Supplementary figure 4
Last updated: 2024-12-24
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Knit directory: proj_distal/analysis/
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# scRNA-seq
library(Seurat)
#packageVersion("Seurat")
# Plotting
library("ggplot2")
library(cowplot)
# Presentation
library("knitr")
# Others
library(stringr)
library("readxl")
library("rstatix")
library(ggpubr)
library('scales')
library( "RColorBrewer")source(here::here("R/00_generalDeps.R"))
source(here::here("R/output.R"))filt_path <- here::here("data/processed/figure2_output_seurat_subset.rds")Introduction
In this document we are going to perform plotting supplementary figure 4 panel A using Seurat.
Loading seurat object processed
if (file.exists(filt_path)) {
subset <- readRDS(filt_path)
} else {
stop("Supplementary figure 4 dataset is missing. ",
"Please check Input first.",
call. = FALSE)
}visualization
Literature-based-gene set score
DimPlot( subset, label=TRUE, label.size = 8) +
theme( axis.title.x = element_blank(),
axis.title.y = element_blank(),
legend.position = "none") 
gene_set_pub <- read_excel(paste0(here::here("data/processed/Gene set publications.xlsx")), col_names = FALSE, sheet = "Feuil1")
gene_set_pub <- as.data.frame(gene_set_pub)
# stocke in list
boxplot_list = list()
featureplot_list = list()
df_scores <- subset@meta.data[,c("UniqueCellID","Group")]
for( j in c(3:5,10,12,15,16)){
paper_names = paste0(gene_set_pub[1,j],"_",gene_set_pub[3,j], "_",gene_set_pub[4,j], "_",gene_set_pub[5,j])
paper_names = gsub('\\(','',paper_names)
paper_names = gsub('\\)','',paper_names)
paper_names = gsub(' ','_',paper_names)
cat("###",paper_names, '<br>', '\n')
genes = gene_set_pub[11:nrow(gene_set_pub),j]
# Remove NA
genes <- genes[!is.na(genes)]
# filtering
genes = genes[genes %in% rownames(subset)]
subset <- AddModuleScore(subset,
features = list(genes),
ctrl = 5,
name = paper_names)
df <- subset@meta.data
# List module score violin Plot pairwise wilcoxon test
liste_scores <- df[,c(paste0(paper_names, "1"),'Group')]
names(liste_scores) <- c('mod_score','Group')
pwWlcx_scores <- pairwise_wilcox_test(liste_scores,formula=mod_score ~ Group,p.adjust.method = "BH")
# Create datatable
cat(knitr::knit_print(DT::datatable( as.data.frame(pwWlcx_scores), height = "100%", width = "100%",
class = "compact",
rownames = FALSE,
#colnames = c("Sample", "Nb. Cells"),
options = list(dom = "<'row'rt>", # Set elements for CSS formatting ('<Blf><rt><ip>')
autoWidth = FALSE,
columnDefs = list( # Center all columns
list( targets = 0:(ncol(pwWlcx_scores)-1),
className = 'dt-center')),
orderClasses = FALSE, # Disable flag for CSS to highlight columns used for ordering (for performance)
