Figures Scripts

Scripts/Create_Paper_Figures.R

+# ======================== LOAD =========================
+library("Seurat")
+library("tidyverse")
+library("viridis")
+library("ggpubr")
+library("gridExtra")
+library("VennDiagram")
+library("RColorBrewer")
+Combined<- readRDS("Seurat.rds")
+DefaultAssay(Combined) <- "SCT"
+Combined$Timepoints <- as.vector(Combined$condition)
+Combined$Timepoints[grep("IPSC",Combined$condition)] <-"iPSCs"
+Combined$Timepoints[grep("D06",Combined$condition)] <-"Day06"
+Combined$Timepoints[grep("D10",Combined$condition)] <-"Day10"
+Combined$Timepoints[grep("D15",Combined$condition)] <-"Day15"
+Combined$Timepoints[grep("D21",Combined$condition)] <-"Day21"
+Combined$Timepoints <- factor(Combined$Timepoints,c("iPSCs","Day06","Day10","Day15","Day21"))
+
+# -------------------------------------------------------
+
+
+# ======================= FIGURE 3 ==========================
+# === Figure a
+dir.create("DF_Conditions")
+setwd("DF_Conditions")
+DefaultAssay(Combined) <-"RNA"
+Combined <- NormalizeData(Combined)
+Combined <- ScaleData(Combined)
+Controls_DM <- subset(Combined,subset= Treatment !="PINK")
+DefaultAssay(Controls_DM) <- "RNA"
+Idents(Controls_DM)<-as.factor(Controls_DM$condition)
+pbmc.markers <- FindAllMarkers(object = Controls_DM,
+                            assay ="RNA",min.pct =0.1,
+                            logfc.threshold=0.1,
+                            only.pos = TRUE,
+                            test.use = "MAST",latent.vars = c("nCount_RNA"))
+
+pbmc.markers$gene <- rownames(pbmc.markers)
+qvalue <- p.adjust(pbmc.markers$p_val, method = "BH",n=dim(Controls_DM@assays$RNA@counts)[1])
+pbmc.markers$qvalue <- qvalue
+
+top <- pbmc.markers[pbmc.markers$p_val_adj<0.01 & abs(pbmc.markers$avg_logFC) >0.1,]
+to_heat <- top %>% group_by(cluster) %>% top_n(n = 15, wt = abs(avg_logFC)) 
+to_heat <- to_heat[order(to_heat$cluster),]
+Controls_DM$condition <- as.factor(Controls_DM$condition)
+ICSWrapper::annotated_heat(object=Controls_DM,
+                   row_annotation=c(1),
+                   gene_list=to_heat$gene,
+                   Rowv=NA,
+                   gene_list_name="DF_genes",
+                   title="Figure3a",
+                   ordering="Treatment",One_annot = TRUE,color_list = color_list)
+ 
+
+# === Figure b
+Stemness_markers<- c("SOX2", "MYC", "POU5F1", "NANOG", "LIN28")
+differentiation_path<- c("OTX2", "LMX1B", "LMX1A", "FOXA2", "PTCH1", "FZD7")
+last <- c(Stemness_markers,differentiation_path)
+pdf("Figure3b.pdf",width= 8)
+DoHeatmap(Combined,last,group.by = "Timepoints", raster = FALSE)+ scale_fill_viridis(option="inferno")
+dev.off()
+# -----------------------------------------------------------
+
+
+
+
+
+
+# ======================= FIGURE 4 ==========================
+mDA <- c("TCF12", "ALCAM", "PITX2", "DDC", "ASCL1")
+mDA <- mDA[mDA %in% rownames(Combined@assays$RNA@counts)]
