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10_cellchat_sender_receiver.R
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################################################################################################################################################
# Cellchat downstream analysis
# obtaining pathways, cell types, DEGs, sender, reciever, pvalues,contribution degree
########################################################################
# pathways, DEGs , LR pairs
########################################################################
locations<-c("CAM" , "PVBP")
conditions<-c("TIL" ,"TNL")
cell.type.annotation<-read_tsv("cell.type.annotation.v2.tsv")
#rownames(cell.type.annotation)<-NULL
clust2Names<-cell.type.annotation$Potential.final #c("Stromal-1","Macrophage-2","Macrophage-1","Endothelial-1","Monocyte","CD4_T-cell","Decidual","CD8_T-cell","LED","Stromal-2","ILC","NK-cell","Smooth muscle cells-1","Stromal Fibroblast","Macrophage-3","Endothelial-2","DC","Smooth muscle cells-2","EVT","Plasmablast","Smooth muscle cells","Macrophage-4","B-cell","Unciliated Epithelial")
clust2Names<-paste0(cell.type.annotation$Cluster,":",clust2Names)
names(clust2Names)<-as.character(cell.type.annotation$Cluster)
res <- read_tsv("./7_outputs_DESeq_ConditionsByCluster_with_covidcontrol_res1.0_library/ALL.combined.2022-03-29.tsv")
res<-res %>% filter(padj<0.1)
res <- res %>% separate(cname,c("Location","Cell_type","Origin"),sep="_",remove=FALSE)
res$Cell_type<-clust2Names[res$Cell_type]
celltype_DE<-table(res$Cell_type,res$Location)
res$cname<-paste(res$Cell_type,res$Origin,sep="_")
pathways_genes_celltypes_db_final<-lapply(locations, function(xlocation){
subFolder<-xlocation
system(paste0("mkdir -p ", outFolder,subFolder,"/"))
#pathways_genes_celltypes_db_list<-lapply (conditions ,function(xcondition){
pathways_genes_celltypes_db_list<-list()
for (i in 1:length(conditions)){
xcondition<-conditions[i]
cellchat<-read_rds(paste0("./10_CellChat_analysis_withcovidcontrol_origin_or_500/","cellchat_",xlocation,"_",xcondition,"_","2022-06-01",".rds"))
pathways<-cellchat@netP$pathways
groupSize <- as.numeric(table(cellchat@idents))
system(paste0("mkdir -p ", outFolder,subFolder,"/",xcondition,"/"))
print(paste0("mkdir -p ", outFolder,subFolder,"/",xcondition,"/"))
pathways_genes_celltypes<-lapply(pathways,function(x){
pairLR <- extractEnrichedLR(cellchat, signaling = x, geneLR.return = FALSE)
LR_genes<-unique(unlist(str_split(pairLR$interaction_name,"_")))
#LR_genes<-tolower(LR_genes)
celltypes<-res %>% filter(gene_name %in% LR_genes & Location== xlocation)%>% dplyr::select(Cell_type)%>% unlist %>% unique()
LR_DEGs <-res %>% filter (gene_name %in% LR_genes& Location== xlocation) %>% dplyr::select(gene_name)%>% unlist %>% unique()
LR_DEGs_len<-length(LR_DEGs)
LR_DEGs<-paste(LR_DEGs,collapse = ", ")
LR_genes<-paste(LR_genes,collapse = ", ")
celltype_len<-length(celltypes)
celltypes<-paste(celltypes,collapse = ", ")
if (celltypes=="") celltypes<-"NA"
return(c(x,LR_genes,LR_DEGs,celltypes,celltype_len,LR_DEGs_len))
})
pathways_genes_celltypes_db<-do.call(rbind,pathways_genes_celltypes)
pathways_genes_celltypes_db<-as.data.frame(pathways_genes_celltypes_db)
print(xcondition)
pathways_genes_celltypes_db$condition<-xcondition
pathways_genes_celltypes_db$location<-xlocation
