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CCI.R
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library(circlize)
### CCI analysis
### ligand-receptor list
### https://baderlab.org/CellCellInteractions
CCI_list <- read_csv("CCI_list.csv")
CCIgene <- read_csv("CCIgene.csv")
Chemo = CCI_list[CCI_list$AliasA %in% unlist(CCIgene),]
uni.chemo = list(Chemo[,1], Chemo[,2])
uni.chemo = unique(unlist(uni.chemo))
ALVCCI = ALV[uni.chemo,]
BROCCI = BRO[uni.chemo,]
IMMCCI = IMM[uni.chemo,]
## Reconstruction of object
new.cluster.ids <- c("AE2-1", "AE1-1", "AE2-2", "AE2-3", "AE2-4", "AE1-2", "AE1-3", "AE(2-5(Inflammation)", "AE2-6", "AE2-7")
names(new.cluster.ids) <- levels(ALVCCI)
ALVCCI <- RenameIdents(ALVCCI, new.cluster.ids)
new.cluster.ids <- c("Ciliated-1", "Ciliated-2", "Club1(AQP5+, SCGB1A1+)", "Intermediate(Ciliated, Club)", "Club(MUC5+, MUC5AC+)", "Club(SCCB1A1 high, MUC5-, MUC5AC-)", "Ciliated-3", "Basal")
names(new.cluster.ids) <- levels(BROCCI)
BROCCI <- RenameIdents(BROCCI, new.cluster.ids)
new.cluster.ids <- c("T-Cell", "NK", "CD8T", "Neutrophil-1", "Macrophage-1", "MastCell-1", "MT-1", "Macrophage-2", "Myeloid-DC", "Neutrophil-2", "MT-2", "NaiveB",
"MemoryB", "Plasmacytoid DC", "MastCell-2", "Macrophage-3")
names(new.cluster.ids) <- levels(IMMCCI)
IMMCCI <- RenameIdents(IMMCCI, new.cluster.ids)
CCImerge = merge(IMMCCI, c(ALVCCI, BROCCI))
### extraction of high expreesed genes ( > 2 )
unigenes = rownames(CCImerge)
mel = list()
for(i in 1: length(unigenes)){
expr <- FetchData(object = CCImerge, vars = unigenes[i])
if(any(expr > 2) >= 1){
ge = CCImerge[, which(x = expr > 2)]
ge = table(ge@active.ident)
ho = melt(ge)
ho = mutate(ho, Gene = unigenes[i])
mel = rbind(mel, ho)
}else{
print(unigenes[i])
}
}
### Convert to expressed cell ratio in the subpopulations
### Construct matrix
tocell = table(CCImerge@active.ident)
Ratiomel = list()
for(i in 1:length(tocell)){
cell = names(tocell[i])
LS = mel[mel[,1] == cell,]
LS[,2] = LS[,2]/tocell[i]
Ratiomel = rbind(Ratiomel, LS)
}
Ratiomel = dcast(Ratiomel, Var1 ~ Gene, value.var = "value")
write.table(Ratiomel, file = "CCI-RatioMAT.txt", sep = " ")
A = list()
B = list()
CCItotal = list()
CCI_perlist = Chemo[Chemo$AliasA %in% unlist(unique(mel[,3])),]
CCI_perlist = CCI_perlist[CCI_perlist$AliasB %in% unlist(unique(mel[,3])),]
CCI_perlist = mutate(CCI_perlist, merge = paste(CCI_perlist$AliasA, CCI_perlist$AliasB, sep = "|"))
unique(list(paste(CCI_perlist$AliasA, CCI_perlist$AliasB, sep = "|")))
ratiomelt = na.omit(melt(Ratiomel))
ratiomelt = ratiomelt[ratiomelt$value > 0.1,]
CCI_perlist = Chemo[Chemo$AliasA %in% unlist(unique(ratiomelt[,2])),]
CCI_perlist = CCI_perlist[CCI_perlist$AliasB %in% unlist(unique(ratiomelt[,2])),]
CCI_perlist = mutate(CCI_perlist, merge = paste(CCI_perlist$AliasA, CCI_perlist$AliasB, sep = "&"))
a = as.character(unique(CCI_perlist$merge))
