--- a +++ b/6-Figure scripts/Fig S4.R @@ -0,0 +1,146 @@ +library(data.table) +library(dplyr) +library(reshape2) +library(ggplot2) +library(ggdendro) +library(readxl) +library(ggpubr) + +excel_sheets("Fig S4 Source Data.xlsx") + +# Figure S4 --------------------------------- +CorrDf_metab.metag_neu <- read_excel("Fig S4 Source Data.xlsx", sheet = "MetaG-MetaB Full") +CorrDf_metab.trans_neu <- read_excel("Fig S4 Source Data.xlsx", sheet = "Trans-MetaB") +CorrDf_spupro.trans_neu <- read_excel("Fig S4 Source Data.xlsx", sheet = "Trans-Sputpro") +CorrDf_serpro.trans_neu <- read_excel("Fig S4 Source Data.xlsx", sheet = "Trans-Serpro") + +keyStr_df <- cbind.data.frame(dfnameStr = c("metag","metab","trans","serpro","spupro"), + colStr = c("MetaG","MetaB","Trans","Cyto","Cyto"), + stringsAsFactors=F) + +# nodes and types +nodeXs <- c("metab","serpro","spupro") #do not change the sequences of elements in nodeXs +nodeYs <- c("metag","trans") #do not change the sequences of elements in nodeYs +ENtypes <- c("neu") + +for(enType in ENtypes){ + # enType = ENtypes[2] + + for(nodex in nodeXs){ + # nodex = nodeXs[1] + + for(nodey in nodeYs){ + # nodey = nodeYs[2] + + + corrDfName <- paste("CorrDf_",nodex,".",nodey,"_",enType,sep = "") + if(!exists(corrDfName)) next + + CorrDf <- eval(parse(text = corrDfName)) + + NodeXCol <- which(sapply(CorrDf, function(x) all(grepl(keyStr_df$colStr[which(keyStr_df$dfnameStr == nodex)], x) )) ) + colnames(CorrDf)[NodeXCol] <- "NodeX" + + NodeYCol <- which(sapply(CorrDf, function(x) all(grepl(keyStr_df$colStr[which(keyStr_df$dfnameStr == nodey)], x) )) ) + colnames(CorrDf)[NodeYCol] <- "NodeY" + + + # organize the orders of nodex and nodey + dat_r.w <- CorrDf %>% reshape2::dcast(NodeY ~ NodeX, value.var = "Correlation") + rownames(dat_r.w) <- dat_r.w$NodeY; dat_r.w <- dat_r.w[-1] + + if(T){ + df <- t(dat_r.w) + x <- as.matrix(scale(df)) + dd.col <- as.dendrogram(hclust(dist(x))) + col.ord <- order.dendrogram(dd.col) + + dd.row <- as.dendrogram(hclust(dist(t(x)))) + row.ord <- order.dendrogram(dd.row) + + xx <- scale(df)[col.ord, row.ord] + xx_names <- attr(xx, "dimnames") + #df <- as.data.frame(xx) + ddata_x <- dendro_data(dd.row) + ddata_y <- dendro_data(dd.col) + } + if(!exists(paste("order_",nodey,sep = ""))) assign(paste("order_",nodey,sep = ""), xx_names[[2]],envir = .GlobalEnv) + if(!exists(paste("order_",nodex,sep = ""))) assign(paste("order_",nodex,sep = ""), xx_names[[1]],envir = .GlobalEnv) + + + order_nodex <- eval(parse(text = paste("order_",nodex,sep = ""))) + order_nodey <- eval(parse(text = paste("order_",nodey,sep = ""))) + + if(!all(unique(CorrDf$NodeX) %in% order_nodex) ) {print(paste("not all nodes of ", nodex," were in predefined order so stop",sep = ""));break} + if(!all(unique(CorrDf$NodeY) %in% order_nodey) ) {print(paste("not all nodes of ", nodey," were in predefined order so stop",sep = ""));break} + + + CorrDf$NodeX <- factor(CorrDf$NodeX, levels = order_nodex) + CorrDf$NodeY <- factor(CorrDf$NodeY, levels = order_nodey) + + CorrDf$ColorType <- sapply(c(1:nrow(CorrDf)), + function(i) { + if(CorrDf$Linked[i] == "Y") return("Y") else if(CorrDf$`P-value`[i] >= 0.05) return("N_ns") else if(CorrDf$Correlation[i]>0) return("N_sig_posCorr") else return("N_sig_negCorr") + }) + + CorrDf$absCorr <- abs(CorrDf$Correlation) + + + CorrDf <- CorrDf %>% filter( NodeX %in% order_nodex) %>% filter(NodeY %in% order_nodey) + CorrDf$NodeX <- factor(CorrDf$NodeX, levels = order_nodex) + CorrDf$NodeY <- factor(CorrDf$NodeY, levels = order_nodey) + + + p <- ggplot(data = CorrDf, aes(x=NodeX,y=NodeY))+ + geom_tile(aes(fill=ColorType, alpha=absCorr),color="white") + + theme(axis.text.x = element_text(angle = 90))+ + #scale_fill_manual(values=c("white","#e2e2e2","#cc0202"))+ + scale_fill_manual(values = c("white","#c1c1ff","#ffb6b6","#cc0202")) + + #scale_alpha(limits = c(0.0,1.0), range = c(0,0.6))+ + theme( panel.grid.major = element_blank(), + panel.grid.minor = element_blank(), + panel.background = element_blank()) + # axis.title.x = element_text(colour=NA), + # axis.title.y = element_blank()) + + assign(paste("HeatP_",nodex,".",nodey,"_",enType,sep = ""), p, envir = .GlobalEnv) + + } + + + } + + + assign(paste("order_metab_",enType,sep = ""), order_metab, envir = .GlobalEnv) + assign(paste("order_metag_",enType,sep = ""), order_metag, envir = .GlobalEnv) + assign(paste("order_trans_",enType,sep = ""), order_trans, envir = .GlobalEnv) + assign(paste("order_serpro_",enType,sep = ""), order_serpro, envir = .GlobalEnv) + assign(paste("order_spupro_",enType,sep = ""), order_spupro, envir = .GlobalEnv) + + remove(order_metab,order_metag,order_trans, order_serpro, order_spupro) +} + + + + +# Fig S4. NEU integrated plot +ggarrange(ggarrange(HeatP_metab.trans_neu + + theme(legend.position = "none", axis.text.x = element_blank(),axis.text.y = element_blank()) + + xlab("MetaB") + ylab("Trans"), + HeatP_spupro.trans_neu + + theme(legend.position = "none", axis.text.x = element_blank(),axis.text.y = element_blank()) + + xlab("Sputum") + ylab("Trans"), + HeatP_serpro.trans_neu + + theme(legend.position = "none", axis.text.x = element_blank(),axis.text.y = element_blank()) + + xlab("Serum") + ylab("Trans"), + nrow = 1, widths = c(0.55,0.3,0.15)), + ggarrange(HeatP_metab.metag_neu + + theme(legend.position = "none", axis.text.x = element_blank(),axis.text.y = element_blank()) + + xlab("MetaB") + ylab("MetaG"), + ggplot() + geom_text(aes(x=0,y=0),label="NEU") + theme_dendro(), + nrow = 1, widths = c(0.55,0.45)), + nrow = 2,heights = c(0.6,0.4)) + + + +