colnames(pathways_genes_celltypes_db)<-c("Pathway","Genes_in_pathway","DEGs_in_pathway","Celltype","celltype_len","LR_DEGs_len","Condition","Location")
pathways_genes_celltypes_db_list[[i]]<-pathways_genes_celltypes_db
#return(pathways_genes_celltypes_db)
} #)
pathways_genes_celltypes_db<-do.call(rbind,pathways_genes_celltypes_db_list)
return(pathways_genes_celltypes_db)
})
pathways_genes_celltypes_db<-do.call(rbind,pathways_genes_celltypes_db_final)
pathways_genes_celltypes_db<-pathways_genes_celltypes_db[order(as.numeric(pathways_genes_celltypes_db$celltype_len),decreasing = TRUE),]
write.csv(pathways_genes_celltypes_db,file=paste0(outFolder,"pathways_genes_celltypes_db.csv"))
write_rds(pathways_genes_celltypes_db,file=paste0(outFolder,"pathways_genes_celltypes_db.rds"))
########################################################################
# pathways, information flow
########################################################################
informationflow_list<-lapply(locations,function(xlocation){
subFolder<-xlocation
system(paste0("mkdir -p ", outFolder,subFolder,"/"))
# cellchat_TNL<-cellchat_TNL_original<-read_rds(paste0("./10_CellChat_analysis_withcovidcontrol_origin_500/","cellchat_",xlocation,"_","TNL","_","2022-05-06",".rds"))
# cellchat_TIL<-cellchat_TIL_original<-read_rds(paste0("./10_CellChat_analysis_withcovidcontrol_origin_500/","cellchat_",xlocation,"_","TIL","_","2022-05-06",".rds"))
#
cellchat_TNL<-cellchat_TNL_original<-read_rds(paste0("./10_CellChat_analysis_withcovidcontrol_origin_or_500/","cellchat_",xlocation,"_","TNL","_","2022-06-01",".rds"))
cellchat_TIL<-cellchat_TIL_original<-read_rds(paste0("./10_CellChat_analysis_withcovidcontrol_origin_or_500/","cellchat_",xlocation,"_","TIL","_","2022-06-01",".rds"))
pathways_TNL<-cellchat_TNL_original@netP$pathways
controls<-cbind(pathways_TNL, rep("TNL",length(pathways_TNL)))
controls<-as.data.frame(controls)
colnames(controls)<-c("pathway","TNL")
pathways_TIL<-cellchat_TIL_original@netP$pathways
TILs<-cbind(pathways_TIL, rep("TIL",length(pathways_TIL)))
TILs<-as.data.frame(TILs)
colnames(TILs)<-c("pathway","TIL")
allpathways<-TILs %>% full_join(controls)
allpathways<-allpathways %>% arrange(desc(!is.na(TNL),(!is.na(TIL))))
write.csv(allpathways,file=paste0(outFolder,subFolder,"/","pathways_",xlocation,".csv"))
shared_pathways<-intersect(pathways_TNL,pathways_TIL)
pathways_TNL_only<-pathways_TNL[!pathways_TNL %in% pathways_TIL]
pathways_TIL_only<-pathways_TIL[! pathways_TIL %in% pathways_TNL]
# there is an additional population 30_B cell specific to cellchat_TNL compared to TIL
# we lift up Ecoli by lifting up the cell groups to the same cell labels as cellchat_TNL
control_cells<-rownames(cellchat_TNL@net$prob)
TIL_cells<-rownames(cellchat_TIL@net$prob)
TIL_cells_only<-TIL_cells [!TIL_cells %in%control_cells ]
control_cells_only<-control_cells [! control_cells %in%TIL_cells ]
if (length(TIL_cells_only)==0)
{
group.new = levels(cellchat_TNL@idents)
cellchat_TIL <- liftCellChat(cellchat_TIL, group.new)
}else if (length(control_cells_only)==0){
group.new = levels(cellchat_TIL@idents)
cellchat_TNL <- liftCellChat(cellchat_TNL, group.new)} else
{
group.new = union(levels( cellchat_TIL@idents), levels(cellchat_TNL@idents))
cellchat_TNL <- liftCellChat(cellchat_TNL, group.new)
cellchat_TIL <- liftCellChat(cellchat_TIL, group.new)
}
# now merge
object.list <- list(TNL = cellchat_TNL, TIL = cellchat_TIL)
