stacked_vlnplot_seurat
Ehsan.Rz
2022-05-23
library(Seurat)## Attaching SeuratObjectlibrary(SeuratData)## ── Installed datasets ───────────────────────────────────── SeuratData v0.2.2 ──## ✓ ifnb 3.1.0 ✓ pbmcsca 3.0.0
## ✓ panc8 3.0.2## ────────────────────────────────────── Key ─────────────────────────────────────## ✓ Dataset loaded successfully
## > Dataset built with a newer version of Seurat than installed
## ❓ Unknown version of Seurat installedlibrary(SeuratWrappers)
library(SeuratObject)
library(ggplot2)
library(devtools)## Loading required package: usethislibrary(ggpubr)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlastone <- readRDS("/mnt/nectar_volume/home/eraz0001/new/alberto final files/lastone.rds")head(lastone)## orig.ident nCount_RNA nFeature_RNA
## C1L_C1L_AAACCCAAGACCTGGA-1_1_1_1_1 C1L 5447 1683
## C1L_C1L_AAACCCACAATACCCA-1_1_1_1_1 C1L 8203 2268
## C1L_C1L_AAACCCACAGTACTAC-1_1_1_1_1 C1L 3869 1309
## C1L_C1L_AAACCCAGTTATGGTC-1_1_1_1_1 C1L 9335 2557
## C1L_C1L_AAACCCAGTTGAGAGC-1_1_1_1_1 C1L 2544 1060
## C1L_C1L_AAACCCAGTTGCTCAA-1_1_1_1_1 C1L 13549 3026
## C1L_C1L_AAACCCATCAACTCTT-1_1_1_1_1 C1L 6375 1843
## C1L_C1L_AAACGAAAGCTTGTGT-1_1_1_1_1 C1L 2104 953
## C1L_C1L_AAACGAAAGGTGCTAG-1_1_1_1_1 C1L 3107 1218
## C1L_C1L_AAACGAAAGTCCGCCA-1_1_1_1_1 C1L 991 512
## RNA_snn_res.0.8 seurat_clusters nCount_SCT
## C1L_C1L_AAACCCAAGACCTGGA-1_1_1_1_1 6 3 3033
## C1L_C1L_AAACCCACAATACCCA-1_1_1_1_1 11 17 3269
## C1L_C1L_AAACCCACAGTACTAC-1_1_1_1_1 3 4 3257
## C1L_C1L_AAACCCAGTTATGGTC-1_1_1_1_1 2 1 3217
## C1L_C1L_AAACCCAGTTGAGAGC-1_1_1_1_1 4 10 2640
## C1L_C1L_AAACCCAGTTGCTCAA-1_1_1_1_1 3 2 2936
## C1L_C1L_AAACCCATCAACTCTT-1_1_1_1_1 4 6 3018
## C1L_C1L_AAACGAAAGCTTGTGT-1_1_1_1_1 5 5 2844
## C1L_C1L_AAACGAAAGGTGCTAG-1_1_1_1_1 5 11 3063
## C1L_C1L_AAACGAAAGTCCGCCA-1_1_1_1_1 8 0 2271
## nFeature_SCT SCT_snn_res.0.8 percent.mt
## C1L_C1L_AAACCCAAGACCTGGA-1_1_1_1_1 1626 3 0.00000000
## C1L_C1L_AAACCCACAATACCCA-1_1_1_1_1 1826 17 0.00000000
## C1L_C1L_AAACCCACAGTACTAC-1_1_1_1_1 1309 4 0.03944773
## C1L_C1L_AAACCCAGTTATGGTC-1_1_1_1_1 2068 1 0.00000000
## C1L_C1L_AAACCCAGTTGAGAGC-1_1_1_1_1 1060 10 0.00000000
## C1L_C1L_AAACCCAGTTGCTCAA-1_1_1_1_1 1724 2 0.00000000
## C1L_C1L_AAACCCATCAACTCTT-1_1_1_1_1 1578 6 0.00000000
## C1L_C1L_AAACGAAAGCTTGTGT-1_1_1_1_1 952 5 0.04405286
## C1L_C1L_AAACGAAAGGTGCTAG-1_1_1_1_1 1218 11 0.07049700
## C1L_C1L_AAACGAAAGTCCGCCA-1_1_1_1_1 546 0 0.00000000
## nFeature_RNA_MAD nCount_RNA_MAD method
## C1L_C1L_AAACCCAAGACCTGGA-1_1_1_1_1 0.3925254 0.45828981 Chip1
## C1L_C1L_AAACCCACAATACCCA-1_1_1_1_1 0.9813830 0.98712902 Chip1
## C1L_C1L_AAACCCACAGTACTAC-1_1_1_1_1 -0.1035465 0.01646269 Chip1
## C1L_C1L_AAACCCAGTTATGGTC-1_1_1_1_1 1.2181264 