+p0 <- DimPlot(Combined,group.by = "condition",cols=color_cond)
+#FeaturePlot(Combined,features = c("TH","KCNJ6"),pt.size = 2,,order = TRUE,cols = c("lightgrey","#FDBB84","#EF6548","#D7301F","#B30000","#7F0000"))
+results <- ICSWrapper::scatter_gene(object = Combined,features = c("TH","KCNJ6"),ncol =1 ,nrow =2)+ theme_void()
+plot4 <- DoHeatmap(Combined,mDA,group.by = "Timepoints", raster = FALSE)+  
+scale_fill_viridis(option="inferno")
+plot5 <- grid.arrange(p0, results, widths=c(2/3, 1/2), ncol=2, nrow=1)
+pdf("Figure4.pdf",width=12,height=10)
+grid.arrange(plot5,plot4,ncol=1, nrow=2,clip=TRUE)
+dev.off()
+# -----------------------------------------------------------
+
+
+# ================== FIGURE 5 ==============================
+color_list_three <- color_list
+color_list_three$condition <- color_list_three$condition[-c(1,3,6)]
+dirs_pairs <- list.dirs("C:/Users/dimitrios.kyriakis/Desktop/PhD/Projects/Michi_Data/2020-04-17_seurat_elbow_TRUE_Mito-FALSE_Ribo-FALSE_SCT-TRUE_criteria_pass-3/DF_Pairwise",full.names = TRUE )[-1]
+dirs_pairs <- grep('IPSC|D06.*D06|D15.*D15|D21.*D21',dirs_pairs,value = TRUE)
+dirs_pairs <- dirs_pairs[-4]
+df_return_nt_cntrl <- list()
+df_return_nt_pink <- list()
+df_return_nt_all <- list()
+for (iter in 1:length(dirs_pairs)){
+    dirs_iter <- dirs_pairs[iter]
+    file <- paste0(dirs_iter ,"/", dir(dirs_iter, "*.tsv"))
+    l1 <- read.table(file,header=TRUE)
+    l1$cluster <- l1$avg_logFC
+    l1$cluster[ l1$avg_logFC<0] <- "PINK"
+    l1$cluster[ l1$avg_logFC>0] <- "Control"
+    ctrl_l1 <- l1[grep("Control",l1$cluster),]
+    pink_l1 <- l1[grep("PINK",l1$cluster),]
+	all_l1 <-  l1
+    df_return_nt_cntrl[[iter]] <- as.vector(ctrl_l1[ctrl_l1$p_val_adj<0.01 & abs(ctrl_l1$avg_logFC) >0.1,"gene"])
+    df_return_nt_pink[[iter]] <- as.vector(pink_l1[pink_l1$p_val_adj<0.01 & abs(pink_l1$avg_logFC) >0.1,"gene"])
+    print(length(df_return_nt_cntrl[[iter]]))
+    print(length(df_return_nt_pink[[iter]]))
+    df_return_nt_all[[iter]] <- c(df_return_nt_cntrl[[iter]] ,df_return_nt_pink[[iter]])
+}
+
+# # ============= Intersect Common Genes
+cntrl_intesect <- Reduce(intersect, df_return_nt_cntrl)
+print(cntrl_intesect)
+pink_intesect <- Reduce(intersect, df_return_nt_pink)
+print(pink_intesect)
+length(cntrl_intesect)
+length(pink_intesect)
+
+
+Conserved_M <- subset(Combined,subset= Timepoints %in% c("Day06","Day15","Day21"))
+
+Conserved_M$condition<- factor(Conserved_M$condition)
+ICSWrapper::annotated_heat(object=Conserved_M,
+                   row_annotation=c(1),
+                   gene_list=c(cntrl_intesect,pink_intesect),
+                   Rowv=NA,
+                   gene_list_name="DF_genes",
+                   title="Figure5a",
+                   ordering="Treatment",One_annot = TRUE,color_list =  color_list_three)
+
+
+# ============================= Figure 5b
+df_return_nt_cntrl <- list()
