plot_median = TRUE does not work in VlnPlot_scCustom when features contains more than one gene · Issue #169 · samuel-marsh/scCustomize (original) (raw)
Hello,
Thanks for all your amazing work!
Everything is in the title. Actually, plot_median = TRUE works but only for the last gene...
Here is a minimal example:
library(Seurat) library(SeuratData) library(scCustomize)
data("pbmc3k") pbmc3k = UpdateSeuratObject(pbmc3k)
pbmc3k = NormalizeData(object = pbmc3k) pbmc3k = FindVariableFeatures(object = pbmc3k) pbmc3k = ScaleData(object = pbmc3k) pbmc3k = RunPCA(object = pbmc3k) pbmc3k = RunUMAP(object = pbmc3k, dims = 1:20) pbmc3k = FindNeighbors(object = pbmc3k, dims = 1:20) pbmc3k = FindClusters(object = pbmc3k, resolution = 0.50)
DimPlot_scCustom(seurat_object = pbmc3k, group.by = "seurat_clusters")
The following code works if only one gene is in feature =
FeaturePlot_scCustom(seurat_object = pbmc3k, features = "GAPDH") / VlnPlot_scCustom(seurat_object = pbmc3k, group.by = "seurat_clusters", features = "GAPDH", plot_median = TRUE) & NoLegend()
But the following codes do not work if several genes are in feature =
FeaturePlot_scCustom(seurat_object = pbmc3k, features = c("GAPDH", "VIM"), num_columns = 2) / VlnPlot_scCustom(seurat_object = pbmc3k, group.by = "seurat_clusters", features = c("GAPDH", "VIM"), plot_median = TRUE, num_columns = 2)
FeaturePlot_scCustom(seurat_object = pbmc3k, features = c("GAPDH", "VIM", "RPS18"), num_columns = 3) / VlnPlot_scCustom(seurat_object = pbmc3k, group.by = "seurat_clusters", features = c("GAPDH", "VIM", "RPS18"), plot_median = TRUE, num_columns = 3)
I tried these codes, but it didn't work... Plus, using these codes, I don't see any median at all in the plots, and no warning in the console.
FeaturePlot_scCustom(seurat_object = pbmc3k, features = c("GAPDH", "VIM"), num_columns = 2) / VlnPlot_scCustom(seurat_object = pbmc3k, group.by = "seurat_clusters", features = c("GAPDH", "VIM"), plot_median = c(TRUE, TRUE), num_columns = 2)
FeaturePlot_scCustom(seurat_object = pbmc3k, features = c("GAPDH", "VIM"), num_columns = 2) / VlnPlot_scCustom(seurat_object = pbmc3k, group.by = "seurat_clusters", features = c("GAPDH", "VIM"), plot_median = list(TRUE, TRUE), num_columns = 2)
Thanks in advance for solving this issue,
Best regards,
sessionInfo() R version 4.3.1 (2023-06-16) Platform: x86_64-apple-darwin20 (64-bit) Running under: macOS Monterey 12.7.4
Matrix products: default BLAS: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRblas.0.dylib LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
locale: [1] C
time zone: Europe/Paris tzcode source: internal
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] scCustomize_2.0.1 pbmc3k.SeuratData_3.1.4 ifnb.SeuratData_3.1.0
[4] SeuratData_0.2.2.9001 Seurat_5.0.1 SeuratObject_5.0.1
[7] sp_2.1-3
loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 jsonlite_1.8.8 shape_1.4.6
[4] magrittr_2.0.3 spatstat.utils_3.0-4 ggbeeswarm_0.7.2
[7] farver_2.1.1 GlobalOptions_0.1.2 vctrs_0.6.5
[10] ROCR_1.0-11 spatstat.explore_3.2-6 paletteer_1.6.0
[13] janitor_2.2.0 htmltools_0.5.7 forcats_1.0.0
[16] sctransform_0.4.1 parallelly_1.36.0 KernSmooth_2.23-22
[19] htmlwidgets_1.6.4 ica_1.0-3 plyr_1.8.9
[22] lubridate_1.9.3 plotly_4.10.4 zoo_1.8-12
[25] igraph_2.0.1.1 mime_0.12 lifecycle_1.0.4
[28] pkgconfig_2.0.3 Matrix_1.6-5 R6_2.5.1
[31] fastmap_1.1.1 snakecase_0.11.1 fitdistrplus_1.1-11
[34] future_1.33.1 shiny_1.8.0 digest_0.6.34
[37] colorspace_2.1-0 rematch2_2.1.2 patchwork_1.2.0
[40] tensor_1.5 RSpectra_0.16-1 irlba_2.3.5.1
[43] labeling_0.4.3 progressr_0.14.0 timechange_0.3.0
[46] fansi_1.0.6 spatstat.sparse_3.0-3 httr_1.4.7
[49] polyclip_1.10-6 abind_1.4-5 compiler_4.3.1
[52] withr_3.0.0 fastDummies_1.7.3 MASS_7.3-60.0.1
[55] rappdirs_0.3.3 tools_4.3.1 vipor_0.4.7
[58] lmtest_0.9-40 beeswarm_0.4.0 httpuv_1.6.14
[61] future.apply_1.11.1 goftest_1.2-3 glue_1.7.0
[64] nlme_3.1-164 promises_1.2.1 grid_4.3.1
[67] Rtsne_0.17 cluster_2.1.6 reshape2_1.4.4
[70] generics_0.1.3 gtable_0.3.4 spatstat.data_3.0-4
[73] tidyr_1.3.1 data.table_1.15.0 utf8_1.2.4
[76] spatstat.geom_3.2-8 RcppAnnoy_0.0.22 ggrepel_0.9.5
[79] RANN_2.6.1 pillar_1.9.0 stringr_1.5.1
[82] spam_2.10-0 RcppHNSW_0.6.0 ggprism_1.0.4
[85] later_1.3.2 circlize_0.4.16 splines_4.3.1
[88] dplyr_1.1.4 lattice_0.22-5 survival_3.5-7
[91] deldir_2.0-2 tidyselect_1.2.0 miniUI_0.1.1.1
[94] pbapply_1.7-2 gridExtra_2.3 scattermore_1.2
[97] matrixStats_1.2.0 stringi_1.8.3 lazyeval_0.2.2
[100] codetools_0.2-19 tibble_3.2.1 cli_3.6.2
[103] uwot_0.1.16 xtable_1.8-4 reticulate_1.35.0
[106] munsell_0.5.0 Rcpp_1.0.12 globals_0.16.2
[109] spatstat.random_3.2-2 png_0.1-8 ggrastr_1.0.2
[112] parallel_4.3.1 ellipsis_0.3.2 ggplot2_3.4.4
[115] dotCall64_1.1-1 listenv_0.9.1 viridisLite_0.4.2
[118] scales_1.3.0 ggridges_0.5.6 leiden_0.4.3.1
[121] purrr_1.0.2 crayon_1.5.2 rlang_1.1.3
[124] cowplot_1.1.3