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cellchat_Mga_KO.R
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cellchat_Mga_KO.R
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library(CellChat)
library(patchwork)
options(stringsAsFactors = FALSE)
library(reticulate)
adata <- import("anndata", convert = FALSE)
adata_object <- adata$read_h5ad('C:/Users/hyjfo/Documents/Mga_cellchat_test.h5ad')
# access normalized data matrix
data.input <- t(py_to_r(adata_object$X))
rownames(data.input) <- rownames(py_to_r(adata_object$var))
colnames(data.input) <- rownames(py_to_r(adata_object$obs))
# access meta data
meta.data <- py_to_r(adata_object$obs)
meta <- meta.data
library(Matrix)
data.input <- as(data.input, "CsparseMatrix")
# Create a CellChat object
cellchat <- createCellChat(object = data.input, meta = meta, group.by = "cell_type")
levels(cellchat@idents) # show the cell labels
cellchat@DB <- CellChatDB.mouse # use all datasets
cellchat <- subsetData(cellchat)
cellchat <- identifyOverExpressedGenes(object=cellchat, thresh.pc = 0, thresh.fc = 1, thresh.p = 0.05) # https://github.com/sqjin/CellChat/issues/590
cellchat <- identifyOverExpressedInteractions(object=cellchat)
cellchat <- computeCommunProb(object=cellchat, type = c("triMean"), trim = 0.25, LR.use = NULL, raw.use = TRUE, population.size = FALSE)
cellchat <- filterCommunication(object=cellchat, min.cells = 25)
cellchat <- computeCommunProbPathway(object=cellchat, thresh = 0.05)
cellchat <- aggregateNet(object=cellchat, sources.use = NULL, targets.use = NULL, signaling = NULL, pairLR.use = NULL, thresh = 0.05)
simple_colors=c('#1f77b4', '#ff7f0e', '#279e68', '#d62728', '#aa40fc', '#8c564b', '#e377c2', '#b5bd61', '#17becf', '#aec7e8', '#ffbb78', '#98df8a', '#ff9896')
groupSize <- as.numeric(table(cellchat@idents))
par(mfrow = c(1,2), xpd=TRUE)
netVisual_circle(cellchat@net$count, color.use =simple_colors, vertex.weight = groupSize, weight.scale = TRUE, label.edge= FALSE, title.name = "Number of interactions")
netVisual_circle(cellchat@net$weight, color.use =simple_colors, vertex.weight = groupSize, weight.scale = TRUE, label.edge= FALSE, title.name = "Interaction weights/strength")
mat <- cellchat@net$weight
par(mfrow = c(3,5), xpd=TRUE)
for (i in 1:nrow(mat)) {
mat2 <- matrix(0, nrow = nrow(mat), ncol = ncol(mat), dimnames = dimnames(mat))
mat2[i, ] <- mat[i, ]
netVisual_circle(mat2, vertex.weight = groupSize, weight.scale = T, edge.weight.max = max(mat), title.name = rownames(mat)[i])
}
netVisual_aggregate(object=cellchat, signaling= c("MHC-II"), color.use =simple_colors, thresh = 0.05, vertex.receiver = seq(1,6), sources.use = NULL, targets.use = NULL, idents.use = NULL, top = 1, remove.isolate = FALSE, vertex.weight = NULL, weight.scale = TRUE, layout = c("hierarchy"), pt.title = 12, title.space = 1, vertex.label.cex = 0.8)
netVisual_aggregate(object=cellchat, signaling= c("MHC-II"), color.use =simple_colors, thresh = 0.05, vertex.receiver = seq(1,6), sources.use = NULL, targets.use = NULL, idents.use = NULL, top = 1, remove.isolate = FALSE, vertex.weight = NULL, weight.scale = TRUE, layout = c("circle"), pt.title = 12, title.space = 1, vertex.label.cex = 0.8)
