CD45_analysis_soft_assignment_V1

1 Functions

2 Data

acc_immune = LoadH5Seurat(file = "./Data/acc_immune.h5seurat")

DimPlot(acc_immune,label = T)

FeaturePlot(acc_immune, features = c("CD8A","MS4A1", "CD4","CD14","MS4A2"))

markers = FindAllMarkers(object = acc_immune,densify = T)

3 assign cell type

acc_immune <- RenameIdents(object = acc_immune, 
                               "0" = "CD4",
                               "1" = "CD4",
                               "2" = "CD14+ Mono",
                               "3" = "CD4",
                               "4" = "CD8",
                               "5" = "B",
                               "6" = "CD4",
                               "7" = "CD8",
                               "8" = "FCϵR1")
acc_immune$cell_identity = acc_immune@active.ident
DimPlot(object = acc_immune,label = F)

4 Antigen presenting machinery

apm_genes = c("HLA-A","HLA-B","HLA-C","B2M","TAP1","TAP2", "TAPBP")
apm_score = FetchData(acc_immune,vars = apm_genes,slot = "data") %>% rowMeans()
acc_immune = AddMetaData(object = acc_immune,metadata = apm_score,col.name = "APM_score")

print_tab(plt = FeaturePlot(acc_immune,features = apm_genes),title = "genes")
print_tab(plt = FeaturePlot(acc_immune,features = "APM_score"),title = "score")

5 Exhaustion markers

exhausted_genes = c("PDCD1","CD244","CD160","CTLA4","HAVCR2")
FeaturePlot(acc_immune,features = exhausted_genes)

6 Immune receptors

receptors = c("CCR3", "CCR4", "CCR10","CXCR2", "CXCR3", "CXCR4", "IL17A")
FeaturePlot(acc_immune,features = receptors)

7 CellphoneDB

acc_cancer_cells = readRDS("/sci/labs/yotamd/lab_share/avishai.wizel/R_projects/ACC_microenv/Data/acc_cancer_no146_primaryonly15k_cancercells.rds")
acc_caf = readRDS("/sci/labs/yotamd/lab_share/ACC/ACC_sc/analysis/acc_tpm_nCount_mito_no146_cafs.rds")

DimPlot(acc_caf)

# merge cancer and immune
common_genes = intersect(rownames(acc_cancer_cells),rownames(acc_immune)) %>% intersect(rownames(acc_caf_cells))
acc_cancer_and_cd45 = merge(acc_cancer_cells[common_genes,],acc_immune[common_genes,])
overlapping_cells = colnames(acc_cancer_cells) %>% intersect(colnames(acc_caf)) 
acc_cancer_cd45_caf = merge(acc_cancer_and_cd45[common_genes,],acc_caf_cells[common_genes,!colnames(acc_caf_cells) %in% overlapping_cells] )

  #write metadata

#create lum or myo
lum_over_myo = FetchData(object = acc_cancer_cells,vars = "luminal_over_myo")
lum_over_myo$lum_or_myo = "Unknown"
lum_over_myo$lum_or_myo [lum_over_myo$luminal_over_myo>1]  = "Luminal"
lum_over_myo$lum_or_myo [lum_over_myo$luminal_over_myo<(-1)]  = "Myo"
lum_or_myo = lum_over_myo[,"lum_or_myo",drop = F]
names(lum_or_myo)[1] = "cell_identity"

# combine
immune_identity =FetchData(object = acc_immune,vars = "cell_identity")
caf_identity =FetchData(object = acc_caf_cells,vars = "cell.type")
names(caf_identity)[1] = "cell_identity"
all_identity = do.call("rbind", list(lum_or_myo, immune_identity, caf_identity))

#rename and sort columns
all_identity$barcode_sample = rownames(all_identity)
all_identity = all_identity %>% rename(cell_type = cell_identity)
all_identity = all_identity[,c(2,1)]


write.table(x = all_identity,file = "./Data/CellphoneDB/metadata_soft.tsv",row.names =F,sep = "\t")

#write normalized counts
count_matrix = as.data.frame(acc_cancer_cd45_caf@assays[["RNA"]]@data)
fwrite(count_matrix, file = "./Data/CellphoneDB/counts.txt",sep = "\t",row.names = T)

8 significant interactions heatmap

plot_cpdb_heatmap(scdata = acc_cancer_cd45_caf, idents = 'cell_type',pvals =  pvals,main = "Number of significant interactions",alpha = 0.05)