+df_return_nt_pink <- list()
+df_return_nt_all <- list()
+for (iter in 1:length(dirs_pairs)){
+    dirs_iter <- dirs_pairs[iter]
+    file <- paste0(dirs_iter ,"/", dir(dirs_iter, "*.tsv"))
+    l1 <- read.table(file,header=TRUE)
+    l1$cluster <- l1$avg_logFC
+    l1$cluster[ l1$avg_logFC<0] <- "PINK"
+    l1$cluster[ l1$avg_logFC>0] <- "Control"
+    ctrl_l1 <- l1[grep("Control",l1$cluster),]
+    pink_l1 <- l1[grep("PINK",l1$cluster),]
+	all_l1 <-  l1
+    df_return_nt_cntrl[[iter]] <- as.vector(ctrl_l1[ctrl_l1$p_val_adj<0.01 & abs(ctrl_l1$avg_logFC) >0.4,"gene"])
+    df_return_nt_pink[[iter]] <- as.vector(pink_l1[pink_l1$p_val_adj<0.01 & abs(pink_l1$avg_logFC) >0.4,"gene"])
+    print(length(df_return_nt_cntrl[[iter]]))
+    print(length(df_return_nt_pink[[iter]]))
+    df_return_nt_all[[iter]] <- c(df_return_nt_cntrl[[iter]] ,df_return_nt_pink[[iter]])
+}
+cntrl_intesect <- Reduce(intersect, df_return_nt_cntrl)
+print(cntrl_intesect)
+pink_intesect <- Reduce(intersect, df_return_nt_pink)
+myCol <- brewer.pal(3, "Pastel2")
+# === COntrol
+pdf("Control_venn_diagramm.pdf")
+day06 <- c(df_return_nt_cntrl[[1]])
+day15 <- c(df_return_nt_cntrl[[2]])
+day21 <- c(df_return_nt_cntrl[[3]])
+v <- venn.diagram(list(Day06=day06, Day15=day15,Day21=day21),
+                  fill = myCol,
+                  alpha = c(0.5, 0.5, 0.5), cat.cex = 1.5, cex=1.5,
+                  filename=NULL)
+grid.newpage()
+grid.draw(v)
+lapply(v,  names)
+lapply(v, function(i) i$label)
+v[[11]]$label <- paste(intersect(intersect(day06, day15),day21), collapse="\n")  
+grid.newpage()
+grid.draw(v)
+dev.off()
+v1 <-v
+#------------
+
+# === PINK
+pdf("PINK_venn_diagramm.pdf")
+day06 <- c(df_return_nt_pink[[1]])
+day15 <- c(df_return_nt_pink[[2]])
+day21 <- c(df_return_nt_pink[[3]])
+v <- venn.diagram(list(Day06=day06, Day15=day15,Day21=day21),
+                  fill = myCol,
+                  alpha = c(0.5, 0.5, 0.5), cat.cex = 1.5, cex=1.5,
+                  filename=NULL)
+grid.newpage()
+grid.draw(v)
+lapply(v,  names)
+lapply(v, function(i) i$label)
+
+v[[11]]$label <- paste(intersect(intersect(day06, day15),day21), collapse="\n")  
+grid.newpage()
+p1 <-grid.draw(v)
+dev.off()
+v2 <-v
+# ------------------ 
+
+# ===== Plot
+library(grid)
+library(gridBase)
+graphics.off()
+pdf("Figure5b.pdf")
+plot.new()
+vp1 <- viewport(x=0,y=0.5,width=0.5, height=0.5, just = c("left", "bottom"))
+vp2 <- viewport(x=0,y=0,width=0.5, height=0.5, just = c("left", "bottom"))
+upViewport()
+pushViewport(vp1)
+grid.draw(v1)
+par(new=TRUE, fig=gridFIG())
+
+upViewport()
+pushViewport(vp2)
+grid.draw(v2)
+par(new=TRUE, fig=gridFIG())
+dev.off()
+
+# -----------------------------------------------------------
+
+
+
+
+# ==================== Correlation Network ==================
+# -----------------------------------------------------------
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