Last updated: 2022-02-22

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Knit directory: MelanomaIMC/

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Introduction

Color schemes

Preparations

knitr::opts_chunk$set(echo = TRUE, message= FALSE)
knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())

Load libraries

library(SingleCellExperiment)
library(colorRamps)

Load data

sce_rna <- readRDS("data/data_for_analysis/sce_RNA.rds")
sce_prot <- readRDS("data/data_for_analysis/sce_protein.rds")

All celltypes

colvec <- c("sienna4", "tomato", "gray65", "red3", "blueviolet", "deeppink", "blueviolet",
         "darkorchid1", "deepskyblue", "darkblue", "deepskyblue","aquamarine", "green",
         "darkgreen", "yellow")

names(colvec) <- c("Tumor", "Stroma", "unknown", "Vasculature", "CD8- T cell", "CD8+ T cell", "CD4+ T cell",
           "FOXP3+ T cell", "B cell", "BnT cell", "HLA-DR", "CD38" ,"Macrophage", "Neutrophil", "pDC")

pie(c(rep(1,length((colvec)))),col = colvec,labels = names(colvec))

Version Author Date
5418dcd toobiwankenobi 2022-02-22
col_celltypes <- colvec
names(col_celltypes) <- names(colvec)

RNA

Celltypes

cell_rna <- col_celltypes[c("Tumor", "Stroma", "unknown", "Vasculature", "CD8- T cell", 
                            "CD8+ T cell", "HLA-DR", "CD38","Macrophage", "Neutrophil")]

metadata(sce_rna)$colour_vectors$celltype <- cell_rna

Chemokines (Combinations)

# add color vector to metadata
targets <- metadata(sce_rna)$chemokines_morethan600_withcontrol
color_chemo <- primary.colors(length(targets))
names(color_chemo) <- targets

#barplot(seq_along(targets), col=color_chemo, main="Pastel_hcl", names.arg = targets)
metadata(sce_rna)$colour_vectors$chemokine_combinations <- color_chemo

Chemokines (single)

col_vector_chemokines <- metadata(sce_rna)$colour_vector$chemokine_combinations
col_vector_chemokines <- col_vector_chemokines[c("CXCL13", "CXCL10", "CXCL9", "CCL2", "CXCL12", "CCL19", "CCL18", "CXCL8", "CCL4", "CCL22")]
col_vector_new_chemo <- c("forestgreen")
names(col_vector_new_chemo) <- c("CCL8")
  
col_vector_chemokines <- c(col_vector_chemokines, col_vector_new_chemo)

metadata(sce_rna)$colour_vectors$chemokine_single <- col_vector_chemokines

Protein

Celltypes

cell_protein <- col_celltypes[c("Tumor", "Stroma", "unknown", "CD8+ T cell", 
                                "CD4+ T cell", "FOXP3+ T cell", "B cell", "BnT cell",
                                "Macrophage", "Neutrophil", "pDC")]

metadata(sce_prot)$colour_vectors$celltype <- cell_protein

Save RDS

saveRDS(sce_rna, "data/data_for_analysis/sce_RNA.rds")
saveRDS(sce_prot, "data/data_for_analysis/sce_protein.rds")

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] stats4    stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] colorRamps_2.3              SingleCellExperiment_1.16.0
 [3] SummarizedExperiment_1.24.0 Biobase_2.54.0             
 [5] GenomicRanges_1.46.1        GenomeInfoDb_1.30.1        
 [7] IRanges_2.28.0              S4Vectors_0.32.3           
 [9] BiocGenerics_0.40.0         MatrixGenerics_1.6.0       
[11] matrixStats_0.61.0          workflowr_1.7.0            

loaded via a namespace (and not attached):
 [1] xfun_0.29              bslib_0.3.1            lattice_0.20-45       
 [4] vctrs_0.3.8            htmltools_0.5.2        yaml_2.2.2            
 [7] utf8_1.2.2             rlang_1.0.0            jquerylib_0.1.4       
[10] later_1.3.0            pillar_1.7.0           glue_1.6.1            
[13] GenomeInfoDbData_1.2.7 lifecycle_1.0.1        stringr_1.4.0         
[16] zlibbioc_1.40.0        evaluate_0.14          knitr_1.37            
[19] callr_3.7.0            fastmap_1.1.0          httpuv_1.6.5          
[22] ps_1.6.0               fansi_1.0.2            highr_0.9             
[25] Rcpp_1.0.8             promises_1.2.0.1       DelayedArray_0.20.0   
[28] jsonlite_1.7.3         XVector_0.34.0         fs_1.5.2              
[31] digest_0.6.29          stringi_1.7.6          processx_3.5.2        
[34] getPass_0.2-2          grid_4.1.2             rprojroot_2.0.2       
[37] cli_3.1.1              tools_4.1.2            bitops_1.0-7          
[40] magrittr_2.0.2         sass_0.4.0             RCurl_1.98-1.5        
[43] tibble_3.1.6           crayon_1.4.2           whisker_0.4           
[46] pkgconfig_2.0.3        Matrix_1.4-0           ellipsis_0.3.2        
[49] rmarkdown_2.11         httr_1.4.2             rstudioapi_0.13       
[52] R6_2.5.1               git2r_0.29.0           compiler_4.1.2