CCI_perlist = CCI_perlist[CCI_perlist$merge %in% unique(CCI_perlist$merge),]
CCI_perlist = subset(CCI_perlist, CCI_perlist$merge %in% a)
a = unique(CCI_perlist$merge)
aa = str_split(a, "&", n = 2, simplify = TRUE)
CCI_perlist = data.frame(L = aa[,1], R = aa[,2], merge = unique(CCI_perlist$merge))
CCI_perlist = CCI_perlist[!(as.character(CCI_perlist$L) == as.character(CCI_perlist$R)),]
CCItotal = list()
for(i in 1:nrow(CCI_perlist)){
geneset = CCI_perlist[i,]
Ligand = as.character(unlist(geneset[1]))
Receptor = as.character(unlist(geneset[2]))
LigCCI = ratiomelt[ratiomelt$variable == Ligand, ]
ResCCI = ratiomelt[ratiomelt$variable == Receptor, ]
for(k in 1:nrow(LigCCI)){
Lig = LigCCI[k,3]
score = lapply(ResCCI$value, function(x){x * Lig})
Res = data.frame( CCIscore = unlist(score), Recepter.Cell = ResCCI$Var1)
Res = mutate(Res, Ligand.Cell = LigCCI[k,1], CCI = geneset)
CCItotal = bind_rows(CCItotal, Res)
}
}
CCItotal = CCItotal[CCItotal$Recepter.Cell != c("MT-1") & CCItotal$Ligand.Cell != c("MT-1"),]
CCItotal = CCItotal[CCItotal$Recepter.Cell != c("MT-2") & CCItotal$Ligand.Cell != c("MT-2"),]
GroupA = c(unlist(as.character(unique(ALVCCI@active.ident))), unlist(as.character(unique(BROCCI@active.ident))))
GroupB = c(unlist(as.character(unique(IMMCCI@active.ident))))
AtoB = CCItotal[CCItotal$Ligand.Cell %in% GroupA & CCItotal$Recepter.Cell %in% GroupB,]
BtoA = CCItotal[CCItotal$Ligand.Cell %in% GroupB & CCItotal$Recepter.Cell %in% GroupA,]
LigA = unlist(as.character(unique(AtoB$Ligand.Cell)))
AtoB.CCI = list()
for(i in 1:length(LigA)){
G <- LigA[i]
set = AtoB[AtoB$Ligand.Cell == G, ]
CELLset = unique(set$Recepter.Cell)
for(k in 1:length(CELLset)){
R <- CELLset[k]
REset <- set[set$Recepter.Cell == R, ]
CCIsum <- sum(REset$CCIscore)
DF = data.frame(LigandCell = G, ReceptorCell = R, CCIscore.sum = CCIsum)
AtoB.CCI = rbind(AtoB.CCI, DF)
}
}
LigB = unlist(as.character(unique(BtoA$Ligand.Cell)))
BtoA.CCI = list()
for(i in 1:length(LigB)){
G <- LigB[i]
set = BtoA[BtoA$Ligand.Cell == G, ]
CELLset = unique(set$Recepter.Cell)
for(k in 1:length(CELLset)){
R <- CELLset[k]
REset <- set[set$Recepter.Cell == R, ]
CCIsum <- sum(REset$CCIscore)
DF = data.frame(LigandCell = G, ReceptorCell = R, CCIscore.sum = CCIsum)
BtoA.CCI = rbind(BtoA.CCI, DF)
}
}
write.table(AtoB, file = "CCI-interaction-score-AtoB.txt", sep = " ")
write.table(BtoA, file = "CCI-interaction-score-BtoA.txt", sep = " ")
write.table(AtoB.CCI, file = "CCI-interaction-score-AtoB-CELL.txt", sep = " ")
write.table(BtoA.CCI, file = "CCI-interaction-score-BtoA-CELL.txt", sep = " ")
### Draw circos plot
#> head(data)
# LigandCell ReceptorCell CCIscore.sum
#1 Arteries_EC AT1-1 0.5523612
#2 Arteries_EC AT2-7 0.3719545
#3 Arteries_EC AT1-2 0.6276795
#4 Arteries_EC AT2-6 0.2278950
#5 Arteries_EC Ciliated-2 0.5344556
#6 Arteries_EC AT1-3 0.4777029
chordDiagram(data, col = ifelse(data$CCIscore.sum > 0, "red", "blue"))