CellChat 三部曲3：具有不同细胞类型成分的多个数据集的细胞通讯比较分析

library(CellChat)
library(ggplot2)                  
library(patchwork)
library(igraph)

cellchat.E13 <- readRDS(url("https://ndownloader.figshare.com/files/25957094"))
cellchat.E13 <- updateCellChat(cellchat.E13)
#> Update slot 'var.features' from a vector to a list
cellchat.E14 <- readRDS(url("https://ndownloader.figshare.com/files/25957634"))
cellchat.E14 <- updateCellChat(cellchat.E14)
#> Update slot 'var.features' from a vector to a list

# Define the cell labels to lift up
group.new = levels(cellchat.E14@idents)
cellchat.E13 <- liftCellChat(cellchat.E13, group.new)
#> The CellChat object will be lifted up using the cell labels FIB-A, FIB-B, FIB-P, DC, Pericyte, MYL, Immune, ENDO, Muscle, MELA, Basal-P, Basal, Spinious
#> Update slots object@net, object@netP, object@idents in a single dataset...
object.list <- list(E13 = cellchat.E13, E14 = cellchat.E14)
cellchat <- mergeCellChat(object.list, add.names = names(object.list), cell.prefix = TRUE)
#> Warning in mergeCellChat(object.list, add.names = names(object.list),
#> cell.prefix = TRUE): Prefix cell names!
#> Merge the following slots: 'data.signaling','net', 'netP','meta', 'idents', 'var.features' , 'DB', and 'LR'.

# Hierarchy plot
pathways.show <- c("WNT") 
weight.max <- getMaxWeight(object.list, slot.name = c("netP"), attribute = pathways.show) # control the edge weights across different datasets
vertex.receiver = seq(1,10) # Left portion of hierarchy plot the shows signaling to dermal cells and right portion shows signaling to epidermal cells
par(mfrow = c(1,2), xpd=TRUE)
for (i in 1:length(object.list)) {
  netVisual_aggregate(object.list[[i]], signaling = pathways.show, vertex.receiver = vertex.receiver, edge.weight.max = weight.max[1], edge.width.max = 10, signaling.name = paste(pathways.show, names(object.list)[i]))
}

# Circle plot
pathways.show <- c("WNT") 
weight.max <- getMaxWeight(object.list, slot.name = c("netP"), attribute = pathways.show) # control the edge weights across different datasets
par(mfrow = c(1,2), xpd=TRUE)
for (i in 1:length(object.list)) {
  netVisual_aggregate(object.list[[i]], signaling = pathways.show, layout = "circle", edge.weight.max = weight.max[1], edge.width.max = 10, signaling.name = paste(pathways.show, names(object.list)[i]))
}

# Chord diagram
pathways.show <- c("WNT") 
par(mfrow = c(1,2), xpd=TRUE)
for (i in 1:length(object.list)) {
  netVisual_aggregate(object.list[[i]], signaling = pathways.show, layout = "chord", signaling.name = paste(pathways.show, names(object.list)[i]))
}
#> Note: The second link end is drawn out of sector 'Basal-P'.
#> Note: The second link end is drawn out of sector 'FIB-A'.

# Chord diagram
group.merged <- c(rep("Dermal", 10), rep("Epidermal", 3)) # grouping cell clusters into dermal and epidermal cells to study the cell-cell communication between dermal and epidermal
names(group.merged) <- levels(object.list[[1]]@idents)
pathways.show <- c("WNT") 
par(mfrow = c(1,2), xpd=TRUE)
for (i in 1:length(object.list)) {
  netVisual_chord_cell(object.list[[i]], signaling = pathways.show, group = group.merged, title.name = paste0(pathways.show, " signaling network - ", names(object.list)[i]))
}
#> Plot the aggregated cell-cell communication network at the signaling pathway level
#> Note: The second link end is drawn out of sector 'Basal-P'.
#> Plot the aggregated cell-cell communication network at the signaling pathway level
#> Note: The second link end is drawn out of sector 'FIB-A'.