cellchat <- mergeCellChat(object.list, add.names = names(object.list))
#pdf(paste0(outFolder,subFolder,"/","informationflow_",xlocation,".pdf"),width=10,height=18)
#gg1 <- rankNet(cellchat, mode = "comparison", stacked = T, do.stat = TRUE)
gg2 <- rankNet(cellchat, mode = "comparison", stacked = F, do.stat = TRUE,color.use=c("#333399","#A50021"),font.size=15)
# gg2
# dev.off()
data<-gg2$data
colnames(data)<-c("Pathway","contribution","contribution.scaled","Condition","contribution.relative.1","pvalues" )
data$Location<-xlocation
#data$Condition[which(data$Condition=="Control")]<-"control"
data<-data %>% dplyr::select(Pathway,Location,Condition,contribution,contribution.scaled,pvalues)
return (data)
})
informationflow_data<-do.call(rbind,informationflow_list)
write.csv(informationflow_data,file=paste0(outFolder,"informationflow_data.csv"))
write_rds(informationflow_data,paste0(outFolder,"informationflow_data.rds"))
#informationflow_data<-read_csv("10_CellChat_analysis_withcovidcontrol_500_v2_plots/informationflow_data.rds")
#informationflow_data$Condition<-tolower(informationflow_data$Condition)
#pathways_genes_celltypes_db$Condition<-tolower(pathways_genes_celltypes_db$Condition)
informationflow_data$Pathway<-as.character(informationflow_data$Pathway)
informationflow_data$Condition<-as.character(informationflow_data$Condition)
informationflow_data$Location<-as.character(informationflow_data$Location)
pathways_genes_celltypes_contribution<-pathways_genes_celltypes_db %>% left_join(informationflow_data)
write.csv(pathways_genes_celltypes_contribution,file=paste0(outFolder,"pathways_genes_celltypes_contribution.csv"))
write_rds(pathways_genes_celltypes_contribution,file=paste0(outFolder,"pathways_genes_celltypes_contribution.rds"))
outFolder="10_CellChat_analysis_withcovidcontrol_origin_500_or_plots/"
#10_CellChat_analysis_withcovidcontrol_origin_500_plots
system(paste0("mkdir -p ", outFolder))
cell.type.annotation<-read_tsv("cell.type.annotation.v2.tsv")
#rownames(cell.type.annotation)<-NULL
clust2Names<-cell.type.annotation$Potential.final #c("Stromal-1","Macrophage-2","Macrophage-1","Endothelial-1","Monocyte","CD4_T-cell","Decidual","CD8_T-cell","LED","Stromal-2","ILC","NK-cell","Smooth muscle cells-1","Stromal Fibroblast","Macrophage-3","Endothelial-2","DC","Smooth muscle cells-2","EVT","Plasmablast","Smooth muscle cells","Macrophage-4","B-cell","Unciliated Epithelial")
clust2Names<-paste0(cell.type.annotation$Cluster,":",clust2Names)
names(clust2Names)<-as.character(cell.type.annotation$Cluster)
# cluster.Colors<-cell.type.annotation$color
# names(cluster.Colors)<-clust2Names
################################
# cells with sending role (from cellchat)
################################
locations<-c("CAM" , "PVBP")
conditions<-c("TIL" ,"TNL")
####################################################
####################################################
data_list<-lapply(locations, function(xlocation){
data_list<-lapply (conditions ,function(xcondition){
#cellchat<-read_rds(paste0("./10_CellChat_analysis_withcovidcontrol_origin_500/","cellchat_",xlocation,"_",xcondition,"_","2022-05-06",".rds"))
cellchat<-read_rds(paste0("./10_CellChat_analysis_withcovidcontrol_origin_or_500/","cellchat_",xlocation,"_",xcondition,"_2022-06-01.rds"))
pathways<-cellchat@netP$pathways
groupSize <- as.numeric(table(cellchat@idents))
nPatterns<-3 #
cellchat <- identifyCommunicationPatterns(cellchat, pattern = "outgoing", k = nPatterns)