paging = FALSE, # Disable pagination (show all)
processing = TRUE,
scrollCollapse = TRUE,
scroller = TRUE, # Only load visible data
scrollX = TRUE,
scrollY = "525px",
stateSave = TRUE))
))
p <- ggplot(df, aes(x=Group, y=eval(parse(text = paste0(paper_names, "1"))), color =Group)) +
geom_boxplot(color="grey") + geom_jitter(shape=16, position=position_jitter(0.2))+
theme_classic() +
stat_pvalue_manual(pwWlcx_scores, hide.ns = FALSE, y.position=max(df[[paste0(paper_names, "1")]])+0.05, step.increase=0.05) +
#scale_color_manual(values=col)+
theme(axis.text.x = element_text(angle = 0)) + theme(legend.position = 'none') + xlab("") + ylab(paper_names)
print(p)
# variable scope: local
boxplot_list[[paper_names]] <- local({
paper_names <- paper_names
ggplot(df, aes(x=Group, y=eval(parse(text = paste0(paper_names, "1"))), color =Group)) +
geom_boxplot(color="grey") + geom_jitter(shape=16, position=position_jitter(0.2))+
theme_classic() +
stat_pvalue_manual(pwWlcx_scores, hide.ns = FALSE, y.position=max(df[[paste0(paper_names, "1")]])+0.05, step.increase=0.05) +
#scale_color_manual(values=col)+
theme(axis.text.x = element_text(angle = 0)) + theme(legend.position = 'none') + xlab("") + ylab(paper_names)
})
#print(boxplot_list[[paper_names]] )
p<-FeaturePlot(subset,
features = paste0(paper_names, "1"), repel = TRUE) +
scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu")))
print(p)
featureplot_list[[paper_names]] <- p + labs(title = "")& NoAxes()
df_scores[[paper_names]] = subset@meta.data[[paste0(paper_names, "1")]]
cat("\n\n")
}Poon_et_al_2022_nat_immunol_Human_Lung_CD4_TRM
Poon_et_al_2022_nat_immunol_Human_Skin_CD4_TRM
Poon_et_al_2022_nat_immunol_Human_jejunum_CD4_TRM
Zhang_2022_Gut_Human_Liver_HBV_infiltrating_CD4
Zheng_2017_Cell_Human_HCC_infiltrating_CD4
Argyriou_2022_Nat_Comm_Human_Synovial_tissues_TPH
Law_et_al_2024_Nature_Human_Synovial_tissues_TPH
Supplementary figure 4
Panel A
fig <- plot_grid(boxplot_list[[1]], featureplot_list[[1]],
boxplot_list[[2]], featureplot_list[[2]],
boxplot_list[[3]], featureplot_list[[3]],
boxplot_list[[4]], featureplot_list[[4]],
boxplot_list[[5]], featureplot_list[[5]],
boxplot_list[[6]], featureplot_list[[6]],
boxplot_list[[7]], featureplot_list[[7]],
nrow = 3, labels = "A")
dir.create(here::here("output", DOCNAME), showWarnings = FALSE)
ggsave(here::here("output", DOCNAME, "suppfigure4-panelA.pdf"), fig,
width = 24, height = 12, scale = 1)
ggsave(here::here("output", DOCNAME, "suppfigure4-panelA.png"), fig,
width = 24, height = 12, scale = 1)
fig
Output files
saveRDS(subset, here::here("data/processed/suppfigure4_output_seurat_subset.rds"))
write.table(df_scores, here::here("output", DOCNAME,"suppfigure4-raw_data.csv"), row.names=TRUE,col.names=TRUE, sep =',')Session information
