Add initial code for ds.aggr (CellRanger tSNE and K-clust=10)

r.scripts/sc-TissueMapper_RUN.DS.aggr.R

+gc()
+library(methods)
+library(optparse)
+library(Seurat)
+library(readr)
+library(fBasics)
+library(pastecs)
+library(qusage)
+library(RColorBrewer)
+library(monocle)
+library(dplyr)
+library(viridis)
+library(reshape2)
+library(NMI)
+
+
+source("../r.scripts/sc-TissueMapper.R")
+setwd("../")
+
+if (!dir.exists("./analysis")){
+  dir.create("./analysis")
+}
+
+downsamples <- c("All","350","300","250","200","150","100","075","050","037","025","012")
+samples <- c("D17","D27","D35")
+
+all.cells <- NULL
+for (i in downsamples){
+  assign(paste0("cluster.",i),read_csv(paste0("./analysis/DATA/10x/",i,"/kmeans_10_clusters/clusters.csv")))
+  all.cells <- c(all.cells,get(paste0("cluster.",i))$Barcode)
+}
+all.cells <- unique(all.cells)
+all.cells <- data.frame(Barcode=all.cells)
+shared.cells <- Reduce(intersect,list(cluster.All$Barcode,cluster.350$Barcode,cluster.300$Barcode,cluster.250$Barcode,cluster.200$Barcode,cluster.150$Barcode,cluster.100$Barcode,cluster.075$Barcode,cluster.050$Barcode,cluster.037$Barcode,cluster.025$Barcode,cluster.012$Barcode))
+for (i in downsamples){
+  assign(paste0("cluster.",i),get(paste0("cluster.",i))[get(paste0("cluster.",i))$Barcode %in% shared.cells,])
+}
+
+#for (i in downsamples){
+#  cluster <- all.cells
+#  cluster$Cluster <- 0
+#  cluster <- merge(cluster,get(paste0("cluster.",i)),all=TRUE,by.x="Barcode",by.y="Barcode",no.dups=TRUE)
+#  cluster[is.na(cluster)] <- 0
+#  cluster$Cluster <- cluster$Cluster.x+cluster$Cluster.y
+#  cluster <- cluster[,-2]
+#  cluster <- cluster[,-2]
+#  assign(paste0("cluster.",i),cluster)
+#  rm(cluster)
+#}
+
+for (i in downsamples[3:12]){
+  png(paste0("./analysis/",i,".png"),width=500,height=500,type="cairo")
+  assign(paste0("plot.",i),ggplot(melt(prop.table(table(cluster.350$Cluster,get(paste0("cluster.",i))$Cluster),1)*100),aes(x=factor(Var1),y=factor(Var2),fill=value))+geom_tile(color="black")+labs(x="350",y=i,fill="% of 350")+theme(line = element_blank())+scale_fill_gradientn(colours=c("white","black")))
+  plot(get(paste0("plot.",i)))
+  dev.off()
+}
+
+nmi <- data.frame(group1=character(),group2=character(),value=double())
+for (i in downsamples[-1]){
+  for (j in downsamples[-1]){
+    nmi <- rbind(nmi,data.frame(group1=i,group2=j,nmi=NMI(get(paste0("cluster.",i)),get(paste0("cluster.",j)))))
+}}
+png(paste0("./analysis/NMI.png"),width=500,height=500,type="cairo")
+plot.nmi <- ggplot(nmi,aes(x=factor(group1),y=factor(group2),fill=value))+geom_tile(color="black")+labs(x="",y="",fill="NMI")+theme(line = element_blank())+scale_fill_gradientn(colours=c("white","black"))
+plot(plot.nmi)
+dev.off()