1.15409935 Chip1
## C1L_C1L_AAACCCAGTTGAGAGC-1_1_1_1_1 -0.5200306 -0.52506485 Chip1
## C1L_C1L_AAACCCAGTTGCTCAA-1_1_1_1_1 1.5505464 1.63528641 Chip1
## C1L_C1L_AAACCCATCAACTCTT-1_1_1_1_1 0.5717895 0.66148816 Chip1
## C1L_C1L_AAACGAAAGCTTGTGT-1_1_1_1_1 -0.7300729 -0.77034231 Chip1
## C1L_C1L_AAACGAAAGGTGCTAG-1_1_1_1_1 -0.2457732 -0.26684183 Chip1
## C1L_C1L_AAACGAAAGTCCGCCA-1_1_1_1_1 -1.9564436 -1.74278744 Chip1
## group
## C1L_C1L_AAACCCAAGACCTGGA-1_1_1_1_1 Control
## C1L_C1L_AAACCCACAATACCCA-1_1_1_1_1 Control
## C1L_C1L_AAACCCACAGTACTAC-1_1_1_1_1 Control
## C1L_C1L_AAACCCAGTTATGGTC-1_1_1_1_1 Control
## C1L_C1L_AAACCCAGTTGAGAGC-1_1_1_1_1 Control
## C1L_C1L_AAACCCAGTTGCTCAA-1_1_1_1_1 Control
## C1L_C1L_AAACCCATCAACTCTT-1_1_1_1_1 Control
## C1L_C1L_AAACGAAAGCTTGTGT-1_1_1_1_1 Control
## C1L_C1L_AAACGAAAGGTGCTAG-1_1_1_1_1 Control
## C1L_C1L_AAACGAAAGTCCGCCA-1_1_1_1_1 Controlnew.cluster.ids <- c("Chondrocytes", "Hes1+", "PACs", "Pdgfra+", "Adipocytes", "NA1", "Osteoclasts",
"Muscle Cells", "Lepr+", "Muscle Cells", "SSPC", "HTC",
"Chondrocytes", "Muscle Cells", "Osteoblasts", "Chondrocytes",
"Muscle Cells", "Macrophages", "Endothelial Cells", "Macrophages",
"Muscle Cells", "EA-Chondrocytes", "Immuno-Cells", "Fibroblasts",
"Muscle Cells", "MSCs")
names(new.cluster.ids) <- levels(lastone)
lastone <- RenameIdents(lastone, new.cluster.ids)your_font_size <- 15
a <- VlnPlot(lastone, features = 'Col2a1', split.by = 'group', pt.size = 0.0, combine = T, split.plot = T, cols =c("#e31a1c", "#ffda79")) + theme_bw() + theme(legend.title = element_blank()) +
stat_summary(fun = median, fun.min = median, fun.max = median,
geom = "crossbar",
width = 0.6,
position = position_dodge(width = .70)) + xlab("Clusters") + ylab("Gene Expression") + stat_compare_means(aes(label = ifelse(p < 1.e-4, sprintf("p = %2.1e",as.numeric(..p.format..)), sprintf("p = %5.4f", as.numeric(..p.format..)))), method = "wilcox.test", paired = T) + stat_compare_means(size = your_font_size, label = "p.signif")+theme(text = element_text(size = 20, angle = 45))+
guides(fill = guide_legend(override.aes = list(linetype = 0)),
color = guide_legend(override.aes = list(linetype = 0)))## The default behaviour of split.by has changed.
## Separate violin plots are now plotted side-by-side.
## To restore the old behaviour of a single split violin,
## set split.plot = TRUE.
##
## This message will be shown once per session.The most common methods for comparing means include:
t.test() Compare two groups (parametric) wilcox.test() Compare two groups (non-parametric) anova() Compare multiple groups (parametric) kruskal.test() Compare multiple groups (non-parametric)
a## Warning: Computation failed in `stat_compare_means()`:
## Problem while computing `p = purrr::map(...)`.
sessionInfo()## R version 4.0.2 (2020-06-22)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.4 LTS
##
## Matrix products: default
## BLAS: /mnt/nectar_volume/software/apps/R/4.0.2/lib/R/lib/libRblas.so
## LAPACK: /mnt/nectar_volume/software/apps/R/4.0.2/lib/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8
## [5] LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8
## [7] LC_PAPER=en_AU.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] dplyr_1.0.8 ggpubr_0.4.0 devtools_2.4.3
## [4] usethis_2.1.5 ggplot2_3.3.6 SeuratWrappers_0.3.0
## [7] pbmcsca.SeuratData_3.0.0 panc8.SeuratData_3.0.2 ifnb.SeuratData_3.1.0
## [10] SeuratData_0.2.2 SeuratObject_4.0.4 Seurat_4.1.0
##
## loaded via a namespace (and not attached):
## [1] backports_1.4.1 plyr_1.8.6 igraph_1.2.11
## [4] lazyeval_0.2.2 splines_4.0.2 listenv_0.8.0
## [7] scattermore_0.7 digest_0.6.29 htmltools_0.5.2
## [10] fansi_1.0.2 magrittr_2.0.2 memoise_2.0.1
## [13] tensor_1.5 cluster_2.1.3 ROCR_1.0-11
## [16] remotes_2.4.2 globals_0.14.0 matrixStats_0.61.0
## [19] R.utils_2.11.0 spatstat.sparse_2.1-0 prettyunits_1.1.1
## [22] colorspace_2.0-2 rappdirs_0.3.3 ggrepel_0.9.1
## [25] xfun_0.30 callr_3.7.0 crayon_1.4.2
## [28] jsonlite_1.7.3 spatstat.data_2.1-2 survival_3.1-12
## [31] zoo_1.8-9 glue_1.6.1 polyclip_1.10-0
## [34] gtable_0.3.0 leiden_0.3.9 car_3.0-12
## [37] pkgbuild_1.3.1 future.apply_1.8.1 abind_1.4-5
## [40] scales_1.1.1 DBI_1.1.2 rstatix_0.7.0
## [43] miniUI_0.1.1.1 Rcpp_1.0.8 viridisLite_0.4.0
## [46] xtable_1.8-4 reticulate_1.24 spatstat.core_2.3-2
## [49] rsvd_1.0.5 htmlwidgets_1.5.4 httr_1.4.2
## [52] RColorBrewer_1.1-2 ellipsis_0.3.2 ica_1.0-2
## [55] farver_2.1.0 pkgconfig_2.0.3 R.methodsS3_1.8.1
## [58] sass_0.4.0 uwot_0.1.11 deldir_1.0-6
## [61] utf8_1.2.2 labeling_0.4.2 tidyselect_1.1.2
## [64] rlang_1.0.2 reshape2_1.4.4 later_1.3.0
## [67] munsell_0.5.0 tools_4.0.2 cachem_1.0.6
## [70] cli_3.2.0 generics_0.1.2 broom_0.7.12
## [73] ggridges_0.5.3 evaluate_0.15 stringr_1.4.0
## [76] fastmap_1.1.0 yaml_2.2.2 goftest_1.2-3
## [79] processx_3.5.2 knitr_1.39 fs_1.5.2
## [82] fitdistrplus_1.1-6 purrr_0.3.4 RANN_2.6.1
## [85] pbapply_1.5-0 future_1.23.0 nlme_3.1-148
## [88] mime_0.12 ggrastr_1.0.1 R.oo_1.24.0
## [91] brio_1.1.3 compiler_4.0.2 rstudioapi_0.13
## [94] beeswarm_0.4.0 plotly_4.10.0 png_0.1-7
## [97] ggsignif_0.6.3 testthat_3.1.2 spatstat.utils_2.3-0
## [100] tibble_3.1.6 bslib_0.3.1 stringi_1.7.6
## [103] highr_0.9 ps_1.6.0 desc_1.4.0
## [106] lattice_0.20-41 Matrix_1.4-0 vctrs_0.3.8
## [109] pillar_1.7.0 lifecycle_1.0.1 BiocManager_1.30.16
## [112] spatstat.geom_2.3-1 lmtest_0.9-39 jquerylib_0.1.4
## [115] RcppAnnoy_0.0.19 data.table_1.14.2 cowplot_1.1.1
## [118] irlba_2.3.5 httpuv_1.6.5 patchwork_1.1.1
## [121] R6_2.5.1 promises_1.2.0.1 KernSmooth_2.23-17
## [124] gridExtra_2.3 vipor_0.4.5 parallelly_1.30.0
## [127] sessioninfo_1.2.2 codetools_0.2-16 pkgload_1.2.4
## [130] MASS_7.3-51.6 assertthat_0.2.1 rprojroot_2.0.2
## [133] withr_2.4.3 sctransform_0.3.3 mgcv_1.8-31
## [136] parallel_4.0.2 grid_4.0.2 rpart_4.1-15
## [139] tidyr_1.2.0 rmarkdown_2.14 carData_3.0-5
## [142] Rtsne_0.15 shiny_1.7.1 ggbeeswarm_0.6.0