Last updated: 2022-02-22

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Knit directory: MelanomaIMC/

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Introduction

This script generates plots for Supplementary Figure 12.

Preparations

Load libraries

sapply(list.files("code/helper_functions", full.names = TRUE), source)
        code/helper_functions/calculateSummary.R
value   ?                                       
visible FALSE                                   
        code/helper_functions/censor_dat.R
value   ?                                 
visible FALSE                             
        code/helper_functions/detect_mRNA_expression.R
value   ?                                             
visible FALSE                                         
        code/helper_functions/DistanceToClusterCenter.R
value   ?                                              
visible FALSE                                          
        code/helper_functions/findMilieu.R code/helper_functions/findPatch.R
value   ?                                  ?                                
visible FALSE                              FALSE                            
        code/helper_functions/getInfoFromString.R
value   ?                                        
visible FALSE                                    
        code/helper_functions/getSpotnumber.R
value   ?                                    
visible FALSE                                
        code/helper_functions/plotCellCounts.R
value   ?                                     
visible FALSE                                 
        code/helper_functions/plotCellFractions.R
value   ?                                        
visible FALSE                                    
        code/helper_functions/plotDist.R code/helper_functions/read_Data.R
value   ?                                ?                                
visible FALSE                            FALSE                            
        code/helper_functions/scatter_function.R
value   ?                                       
visible FALSE                                   
        code/helper_functions/sceChecks.R
value   ?                                
visible FALSE                            
        code/helper_functions/validityChecks.R
value   ?                                     
visible FALSE                                 
library(SingleCellExperiment)
library(sf)
library(concaveman)
library(RANN)
library(dplyr)
library(data.table)
library(ggplot2)
library(ggrastr)

Load Data

## Read the data
sce_prot = readRDS(file = "data/data_for_analysis/sce_protein.rds")
sce_prot <- sce_prot[,sce_prot$Location != "CTRL"]

Supp Fig 12A

example <- findPatch(sce_prot[,sce_prot$Description == "G3"], sce_prot[,colData(sce_prot)$celltype %in% c("B cell", "BnT cell")]$cellID, 
                    'cellID', 
                    'Center_X', 'Center_Y', 
                    'Description', 
                    distance = 15, 
                    min_clust_size = 20,
                    output_colname = "example_patch")
Time difference of 0.4335275 secs
[1] "patches successfully added to sce object"
example <- findMilieu(example, 
              'cellID', 
              'Center_X', 'Center_Y', 
              'Description', 
              'example_patch', 
              distance = 30,
              output_colname = "example_milieu",
              plot = TRUE)

Version Author Date
235386f toobiwankenobi 2022-02-22
Time difference of 0.5727913 secs
[1] "milieus successfully added to sce object"

Supp Fig 12B

example <- findPatch(sce_prot[,sce_prot$Description == "F5"], sce_prot[,colData(sce_prot)$celltype %in% c("B cell", "BnT cell")]$cellID, 
                    'cellID', 
                    'Center_X', 'Center_Y', 
                    'Description', 
                    distance = 15, 
                    min_clust_size = 20,
                    output_colname = "example_patch")
Time difference of 0.4490788 secs
[1] "patches successfully added to sce object"
example <- findMilieu(example, 
              'cellID', 
              'Center_X', 'Center_Y', 
              'Description', 
              'example_patch', 
              distance = 30,
              output_colname = "example_milieu",
              plot = TRUE)

Version Author Date
235386f toobiwankenobi 2022-02-22
Time difference of 2.110536 secs
[1] "milieus successfully added to sce object"

Supp Fig 12C

example <- findPatch(sce_prot[,sce_prot$Description == "B6"], sce_prot[,colData(sce_prot)$celltype %in% c("B cell", "BnT cell")]$cellID, 
                    'cellID', 
                    'Center_X', 'Center_Y', 
                    'Description', 
                    distance = 15, 
                    min_clust_size = 20,
                    output_colname = "example_patch")
Time difference of 1.270536 secs
[1] "patches successfully added to sce object"
example <- findMilieu(example, 
              'cellID', 
              'Center_X', 'Center_Y', 
              'Description', 
              'example_patch', 
              distance = 30,
              output_colname = "example_milieu",
              plot = TRUE)

Version Author Date
235386f toobiwankenobi 2022-02-22
Time difference of 1.051517 secs
[1] "milieus successfully added to sce object"

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] ggrastr_1.0.1               ggplot2_3.3.5              
 [3] data.table_1.14.2           RANN_2.6.1                 
 [5] concaveman_1.1.0            sf_1.0-5                   
 [7] SingleCellExperiment_1.16.0 SummarizedExperiment_1.24.0
 [9] Biobase_2.54.0              GenomicRanges_1.46.1       
[11] GenomeInfoDb_1.30.1         IRanges_2.28.0             
[13] S4Vectors_0.32.3            BiocGenerics_0.40.0        
[15] MatrixGenerics_1.6.0        matrixStats_0.61.0         
[17] dplyr_1.0.7                 workflowr_1.7.0            

loaded via a namespace (and not attached):
 [1] httr_1.4.2             sass_0.4.0             jsonlite_1.7.3        
 [4] bslib_0.3.1            assertthat_0.2.1       getPass_0.2-2         
 [7] highr_0.9              vipor_0.4.5            GenomeInfoDbData_1.2.7
[10] yaml_2.2.2             pillar_1.7.0           lattice_0.20-45       
[13] glue_1.6.1             digest_0.6.29          promises_1.2.0.1      
[16] XVector_0.34.0         colorspace_2.0-2       htmltools_0.5.2       
[19] httpuv_1.6.5           Matrix_1.4-0           pkgconfig_2.0.3       
[22] zlibbioc_1.40.0        purrr_0.3.4            scales_1.1.1          
[25] processx_3.5.2         whisker_0.4            later_1.3.0           
[28] git2r_0.29.0           tibble_3.1.6           proxy_0.4-26          
[31] farver_2.1.0           generics_0.1.2         ellipsis_0.3.2        
[34] withr_2.4.3            cli_3.1.1              magrittr_2.0.2        
[37] crayon_1.4.2           evaluate_0.14          ps_1.6.0              
[40] fs_1.5.2               fansi_1.0.2            class_7.3-20          
[43] beeswarm_0.4.0         tools_4.1.2            lifecycle_1.0.1       
[46] stringr_1.4.0          V8_4.0.0               munsell_0.5.0         
[49] DelayedArray_0.20.0    callr_3.7.0            compiler_4.1.2        
[52] jquerylib_0.1.4        e1071_1.7-9            rlang_1.0.0           
[55] classInt_0.4-3         units_0.7-2            grid_4.1.2            
[58] RCurl_1.98-1.5         rstudioapi_0.13        bitops_1.0-7          
[61] rmarkdown_2.11         gtable_0.3.0           curl_4.3.2            
[64] DBI_1.1.2              R6_2.5.1               knitr_1.37            
[67] fastmap_1.1.0          utf8_1.2.2             rprojroot_2.0.2       
[70] KernSmooth_2.23-20     ggbeeswarm_0.6.0       stringi_1.7.6         
[73] Rcpp_1.0.8             vctrs_0.3.8            tidyselect_1.1.1      
[76] xfun_0.29