3 Cell-cell communication

3.1 Input

The runCellChat() function requires a SingleCellExperiment object that includes cell clustering information. For details, refer to the Clustering session.

The group parameter should reference a variable within the SingleCellExperiment object that holds the clustering data.

Users can add their own clustering using the following commands:

colData(sce)$group_name <- group
# OR
sce[["group_name"]] <- group

3.2 CellChat

Wrapper function for CellChat¹.

library(sclet)
library(aplot)

# use demo data from CellChat, hmskin_sce
sce <- qs::qread("data/hmskin_sce.qs")
cci_obj <- runCellChat(sce, group = "labels")

## [1] "Create a CellChat object from a data matrix"

## Set cell identities for the new CellChat object 
## The cell groups used for CellChat analysis are  APOE+ FIB, FBN1+ FIB, COL11A1+ FIB, Inflam. FIB, cDC1, cDC2, LC, Inflam. DC, TC, Inflam. TC, CD40LG+ TC, NKT 
## The number of highly variable ligand-receptor pairs used for signaling inference is 693 
## triMean is used for calculating the average gene expression per cell group. 
## [1] ">>> Run CellChat on sc/snRNA-seq data <<< [2024-10-09 15:14:23.501698]"
## [1] ">>> CellChat inference is done. Parameter values are stored in `object@options$parameter` <<< [2024-10-09 15:16:06.048892]"

3.3 visulization

groupSize <- as.numeric(table(cci_obj@idents))
plot_list(
    ~CellChat::netVisual_circle(cci_obj@net$count, 
        vertex.weight = groupSize, weight.scale = T, 
        label.edge= F, title.name = "Number of interactions"),
    ~CellChat::netVisual_circle(cci_obj@net$weight, 
        vertex.weight = groupSize, weight.scale = T, 
        label.edge= F, title.name = "Interaction weights/strength")
)

pathways.show <- c("CXCL") 
vertex.receiver = seq(1,4) 
# CellChat::netVisual_aggregate(cci_obj, signaling = pathways.show,  vertex.receiver = vertex.receiver)
CellChat::netVisual_aggregate(cci_obj, signaling = pathways.show, layout = "circle")

CellChat::netVisual_aggregate(cci_obj, signaling = pathways.show, layout = "chord")

CellChat::netVisual_heatmap(cci_obj, signaling = pathways.show, color.heatmap = "Reds")

group.cellType <- c(rep("FIB", 4), rep("DC", 4), rep("TC", 4)) # grouping cell clusters into fibroblast, DC and TC cells
names(group.cellType) <- levels(cci_obj@idents)
CellChat::netVisual_chord_cell(cci_obj, signaling = pathways.show, group = group.cellType, title.name = paste0(pathways.show, " signaling network"))

CellChat::netAnalysis_contribution(cci_obj, signaling = pathways.show)

pairLR.CXCL <- CellChat::extractEnrichedLR(cci_obj, signaling = pathways.show, geneLR.return = FALSE)
LR.show <- pairLR.CXCL[1,] 
vertex.receiver = seq(1,4)
# CellChat::netVisual_individual(cci_obj, signaling = pathways.show,  pairLR.use = LR.show, vertex.receiver = vertex.receiver)
CellChat::netVisual_individual(cci_obj, signaling = pathways.show, pairLR.use = LR.show, layout = "circle")

## [[1]]

CellChat::netVisual_individual(cci_obj, signaling = pathways.show, pairLR.use = LR.show, layout = "chord")

## [[1]]

CellChat::netVisual_bubble(cci_obj, sources.use = 4, targets.use = c(5:11), remove.isolate = FALSE)

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1. https://htmlpreview.github.io/?https://github.com/jinworks/CellChat/blob/master/tutorial/CellChat-vignette.html#c-starting-from-a-singlecellexperiment-object↩︎