devtools::session_info()─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 4.1.2 (2021-11-01)
os Ubuntu 20.04.3 LTS
system x86_64, linux-gnu
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz Etc/UTC
date 2024-12-24
pandoc 2.14.0.3 @ /usr/lib/rstudio-server/bin/pandoc/ (via rmarkdown)
─ Packages ───────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
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assertthat 0.2.1 2019-03-21 [1] RSPM (R 4.1.0)
backports 1.4.1 2021-12-13 [1] RSPM (R 4.1.0)
brio 1.1.3 2021-11-30 [1] RSPM (R 4.1.0)
broom 0.7.12 2022-01-28 [1] RSPM (R 4.1.0)
bslib 0.3.1 2021-10-06 [1] RSPM (R 4.1.0)
cachem 1.0.6 2021-08-19 [1] RSPM (R 4.1.0)
callr 3.7.0 2021-04-20 [1] RSPM (R 4.1.0)
car 3.0-12 2021-11-06 [1] RSPM (R 4.1.0)
carData 3.0-5 2022-01-06 [1] RSPM (R 4.1.0)
cellranger 1.1.0 2016-07-27 [1] RSPM (R 4.1.0)
cli 3.6.1 2023-03-23 [1] RSPM (R 4.1.0)
cluster 2.1.2 2021-04-17 [2] CRAN (R 4.1.2)
codetools 0.2-18 2020-11-04 [2] CRAN (R 4.1.2)
colorspace 2.0-3 2022-02-21 [1] RSPM (R 4.1.0)
cowplot * 1.1.1 2020-12-30 [1] RSPM (R 4.1.0)
crayon 1.5.0 2022-02-14 [1] RSPM (R 4.1.0)
data.table 1.14.2 2021-09-27 [1] RSPM (R 4.1.0)
DBI 1.1.2 2021-12-20 [1] RSPM (R 4.1.0)
deldir 1.0-6 2021-10-23 [1] RSPM (R 4.1.0)
desc 1.4.1 2022-03-06 [1] RSPM (R 4.1.0)
devtools 2.4.3 2021-11-30 [1] RSPM (R 4.1.0)
digest 0.6.29 2021-12-01 [1] RSPM (R 4.1.0)
dplyr 1.0.8 2022-02-08 [1] RSPM (R 4.1.0)
ellipsis 0.3.2 2021-04-29 [1] RSPM (R 4.1.0)
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fansi 1.0.2 2022-01-14 [1] RSPM (R 4.1.0)
fastmap 1.1.0 2021-01-25 [1] RSPM (R 4.1.0)
fitdistrplus 1.1-6 2021-09-28 [1] RSPM (R 4.1.0)
fs 1.5.2 2021-12-08 [1] RSPM (R 4.1.0)
future 1.23.0 2021-10-31 [1] RSPM (R 4.1.0)
future.apply 1.8.1 2021-08-10 [1] RSPM (R 4.1.0)
generics 0.1.2 2022-01-31 [1] RSPM (R 4.1.0)
ggplot2 * 3.4.4 2023-10-12 [1] RSPM (R 4.1.0)
ggpubr * 0.4.0 2020-06-27 [1] RSPM (R 4.1.0)
ggrepel 0.9.1 2021-01-15 [1] RSPM (R 4.1.0)
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ggsignif 0.6.3 2021-09-09 [1] RSPM (R 4.1.0)
git2r 0.33.0 2023-11-26 [1] RSPM (R 4.1.0)
globals 0.14.0 2020-11-22 [1] RSPM (R 4.1.0)
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goftest 1.2-3 2021-10-07 [1] RSPM (R 4.1.0)
gridExtra 2.3 2017-09-09 [1] RSPM (R 4.1.0)
gtable 0.3.0 2019-03-25 [1] RSPM (R 4.1.0)
here 1.0.1 2020-12-13 [1] RSPM (R 4.1.0)
htmltools 0.5.2 2021-08-25 [1] RSPM (R 4.1.0)
htmlwidgets 1.5.4 2021-09-08 [1] RSPM (R 4.1.0)
httpuv 1.6.5 2022-01-05 [1] RSPM (R 4.1.0)
httr 1.4.2 2020-07-20 [1] RSPM (R 4.1.0)
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igraph 1.5.1 2023-08-10 [1] RSPM (R 4.1.0)
irlba 2.3.5 2021-12-06 [1] RSPM (R 4.1.0)
