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compareCluster dotplot: how to modify the genesets order
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