Warning in strwidth(t, units = "in", cex = fontsize_col/fontsize) :
  conversion failure on 'FCϵR1' in 'mbcsToSbcs': dot substituted for <cf>
Warning in strwidth(t, units = "in", cex = fontsize_col/fontsize) :
  conversion failure on 'FCϵR1' in 'mbcsToSbcs': dot substituted for <b5>
Warning in strwidth(t, units = "in", cex = fontsize_row/fontsize) :
  conversion failure on 'FCϵR1' in 'mbcsToSbcs': dot substituted for <cf>
Warning in strwidth(t, units = "in", cex = fontsize_row/fontsize) :
  conversion failure on 'FCϵR1' in 'mbcsToSbcs': dot substituted for <b5>
Warning in grSoftVersion() :
  unable to load shared object '/usr/local/lib/R/modules//R_X11.so':
  libXt.so.6: cannot open shared object file: No such file or directory

#trace(plot_cpdb,edit = T)

uniq_interactions <- function(cell_type1, cell_type2_a ,cell_type2_b, gene.family = NULL,genes = NULL) {

  a = plot_cpdb(cell_type1 = cell_type1, cell_type2 =cell_type2_a, scdata = acc_cancer_cd45_caf,
                      idents = 'cell_type', means = means, pvals = pvals,
                      gene.family = gene.family,return_table = T, p.adjust.method = "fdr",keep_significant_only = T, genes = genes)
  
  b = plot_cpdb(cell_type1 = cell_type1, cell_type2 = cell_type2_b, scdata = acc_cancer_cd45_caf,
                      idents = 'cell_type', means = means, pvals = pvals,
                      gene.family = gene.family,return_table = T,p.adjust.method = "fdr",keep_significant_only = T, genes = genes)
  
  
  all = list()
  i=0
  nelements = a$Var2 %>% unique() %>% length()
  a_couples = a$Var2 %>% unique()%>% as.vector()  
  b_couples = b$Var2 %>% unique()%>% as.vector()  
  for (i in 1:nelements) {
    sig_couples_a = a %>% filter(Var2 == a_couples[i]) %>% filter(pvals_adj <= 0.05) %>%  pull(Var1) %>% as.vector()  
    sig_couples_b = b %>% filter(Var2 == b_couples[i]) %>% filter(pvals_adj <= 0.05) %>%  pull(Var1) %>% as.vector()  
    only_in_a = sig_couples_a[! sig_couples_a %in% sig_couples_b]
    all[[a_couples[i]]] = only_in_a 
    i = i+1
  }
  all = t(map_dfr(all, ~as_data_frame(t(.)))) %>% as.data.frame() %>% set_names(a_couples)
  return(all)
}

9 Costimulatory interactions

print_tab(plt = 
            plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Luminal', scdata = acc_cancer_cd45_caf,
                      idents = 'cell_type', means = means, pvals = pvals,
                      gene.family = 'costimulatory',return_table = F,max_size = 3,p.adjust.method = "fdr",keep_significant_only = T,cluster_rows = F)+
            ggtitle("Costimulatory Luminal")
  ,title = "Luminal")

Luminal

print_tab(plt = 
            plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Myo', scdata = acc_cancer_cd45_caf,
                      idents = 'cell_type', means = means, pvals = pvals,
                      gene.family = 'costimulatory',return_table = F,max_size = 3,p.adjust.method = "fdr",keep_significant_only = T,cluster_rows = F)+
            ggtitle("Costimulatory Myo")
  ,title = "Myo")

Myo

print_tab(plt = 
            plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'CAF', scdata = acc_cancer_cd45_caf,
                      idents = 'cell_type', means = means, pvals = pvals,
                      gene.family = 'costimulatory',return_table = F,max_size = 3,p.adjust.method = "fdr",keep_significant_only = T,cluster_rows = F)+
            ggtitle("Costimulatory Myo")
  ,title = "CAF")

CAF

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'Luminal',cell_type2_b = "Myo",gene.family = "Costimulatory")
,title = "unique in luminal")

unique in luminal

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'Myo',cell_type2_b = "Luminal",gene.family = "Costimulatory")
,title = "unique in myo")

unique in myo

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'CAF',cell_type2_b = "Myo|Luminal",gene.family = "Costimulatory")
,title = "unique in CAF")

unique in CAF

NA

10 Coinhibitory interactions

print_tab(plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Luminal', scdata = acc_cancer_cd45_caf,
          idents = 'cell_type', means = means, pvals = pvals,
          gene.family = 'coinhibitory',return_table = F,max_size = 4,p.adjust.method = "fdr",keep_significant_only = F,cluster_rows = F)+
  ggtitle("coinhibitory Luminal"),title = "Luminal")