jquerylib 0.1.4 2021-04-26 [1] RSPM (R 4.1.0)
jsonlite 1.8.0 2022-02-22 [1] RSPM (R 4.1.0)
KernSmooth 2.23-20 2021-05-03 [2] CRAN (R 4.1.2)
knitr * 1.37 2021-12-16 [1] RSPM (R 4.1.0)
later 1.3.0 2021-08-18 [1] RSPM (R 4.1.0)
lattice 0.20-45 2021-09-22 [2] CRAN (R 4.1.2)
lazyeval 0.2.2 2019-03-15 [1] RSPM (R 4.1.0)
leiden 0.3.9 2021-07-27 [1] RSPM (R 4.1.0)
lifecycle 1.0.3 2022-10-07 [1] RSPM (R 4.1.0)
listenv 0.8.0 2019-12-05 [1] RSPM (R 4.1.0)
lmtest 0.9-39 2021-11-07 [1] RSPM (R 4.1.0)
magrittr 2.0.2 2022-01-26 [1] RSPM (R 4.1.0)
MASS 7.3-54 2021-05-03 [2] CRAN (R 4.1.2)
Matrix 1.3-4 2021-06-01 [2] CRAN (R 4.1.2)
matrixStats 0.61.0 2021-09-17 [1] RSPM (R 4.1.0)
memoise 2.0.1 2021-11-26 [1] RSPM (R 4.1.0)
mgcv 1.8-38 2021-10-06 [2] CRAN (R 4.1.2)
mime 0.12 2021-09-28 [1] RSPM (R 4.1.0)
miniUI 0.1.1.1 2018-05-18 [1] RSPM (R 4.1.0)
munsell 0.5.0 2018-06-12 [1] RSPM (R 4.1.0)
nlme 3.1-153 2021-09-07 [2] CRAN (R 4.1.2)
parallelly 1.30.0 2021-12-17 [1] RSPM (R 4.1.0)
patchwork 1.1.1 2020-12-17 [1] RSPM (R 4.1.0)
pbapply 1.5-0 2021-09-16 [1] RSPM (R 4.1.0)
pillar 1.7.0 2022-02-01 [1] RSPM (R 4.1.0)
pkgbuild 1.3.1 2021-12-20 [1] RSPM (R 4.1.0)
pkgconfig 2.0.3 2019-09-22 [1] RSPM (R 4.1.0)
pkgload 1.2.4 2021-11-30 [1] RSPM (R 4.1.0)
plotly 4.10.0 2021-10-09 [1] RSPM (R 4.1.0)
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promises 1.2.0.1 2021-02-11 [1] RSPM (R 4.1.0)
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purrr 0.3.4 2020-04-17 [1] RSPM (R 4.1.0)
R6 2.5.1 2021-08-19 [1] RSPM (R 4.1.0)
RANN 2.6.1 2019-01-08 [1] RSPM (R 4.1.0)
RColorBrewer * 1.1-2 2014-12-07 [1] RSPM (R 4.1.0)
Rcpp 1.0.8 2022-01-13 [1] RSPM (R 4.1.0)
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spatstat.core 2.3-2 2021-11-26 [1] RSPM (R 4.1.0)
spatstat.data 2.1-2 2021-12-17 [1] RSPM (R 4.1.0)
spatstat.geom 2.4-0 2022-03-29 [1] RSPM (R 4.1.0)
spatstat.sparse 2.1-0 2021-12-17 [1] RSPM (R 4.1.0)
spatstat.utils 2.3-0 2021-12-12 [1] RSPM (R 4.1.0)
stringi 1.7.6 2021-11-29 [1] RSPM (R 4.1.0)
stringr * 1.4.0 2019-02-10 [1] RSPM (R 4.1.0)
survival 3.2-13 2021-08-24 [2] CRAN (R 4.1.2)
tensor 1.5 2012-05-05 [1] RSPM (R 4.1.0)
testthat 3.1.2 2022-01-20 [1] RSPM (R 4.1.0)
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tidyr 1.2.0 2022-02-01 [1] RSPM (R 4.1.0)
tidyselect 1.1.2 2022-02-21 [1] RSPM (R 4.1.0)
usethis 2.1.5 2021-12-09 [1] RSPM (R 4.1.0)
utf8 1.2.2 2021-07-24 [1] RSPM (R 4.1.0)
uwot 0.1.11 2021-12-02 [1] RSPM (R 4.1.0)
vctrs 0.6.4 2023-10-12 [1] RSPM (R 4.1.0)
viridisLite 0.4.0 2021-04-13 [1] RSPM (R 4.1.0)
withr 2.5.0 2022-03-03 [1] RSPM (R 4.1.0)
workflowr 1.7.1 2023-08-23 [1] RSPM (R 4.1.0)
xfun 0.30 2022-03-02 [1] RSPM (R 4.1.0)
