor.org/p/9157602/