netVisual_aggregate(object=cellchat, signaling= c("MHC-II"), color.use =simple_colors, thresh = 0.05, vertex.receiver = seq(1,6), sources.use = NULL, targets.use = NULL, idents.use = NULL, top = 1, remove.isolate = FALSE, vertex.weight = NULL, weight.scale = TRUE, layout = c("chord"), pt.title = 12, title.space = 1, vertex.label.cex = 0.8)
netAnalysis_contribution(object=cellchat, signaling = c("MHC-II"), thresh = 0.05, font.size = 8, font.size.title = 8)
pairLR.MHC <- extractEnrichedLR(object=cellchat, signaling = c("MHC-II"), geneLR.return = FALSE, enriched.only = TRUE, thresh = 0.05)
pairLR.MHC
LR.show <- pairLR.MHC[1,] # choose H2-AA_CD4
LR.show
netVisual_individual(object=cellchat, signaling= c("MHC-II"), pairLR.use = LR.show, color.use =simple_colors, vertex.receiver = seq(1,6), sources.use = NULL, targets.use = NULL, top = 1, remove.isolate = FALSE, vertex.weight = NULL, weight.scale = TRUE, layout = c("hierarchy"), thresh = 0.05)
netVisual_individual(object=cellchat, signaling= c("MHC-II"), pairLR.use = LR.show, color.use =simple_colors, vertex.receiver = seq(1,6), sources.use = NULL, targets.use = NULL, top = 1, remove.isolate = FALSE, vertex.weight = NULL, weight.scale = TRUE, layout = c("circle"), thresh = 0.05)
netVisual_individual(object=cellchat, signaling= c("MHC-II"), pairLR.use = LR.show, color.use =simple_colors, vertex.receiver = seq(1,6), sources.use = NULL, targets.use = NULL, top = 1, remove.isolate = FALSE, vertex.weight = NULL, weight.scale = TRUE, layout = c("chord"), thresh = 0.05)
netVisual_bubble(object=cellchat, sources.use = c(1:6), targets.use = c(7:13), signaling = NULL, pairLR.use = NULL, color.heatmap = c("viridis"), thresh = 0.05, comparison = NULL, remove.isolate = FALSE)
netVisual_bubble(object=cellchat, sources.use = c(1:6), targets.use = c(7:13), signaling = c("MHC-II"), pairLR.use = NULL, color.heatmap = c("viridis"), thresh = 0.05, comparison = NULL, remove.isolate = FALSE)
pairLR.MHC <- extractEnrichedLR(object=cellchat, signaling = c("MHC-II"), geneLR.return = FALSE, enriched.only = TRUE, thresh = 0.05)
pairLR.MHC
netVisual_bubble(object=cellchat, sources.use = c(1:6), targets.use = c(7:13), signaling = NULL, pairLR.use = pairLR.MHC, color.heatmap = c("viridis"), thresh = 0.05, comparison = NULL, remove.isolate = FALSE)
netVisual_chord_gene(object=cellchat, slot.name = "net", color.use =simple_colors, signaling = NULL, pairLR.use = NULL, sources.use = c(1:6), targets.use = c(7:13), lab.cex = 0.5, thresh = 0.05)
netVisual_chord_gene(object=cellchat, slot.name = "net", color.use =simple_colors, signaling = c("MHC-II"), pairLR.use = NULL, sources.use = c(1:6), targets.use = c(7:13), lab.cex = 0.5, thresh = 0.05)
netVisual_chord_gene(object=cellchat, slot.name = "netP", color.use =simple_colors, signaling = NULL, pairLR.use = NULL, sources.use = c(1:6), targets.use = c(7:13), lab.cex = 0.5, thresh = 0.05)
netVisual_chord_gene(object=cellchat, slot.name = "netP", color.use =simple_colors, signaling = c("MHC-II"), pairLR.use = NULL, sources.use = c(1:6), targets.use = c(7:13), lab.cex = 0.5, thresh = 0.05)
plotGeneExpression(object=cellchat, signaling = c("MHC-II"), enriched.only = TRUE, type = c("violin"), color.use =simple_colors, group.by = NULL)
cellchat <- netAnalysis_computeCentrality(object =cellchat, slot.name = "netP", thresh = 0.05)
netAnalysis_signalingRole_network(object =cellchat, signaling = c("MHC-II"), slot.name = "netP", measure = c("outdeg", "indeg", "fMgabet", "info"), measure.name = c("Sender", "Receiver", "Mediator", "Influencer"), color.use =simple_colors, color.heatmap = "BuGn", width = 8, height = 2.5, font.size = 8)