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[1] /usr/local/lib/R/site-library
[2] /usr/local/lib/R/library
──────────────────────────────────────────────────────────────────────────────
sessionInfo()R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.3 LTS
Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] RColorBrewer_1.1-2 scales_1.2.1 ggpubr_0.4.0 rstatix_0.7.0
[5] readxl_1.3.1 stringr_1.4.0 knitr_1.37 cowplot_1.1.1
[9] ggplot2_3.4.4 SeuratObject_4.0.4 Seurat_4.1.0
loaded via a namespace (and not attached):
[1] backports_1.4.1 workflowr_1.7.1 systemfonts_1.0.4
[4] plyr_1.8.6 igraph_1.5.1 lazyeval_0.2.2
[7] splines_4.1.2 crosstalk_1.2.0 listenv_0.8.0
[10] scattermore_0.7 usethis_2.1.5 digest_0.6.29
[13] htmltools_0.5.2 fansi_1.0.2 memoise_2.0.1
[16] magrittr_2.0.2 tensor_1.5 cluster_2.1.2
[19] ROCR_1.0-11 remotes_2.4.2 globals_0.14.0
[22] matrixStats_0.61.0 spatstat.sparse_2.1-0 prettyunits_1.1.1
[25] colorspace_2.0-3 ggrepel_0.9.1 textshaping_0.3.6
[28] xfun_0.30 dplyr_1.0.8 callr_3.7.0
[31] crayon_1.5.0 jsonlite_1.8.0 spatstat.data_2.1-2
[34] survival_3.2-13 zoo_1.8-9 glue_1.6.2
[37] polyclip_1.10-0 gtable_0.3.0 leiden_0.3.9
[40] pkgbuild_1.3.1 car_3.0-12 future.apply_1.8.1
[43] abind_1.4-5 DBI_1.1.2 miniUI_0.1.1.1
[46] Rcpp_1.0.8 viridisLite_0.4.0 xtable_1.8-4
[49] reticulate_1.23 spatstat.core_2.3-2 DT_0.22
[52] htmlwidgets_1.5.4 httr_1.4.2 ellipsis_0.3.2
[55] ica_1.0-2 pkgconfig_2.0.3 farver_2.1.0
[58] sass_0.4.0 uwot_0.1.11 deldir_1.0-6
[61] utf8_1.2.2 here_1.0.1 tidyselect_1.1.2
[64] labeling_0.4.2 rlang_1.1.1 reshape2_1.4.4
[67] later_1.3.0 cachem_1.0.6 munsell_0.5.0
[70] cellranger_1.1.0 tools_4.1.2 cli_3.6.1
[73] generics_0.1.2 devtools_2.4.3 broom_0.7.12
[76] ggridges_0.5.3 evaluate_0.15 fastmap_1.1.0
[79] yaml_2.3.5 ragg_1.2.2 goftest_1.2-3
[82] processx_3.5.2 fs_1.5.2 fitdistrplus_1.1-6
[85] purrr_0.3.4 RANN_2.6.1 pbapply_1.5-0
[88] future_1.23.0 nlme_3.1-153 mime_0.12
[91] brio_1.1.3 compiler_4.1.2 rstudioapi_0.13
[94] plotly_4.10.0 png_0.1-7 testthat_3.1.2
[97] ggsignif_0.6.3 spatstat.utils_2.3-0 tibble_3.1.8
[100] bslib_0.3.1 stringi_1.7.6 ps_1.6.0
[103] highr_0.9 desc_1.4.1 lattice_0.20-45
[106] Matrix_1.3-4 vctrs_0.6.4 pillar_1.7.0
[109] lifecycle_1.0.3 spatstat.geom_2.4-0 lmtest_0.9-39
[112] jquerylib_0.1.4 RcppAnnoy_0.0.19 data.table_1.14.2
[115] irlba_2.3.5 httpuv_1.6.5 patchwork_1.1.1
[118] R6_2.5.1 promises_1.2.0.1 KernSmooth_2.23-20
[121] gridExtra_2.3 parallelly_1.30.0 sessioninfo_1.2.2
[124] codetools_0.2-18 pkgload_1.2.4 MASS_7.3-54
[127] assertthat_0.2.1 rprojroot_2.0.2 withr_2.5.0
[130] sctransform_0.3.3 mgcv_1.8-38 parallel_4.1.2
[133] grid_4.1.2 rpart_4.1-15 tidyr_1.2.0
[136] rmarkdown_2.11 carData_3.0-5 Rtsne_0.15
[139] git2r_0.33.0 shiny_1.7.1