--- title: cellchat (四) 细胞间通讯分析 tags: [] id: '1614' categories: - - 单细胞下游分析 date: 2022-02-12 18:54:49 --- ## 信息流分析 ```r f_CC_IO_iN2pN <- function(cellchat, iN){ iN <- gsub('−','-', iN) unique(cellchat@DB$interaction[cellchat@DB$interaction$interaction_name_2 %in% iN, 'pathway_name']) } require(ComplexHeatmap) f_CC_cmp_IO_signaling <- function(object.list, pattern='all', color.heatmap = "OrRd", width = 5, height = 6, s_pathway=NULL){ i = 1 pathway.union <- union(object.list[[i]]@netP$pathways, object.list[[i+1]]@netP$pathways) if(!is.null(s_pathway)){pathway.union <- intersect(pathway.union, s_pathway)} ht1 = netAnalysis_signalingRole_heatmap(object.list[[i]], pattern = pattern, signaling = pathway.union, title = names(object.list)[i], width = width, height = height, color.heatmap = color.heatmap) ht2 = netAnalysis_signalingRole_heatmap(object.list[[i+1]], pattern = pattern, signaling = pathway.union, title = names(object.list)[i+1], width = width, height = height, color.heatmap = color.heatmap) draw(ht1 + ht2, ht_gap = unit(0.5, "cm")) } ``` ```r SS_s_p <- unlist(openxlsx::read.xlsx(xlsxFile = "SS_selected_signaling_fibroblasts.xlsx", sheet = 1, colNames = F)) ER_s_p <- unlist(openxlsx::read.xlsx(xlsxFile = "ER_selected_signaling_fibroblasts.xlsx", sheet = 1, colNames = F)) CC_s_p <- unlist(openxlsx::read.xlsx(xlsxFile = "CC_selected_signaling_fibroblasts.xlsx", sheet = 1, colNames = F)) pdf(file = 'IO_signaling_all.pdf', height = 8, width = 12) par(mfrow = c(3,1), xpd=TRUE) f_CC_cmp_IO_signaling(SS_l, width = 10, height = 12, s_pathway = f_CC_IO_iN2pN(SS_H, SS_s_p)) f_CC_cmp_IO_signaling(ER_l, width = 10, height = 4, s_pathway = f_CC_IO_iN2pN(ER_H, ER_s_p)) f_CC_cmp_IO_signaling(CC_l, width = 10, height = 4, s_pathway = f_CC_IO_iN2pN(CC_H, CC_s_p)) dev.off() pdf(file = 'IO_signaling_outgoing.pdf', height = 8, width = 12) par(mfrow = c(3,1), xpd=TRUE) f_CC_cmp_IO_signaling(SS_l, pattern = 'outgoing', color.heatmap = 'BuGn', width = 10, height = 12, s_pathway = f_CC_IO_iN2pN(SS_H, SS_s_p)) f_CC_cmp_IO_signaling(ER_l, pattern = 'outgoing', color.heatmap = 'BuGn', width = 10, height = 4, s_pathway = f_CC_IO_iN2pN(ER_H, ER_s_p)) f_CC_cmp_IO_signaling(CC_l, pattern = 'outgoing', color.heatmap = 'BuGn', width = 10, height = 4, s_pathway = f_CC_IO_iN2pN(CC_H, CC_s_p)) dev.off() pdf(file = 'IO_signaling_incoming.pdf', height = 8, width = 12) par(mfrow = c(3,1), xpd=TRUE) f_CC_cmp_IO_signaling(SS_l, pattern = 'incoming', color.heatmap = 'GnBu', width = 10, height = 12, s_pathway = f_CC_IO_iN2pN(SS_H, SS_s_p)) f_CC_cmp_IO_signaling(ER_l, pattern = 'incoming', color.heatmap = 'GnBu', width = 10, height = 4, s_pathway = f_CC_IO_iN2pN(ER_H, ER_s_p)) f_CC_cmp_IO_signaling(CC_l, pattern = 'incoming', color.heatmap = 'GnBu', width = 10, height = 4, s_pathway = f_CC_IO_iN2pN(CC_H, CC_s_p)) dev.off() ``` ## 功能失调信号 ```r f_CC_cmp_dysfunctional_signaling <- function(cellchat, pos.dataset = 'CRPC', neg.dataset='HSPC'){ # define a char name used for storing the results of differential expression analysis features.name = pos.dataset # perform differential expression analysis cellchat <- identifyOverExpressedGenes(cellchat, group.dataset = "datasets", pos.dataset = pos.dataset, features.name = features.name, only.pos = FALSE, thresh.pc = 0.1, thresh.fc = 0.1, thresh.p = 1) #> Use the joint cell labels from the merged CellChat object # map the results of differential expression analysis onto the inferred cell-cell communications to easily manage/subset the ligand-receptor pairs of interest net <- netMappingDEG(cellchat, features.name = features.name) # extract the ligand-receptor pairs with upregulated ligands in LS net.up <- subsetCommunication(cellchat, net = net, datasets = pos.dataset,ligand.logFC = 0.2, receptor.logFC = NULL) # extract the ligand-receptor pairs with upregulated ligands and upregulated recetptors in NL, i.e.,downregulated in LS net.down <- subsetCommunication(cellchat, net = net, datasets = neg.dataset,ligand.logFC = -0.1, receptor.logFC = -0.1) gene.up <- extractGeneSubsetFromPair(net.up, cellchat) gene.down <- extractGeneSubsetFromPair(net.down, cellchat) return(list(net_up=net.up, net_down=net.down, gene_up=gene.up, gene_down=gene.down)) } ``` ```r dSS <- f_CC_cmp_dysfunctional_signaling(SS) dER <- f_CC_cmp_dysfunctional_signaling(ER) dCC <- f_CC_cmp_dysfunctional_signaling(CC) ``` ```r f_CC_s_p_intersect <- function(net_info, DB_s_p){ DB_s_p <- gsub('−','-', DB_s_p) DB_s_p <- DB_s_p[DB_s_p %in% net_info$interaction_name_2] net_info <- net_info[net_info$interaction_name_2 %in% DB_s_p, c("interaction_name", "interaction_name_2"), drop = F] net_info <- net_info[, "interaction_name", drop = F] net_info } f_CC_cmp_dysfunctional_signaling_draw <- function(cellchat, f_res=NULL, sources.use=NULL, targets.use=NULL, pos.dataset = 'CRPC', neg.dataset='HSPC', pairLR.use.up=NULL, pairLR.use.down=NULL){ if(is.null(f_res)){ f_res <- f_CC_cmp_dysfunctional_signaling(cellchat, pos.dataset = pos.dataset, neg.dataset = neg.dataset) } if(is.null(targets.use)){ targets.use <- as.character(unique(unlist(cellchat@meta$ident))) } if(is.null(sources.use)){ sources.use <- as.character(unique(unlist(cellchat@meta$ident))) } if(is.null(pairLR.use.up)){ pairLR.use.up = f_res$net_up[, "interaction_name", drop = F] }else{ pairLR.use.up <- f_CC_s_p_intersect(f_res$net_up, pairLR.use.up) } gg1 <- netVisual_bubble(cellchat, pairLR.use = pairLR.use.up, sources.use = sources.use, targets.use = targets.use, comparison = c(1, 2), angle.x = 90, remove.isolate = T,title.name = paste0("Up-regulated signaling in ", pos.dataset)) #> Comparing communications on a merged object if(is.null(pairLR.use.down)){ pairLR.use.down = f_res$net_down[, "interaction_name", drop = F] }else{ pairLR.use.down <- f_CC_s_p_intersect(f_res$net_down, pairLR.use.down) } gg2 <- netVisual_bubble(cellchat, pairLR.use = pairLR.use.down, sources.use = sources.use, targets.use = targets.use, comparison = c(1, 2), angle.x = 90, remove.isolate = T,title.name = paste0("Down-regulated signaling in ", pos.dataset)) #> Comparing communications on a merged object gg1 + gg2 } ``` ```r flt <- c('Fibroblasts', 'TAM', 'Mast', 'S100A8+ monocytes', 'Proliferating T', 'Proliferating Myeloid', 'Luminal', 'Endothelial', 'Basal cell', 'cDC2') pdf(file = 'dysfunctional_signaling.pdf', height = 12, width = 12) par(mfrow = c(3,1), xpd=TRUE) f_CC_cmp_dysfunctional_signaling_draw(SS, f_res = dSS, sources.use = c('Fibroblasts'), targets.use = flt, pairLR.use.up = SS_s_p, pairLR.use.down = SS_s_p) f_CC_cmp_dysfunctional_signaling_draw(ER, f_res = dER, sources.use = c('Fibroblasts'), targets.use = flt, pairLR.use.up = ER_s_p, pairLR.use.down = ER_s_p) f_CC_cmp_dysfunctional_signaling_draw(CC, f_res = dCC, sources.use = c('Fibroblasts'), targets.use = flt, pairLR.use.up = CC_s_p, pairLR.use.down = CC_s_p) dev.off() pdf(file = 'dysfunctional_signaling_t.pdf', height = 12, width = 12) par(mfrow = c(3,1), xpd=TRUE) f_CC_cmp_dysfunctional_signaling_draw(SS, f_res = dSS, targets.use = c('Fibroblasts'), sources.use = flt, pairLR.use.up = SS_s_p, pairLR.use.down = SS_s_p) f_CC_cmp_dysfunctional_signaling_draw(ER, f_res = dER, targets.use = c('Fibroblasts'), sources.use = flt, pairLR.use.up = ER_s_p, pairLR.use.down = ER_s_p) f_CC_cmp_dysfunctional_signaling_draw(CC, f_res = dCC, targets.use = c('Fibroblasts'), sources.use = flt, pairLR.use.up = CC_s_p, pairLR.use.down = CC_s_p) dev.off() ``` ## 细胞通路弦图 ```r f_CC_IO_iN2pN_2 <- function(cellchat, iN){ iN <- gsub('−','-', iN) unique(cellchat@DB$interaction[cellchat@DB$interaction$interaction_name_2 %in% iN, c('pathway_name', 'interaction_name_2')]['pathway_name']) } f_CC_cmp_nV_c_p <- function(object.list, sources.use=NULL, targets.use=NULL, s_pathway=NULL, title.name){ for (i in 1:length(object.list)) { if(!is.null(s_pathway)){ lc_pairLR.use <- f_CC_IO_iN2pN_2(object.list[[i]], s_pathway) }else{lc_pairLR.use = s_pathway} try(netVisual_chord_gene(object.list[[i]], sources.use = sources.use, pairLR.use = lc_pairLR.use, targets.use = targets.use, slot.name = "netP", title.name = paste0("Signaling pathways - ", names(object.list)[i]), legend.pos.x = 10)) } } ``` ```r pdf(file = 'nV_c_p.pdf', height = 12, width = 12) f_CC_cmp_nV_c_p(SS_l, sources.use = c('Fibroblasts'), targets.use = flt, s_pathway = SS_s_p) f_CC_cmp_nV_c_p(ER_l, sources.use = c('Fibroblasts'), targets.use = flt, s_pathway = ER_s_p) f_CC_cmp_nV_c_p(CC_l, sources.use = c('Fibroblasts'), targets.use = flt, s_pathway = CC_s_p) dev.off() pdf(file = 'nV_c_p_t.pdf', height = 12, width = 12) f_CC_cmp_nV_c_p(SS_l, targets.use = c('Fibroblasts'), sources.use = flt, s_pathway = SS_s_p) f_CC_cmp_nV_c_p(ER_l, targets.use = c('Fibroblasts'), sources.use = flt, s_pathway = ER_s_p) f_CC_cmp_nV_c_p(CC_l, targets.use = c('Fibroblasts'), sources.use = flt, s_pathway = CC_s_p) dev.off() ```