cellchat <- identifyCommunicationPatterns(cellchat, pattern = "incoming", k = nPatterns)
cutoff<-0.70
############################################################################
# outgoing data
############################################################################
outgoing_signaling<-cellchat@netP$pattern$outgoing$pattern$signaling
outgoing_signaling<-outgoing_signaling %>% filter(Contribution>cutoff)
colnames(outgoing_signaling)[3]<-"Contribution_outgoing_signaling"
colnames(outgoing_signaling)[1]<-paste0(colnames(outgoing_signaling)[1],"_outgoing")
outgoing_cell<-cellchat@netP$pattern$outgoing$pattern$cell
outgoing_cell<-outgoing_cell %>% filter(Contribution>cutoff)
colnames(outgoing_cell)[3]<-"Contribution_outgoing_cell"
colnames(outgoing_cell)[2]<-paste0(colnames(outgoing_cell)[2],"_outgoing")
outgoing_data<-outgoing_signaling %>% inner_join(outgoing_cell)
#outgoing_data<-outgoing_data %>% filter(Signaling %in% selected_pathways)
############################################################################
# incoming data
############################################################################
incoming_signaling<-cellchat@netP$pattern$incoming$pattern$signaling
incoming_signaling<-incoming_signaling %>% filter(Contribution>cutoff)
#incoming_signaling$Contribution[incoming_signaling$Contribution < cutoff] <- 0
colnames(incoming_signaling)[3]<-"Contribution_incoming_signaling"
colnames(incoming_signaling)[1]<-paste0(colnames(incoming_signaling)[1],"_incoming")
incoming_cell<-cellchat@netP$pattern$incoming$pattern$cell
incoming_cell<-incoming_cell %>% filter(Contribution>cutoff)
#incoming_cell$Contribution[incoming_cell$Contribution < cutoff] <- 0
colnames(incoming_cell)[3]<-"Contribution_incoming_cell"
colnames(incoming_cell)[2]<-paste0(colnames(incoming_cell)[2],"_incoming")
incoming_data<-incoming_signaling %>% inner_join(incoming_cell)
#incoming_data<-incoming_data %>% filter(Signaling %in% selected_pathways)
#outgoing_data<-outgoing_data %>% filter(Signaling %in% selected_pathways)
outgoing_data<-outgoing_data %>% mutate(CellGroup_outgoing=CellGroup)#,Signaling,Contribution-outgoing_cell,Contribution_outgoing_signaling)
incoming_data<-incoming_data %>% mutate(CellGroup_incoming=CellGroup)#,Signaling,Contribution_incoming_signal,Contribution_incoming_cell)
signalins_incoming<-unique(incoming_data$Signaling)
outgoing_incoming<-unique(outgoing_data$Signaling)
overlap_signalings<-intersect(signalins_incoming,outgoing_incoming)
# summary
majorcells<-rowSums(table(outgoing_data$CellGroup,outgoing_data$Signaling))
majorcells<-majorcells[order(majorcells,decreasing = TRUE)]
majorsignalings<-rowSums(table(outgoing_data$Signaling,outgoing_data$Contribution_outgoing_signaling))
majorsignalings<-majorsignalings[order(majorsignalings,decreasing = TRUE)]
major_cell_signaling<-list(majorcells,majorsignalings)
names(major_cell_signaling)<-c("majorcells","majorsignalings")
outgoing_data$Signaling<-as.character(outgoing_data$Signaling)
outgoing_data<-outgoing_data[order(outgoing_data$Signaling,decreasing = FALSE),]
outgoing_data$Signaling <- factor(outgoing_data$Signaling,levels=unique(outgoing_data$Signaling))
total_signalings<-unique(c(incoming_data$Signaling, outgoing_data$Signaling))
incoming_data_df<-incoming_data %>% dplyr::select(Signaling,CellGroup_incoming)