netAnalysis_signalingRole_scatter(object=cellchat, signaling = NULL, color.use =simple_colors, slot.name = "netP")
netAnalysis_signalingRole_scatter(object=cellchat, signaling = c("MHC-II"), color.use =simple_colors, slot.name = "netP")
ht1=netAnalysis_signalingRole_heatmap(object=cellchat, signaling = NULL, pattern = c("outgoing"), slot.name = "netP", color.use =simple_colors, color.heatmap = "BuGn", font.size = 8, font.size.title = 8)
ht2=netAnalysis_signalingRole_heatmap(object=cellchat, signaling = NULL, pattern = c("incoming"), slot.name = "netP", color.use =simple_colors, color.heatmap = "BuGn", font.size = 8, font.size.title = 8)
ht3=netAnalysis_signalingRole_heatmap(object=cellchat, signaling = NULL, pattern = c("all"), slot.name = "netP", color.use =simple_colors, color.heatmap = "BuGn", font.size = 8, font.size.title = 8)
ht1+ht2+ht3
library(NMF)
library(ggalluvial)
selectK(object=cellchat, slot.name = "netP", pattern = "outgoing")
nPatterns = 2
cellchat <- identifyCommunicationPatterns(object=cellchat, slot.name = "netP", pattern = "outgoing", k = nPatterns, color.use =simple_colors, color.heatmap = "Spectral", font.size = 8)
netAnalysis_river(object=cellchat, slot.name = "netP", pattern = "outgoing", cutoff = 0.5, sources.use = NULL, targets.use = NULL, signaling = NULL, color.use =simple_colors, font.size = 2.5)
netAnalysis_dot(object=cellchat, slot.name = "netP", pattern = "outgoing", cutoff = NULL, color.use =simple_colors, font.size = 8)
selectK(object=cellchat, slot.name = "netP", pattern = "incoming")
nPatterns = 5
cellchat <- identifyCommunicationPatterns(object=cellchat, slot.name = "netP", pattern = "incoming", k = nPatterns, color.use =simple_colors, color.heatmap = "Spectral", font.size = 8)
netAnalysis_river(object=cellchat, slot.name = "netP", pattern = "incoming", cutoff = 0.5, sources.use = NULL, targets.use = NULL, signaling = NULL, color.use =simple_colors, font.size = 2.5)
netAnalysis_dot(object=cellchat, slot.name = "netP", pattern = "incoming", cutoff = NULL, color.use =simple_colors, font.size = 8)
cellchat <- computeNetSimilarity(object=cellchat, slot.name = "netP", type = "functional", thresh = 0.05)
cellchat <- netEmbedding(object=cellchat, slot.name = "netP", type = "functional", umap.method = c("umap-learn"))
cellchat <- netClustering(object=cellchat, slot.name = "netP", type = "functional", do.parallel = TRUE, nCores = 32)
netVisual_embedding(object=cellchat, slot.name = "netP", type = "functional", color.use =simple_colors, label.size = 3, font.size = 8, font.size.title = 8)
cellchat <- computeNetSimilarity(object=cellchat, slot.name = "netP", type = "structural", thresh = 0.05)
cellchat <- netEmbedding(object=cellchat, slot.name = "netP", type = "structural", umap.method = c("umap-learn"))
cellchat <- netClustering(object=cellchat, slot.name = "netP", type = "structural", do.parallel = TRUE, nCores = 32)
netVisual_embedding(object=cellchat, slot.name = "netP", type = "structural", color.use =simple_colors, label.size = 3, font.size = 8, font.size.title = 8)
saveRDS(cellchat, file = "C:/Users/hyjfo/Documents/Mga_cellchat_1000_test.rds")
cellchat <- readRDS(file = "C:/Users/hyjfo/Documents/Mga_cellchat_1000_test.rds")