Luminal

print_tab(plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Myo', scdata = acc_cancer_cd45_caf,
          idents = 'cell_type', means = means, pvals = pvals,
          gene.family = 'coinhibitory',return_table = F,max_size = 4,p.adjust.method = "fdr",keep_significant_only = F,cluster_rows = F)+
  ggtitle("coinhibitory Myo"),title = "Myo")

Myo

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'Luminal',cell_type2_b = "Myo",gene.family = "coinhibitory")
,title = "unique in luminal")

unique in luminal

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'Myo',cell_type2_b = "Luminal",gene.family = "coinhibitory")
,title = "unique in myo")

unique in myo

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'CAF',cell_type2_b = "Myo|Luminal",gene.family = "coinhibitory")
,title = "unique in CAF")

unique in CAF

NA

11 Chemokines interactions

print_tab(
  plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Luminal', scdata = acc_cancer_cd45_caf,
          idents = 'cell_type', means = means, pvals = pvals,
          gene.family = 'chemokines',return_table = F,max_size = 4,p.adjust.method = "fdr",keep_significant_only = F,cluster_rows = F)+
  ggtitle("chemokines Luminal"),title = "Luminal")

Luminal

print_tab(
  plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Myo', scdata = acc_cancer_cd45_caf,
          idents = 'cell_type', means = means, pvals = pvals,
          gene.family = 'chemokines',return_table = F,max_size = 4,p.adjust.method = "fdr",keep_significant_only = F,cluster_rows = F)+
  ggtitle("chemokines Myo"),title = "Myo")

Myo

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'Luminal',cell_type2_b = "Myo",gene.family = "chemokines")
,title = "unique in luminal")

unique in luminal

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'Myo',cell_type2_b = "Luminal",gene.family = "chemokines")
,title = "unique in myo")

unique in myo

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'CAF',cell_type2_b = "Myo|Luminal",gene.family = "chemokines")
,title = "unique in CAF")

unique in CAF

NA

12 Chemokine ligands

genes = c("CXCL1\\D", "CXCL2\\D","CXCL3\\D","CXCL17","C3","CXCL14")
print_tab(plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Myo', scdata = acc_cancer_cd45_caf,
    idents = 'cell_type', means = means, pvals = pvals,
 genes = genes,return_table = F,max_size = 4,p.adjust.method = "fdr" ,keep_significant_only = F) 
 ,title = "Myo")

Myo

print_tab(plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Luminal', scdata = acc_cancer_cd45_caf,
    idents = 'cell_type', means = means, pvals = pvals,
  genes = genes,return_table = F,max_size = 4,p.adjust.method = "fdr" ,keep_significant_only = F) 
,title = "Luminal")

Luminal

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'Luminal',cell_type2_b = "Myo", genes = genes)
,title = "unique in luminal")

unique in luminal

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'Myo',cell_type2_b = "Luminal", genes = genes)
,title = "unique in myo")

unique in myo

print_tab(plt = 
            uniq_interactions(cell_type1 = 'CD|B|FC',cell_type2_a  = 'CAF',cell_type2_b = "Myo|Luminal", genes = genes)
,title = "unique in CAF")

unique in CAF

NA

13 CCL22 and CCL28

print_tab(plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Myo', scdata = acc_cancer_cd45_caf,
    idents = 'cell_type', means = means, pvals = pvals,
 genes = c("CCL22", "CCL28" ),return_table = F,max_size = 4,p.adjust.method = "fdr" ,keep_significant_only = F),title = "Myo")

Myo

print_tab(plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Luminal', scdata = acc_cancer_cd45_caf,
    idents = 'cell_type', means = means, pvals = pvals,
  genes = c("CCL22", "CCL28" ),return_table = F,max_size = 6,p.adjust.method = "fdr" ,keep_significant_only = F),title = "Luminal")

Luminal

NA

plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Myo', scdata = acc_cancer_cd45_caf,
    idents = 'cell_type', means = means, pvals = pvals,
 genes = c("JAG", "MYB" ),return_table = F,max_size = 4,p.adjust.method = "fdr" ,keep_significant_only = F) 

plot_cpdb(cell_type1 = 'CD|B|FC', cell_type2 = 'Luminal', scdata = acc_cancer_cd45_caf,
    idents = 'cell_type', means = means, pvals = pvals,
  genes = c("JAG", "MYB" , "NOTCH","HES1","HEY"),return_table = F,max_size = 4,p.adjust.method = "fdr" ,keep_significant_only = F) 

NA
NA