outgoing_data_df<-outgoing_data %>% dplyr::select(Signaling,CellGroup_outgoing)
data<-incoming_data_df %>% full_join (outgoing_data_df)
data$Location<-xlocation
data$Condition<-xcondition
return(data)
})
data<-do.call(rbind,data_list)
return(data)
})
data<-do.call(rbind,data_list)
data$signaling_Location_condition<-paste0(data$Signaling,"_",data$Location,"_",data$Condition)
senders<-sapply(unique(data$signaling_Location_condition), function(x)
{
sender<-data$CellGroup_outgoing[which(data$signaling_Location_condition==x)]
sender<-as.character(sender)
sender<-unique(sender)
sender<-paste(sender,collapse = ", ")
sender
})
receivers<-sapply(unique(data$signaling_Location_condition), function(x)
{
sender<-data$CellGroup_incoming[which(data$signaling_Location_condition==x)]
sender<-as.character(sender)
sender<-unique(sender)
sender<-paste(sender,collapse = ", ")
sender
})
data<-data.frame(unique(data$signaling_Location_condition),senders,receivers)
data<-data %>% separate(unique.data.signaling_Location_condition.,c("Pathway","Location","Condition"),sep="_",remove=FALSE)
#data<-data %>% dplyr::select(Pathway=Signaling,Location,Condition,senders,receivers)
pathways_genes_celltypes_contribution<-read_rds("10_CellChat_analysis_withcovidcontrol_origin_500_or_plots/pathways_genes_celltypes_contribution.rds")
#pathways_genes_celltypes_contribution<-read_rds("10_CellChat_analysis_withcovidcontrol_200_v2_plots/pathways_genes_celltypes_contribution.rds")
pathways_genes_celltypes_db<-pathways_genes_celltypes_contribution %>% left_join(data)
write.csv(pathways_genes_celltypes_db,file = paste0(outFolder,"pathways_genes_celltypes_sender_receiver_outgoingincoming_cutoff.csv"))
write_rds(pathways_genes_celltypes_db,file = paste0(outFolder,"pathways_genes_celltypes_sender_receiver_outgoingincoming_cutoff.rds"))
########################################################################################################################
# Based on outdegree and indegree cut off
########################################################################################################################
senders_list<-lapply(locations, function(xlocation){
#subFolder<-xlocation
#system(paste0("mkdir -p ", outFolder,subFolder,"/"))
#pathways_genes_celltypes_db_list<-lapply (conditions ,function(xcondition){
senders_list<-lapply(conditions,function(xcondition){
cellchat<-read_rds(paste0("./10_CellChat_analysis_withcovidcontrol_200/","cellchat_",xlocation,"_",xcondition,"_","2022-04-07",".rds"))
cellchat <- netAnalysis_computeCentrality(cellchat, slot.name = "netP")
pathways<-cellchat@netP$pathways
senders<-lapply(pathways,function(x){
scores<-cellchat@netP$centr[[x]]$outdeg
minx<-min(scores)
maxx<-max(scores)
scores_scaled<-sapply( scores, function(x){(x-minx)/(maxx-minx)})
senders<-names(scores_scaled)[which(scores_scaled>=0.75)]
roles<-rep("sender",length(senders))
path<-rep(x,length(senders))
return(cbind(senders,roles,path))
})
senders_df<-do.call(rbind,senders)
senders_df<-as.data.frame(senders_df)
senders_df$Condition<-xcondition
senders_df
})
senders_df<-do.call(rbind,senders_list)
senders_df<-as.data.frame(senders_df)
senders_df$Location<-xlocation
return (senders_df)
})
sender_df<-do.call(rbind,senders_list)
################################
# cells with receiving role (from cellchat)
################################
receivers_list<-lapply(locations, function(xlocation){
#subFolder<-xlocation
#system(paste0("mkdir -p ", outFolder,subFolder,"/"))
#pathways_genes_celltypes_db_list<-lapply (conditions ,function(xcondition){
receivers_list<-lapply(conditions,function(xcondition){
cellchat<-read_rds(paste0("./10_CellChat_analysis_withcovidcontrol_200/","cellchat_",xlocation,"_",xcondition,"_","2022-04-07",".rds"))
cellchat <- netAnalysis_computeCentrality(cellchat, slot.name = "netP")
pathways<-cellchat@netP$pathways
receivers<-lapply(pathways,function(x){
scores<-cellchat@netP$centr[[x]]$indeg
minx<-min(scores)
maxx<-max(scores)
scores_scaled<-sapply( scores, function(x){(x-minx)/(maxx-minx)})
receivers<-names(scores_scaled)[which(scores_scaled>=0.75)]
roles<-rep("receiver",length(receivers))
path<-rep(x,length(receivers))
return(cbind(receivers,roles,path))
})
receivers_df<-do.call(rbind,receivers)
receivers_df<-as.data.frame(receivers_df)
receivers_df$Condition<-xcondition
receivers_df
})
receivers_df<-do.call(rbind,receivers_list)
receivers_df<-as.data.frame(receivers_df)
receivers_df$Location<-xlocation
return (receivers_df)
})
receiver_df<-do.call(rbind,receivers_list)
################################
# merging sender/receiever cells
################################
colnames(sender_df)[1:3]<-c("Celltype","role","Pathway")
colnames(receiver_df)[1:3]<-c("Celltype","role","Pathway")
receiver_senders_df<-rbind(sender_df,receiver_df)
#colnames(receiver_senders_df)<-c("celltype","role","pathway")
receiver_senders_df<-receiver_senders_df[!duplicated(receiver_senders_df), ]
#receiver_senders_df<-receiver_senders_df[order(receiver_senders_df$pathway,decreasing = FALSE),]
#receiver_senders_df<-as.data.frame(receiver_senders_df)
receiver_senders_df<-receiver_senders_df %>% arrange(Pathway)
#write.csv(receiver_senders_df,file=paste0(outFolder,"receiver_senders_df.csv"))
write.csv(receiver_senders_df,file=paste0(outFolder,"receiver_senders_degree_0.75_df.csv"))
sender_receiver_columns<-sapply(1: nrow(pathways_genes_celltypes_db), function(x){
path<-pathways_genes_celltypes_db$Pathway[x]
celltypes<-pathways_genes_celltypes_db$Celltype[x]
celltypes<-unlist(strsplit(celltypes,", ",fixed=TRUE))
location<-pathways_genes_celltypes_db$Location[x]
condition<-pathways_genes_celltypes_db$Condition[x]
senders<- receiver_senders_df %>% filter (Pathway==path & role=="sender" & Location==location & Condition==condition) %>% select(Celltype)%>% unlist %>% unique
receivers<-receiver_senders_df %>% filter (Pathway==path & role=="receiver" & Location==location & Condition==condition) %>% select(Celltype)%>% unlist %>% unique
senders<-paste(senders,collapse = ", ")
receivers<-paste(receivers,collapse = ", ")
if (senders=="") senders<-"NA"
if (receivers=="") receivers<-"NA"
return(c(senders,receivers,location,condition,path))
})
################################
# make the final data frame
################################
sender_receiver_columns<-t(sender_receiver_columns)
sender_receiver_columns<-as.data.frame(sender_receiver_columns)
colnames(sender_receiver_columns)<-c("senders","receivers","Location","Condition","Pathway")
pathways_genes_celltypes_db<-pathways_genes_celltypes_contribution %>% left_join(sender_receiver_columns)
write.csv(pathways_genes_celltypes_db,file = paste0(outFolder,"pathways_genes_celltypes_sender_receiver_cutoffdegree.csv"))
write_rds(pathways_genes_celltypes_db,file = paste0(outFolder,"pathways_genes_celltypes_db.rds"))