From 948bf890a1282c52be1f7790f6907b913a415b06 Mon Sep 17 00:00:00 2001
From: "Gervaise H. Henry" <gervaise.henry@utsouthwestern.edu>
Date: Fri, 26 Oct 2018 08:41:23 -0500
Subject: [PATCH] Add leu geneset, add 3grp cust col tSNE and finalize PdPbPc
leu ID code
---
genesets/40425_2017_215_MOESM1_ESM.xlsx | Bin 0 -> 27512 bytes
r.scripts/sc-TissueMapper.R | 45 ++++
r.scripts/sc-TissueMapper_RUN.PdPbPc.R | 342 ++++++++++++++++++++++++
3 files changed, 387 insertions(+)
create mode 100755 genesets/40425_2017_215_MOESM1_ESM.xlsx
create mode 100755 r.scripts/sc-TissueMapper_RUN.PdPbPc.R
diff --git a/genesets/40425_2017_215_MOESM1_ESM.xlsx b/genesets/40425_2017_215_MOESM1_ESM.xlsx
new file mode 100755
index 0000000000000000000000000000000000000000..5a813a3b5b13a22e578c267e8269b26ab51aca94
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diff --git a/r.scripts/sc-TissueMapper.R b/r.scripts/sc-TissueMapper.R
index 24d1548..5d14042 100644
--- a/r.scripts/sc-TissueMapper.R
+++ b/r.scripts/sc-TissueMapper.R
@@ -1257,6 +1257,51 @@ sctSNECustCol <- function(sc10x,i,bl,rd,file){
dev.off()
}
+sctSNE3CustCol <- function(sc10x,i,bl,rd,gn,file){
+ if (gn!=""){
+ gn.col <- NULL
+ if (length(sc10x@ident[sc10x@ident=="B-cells"])>0){
+ gn.col <- c(gn.col,"#BAE4B3")
+ }
+ if (length(sc10x@ident[sc10x@ident=="T-cells"])>0){
+ gn.col <- c(gn.col,"#74C476")
+ }
+ if (length(sc10x@ident[sc10x@ident=="Macrophages"])>0){
+ gn.col <- c(gn.col,"#31A354")
+ }
+ if (length(sc10x@ident[sc10x@ident=="Mast cells"])>0){
+ gn.col <- c(gn.col,"#006D2C")
+ }
+ }
+ sc10x <- SetAllIdent(object=sc10x,id=i)
+ if (any(sc10x@ident == "Unknown")){
+ sc10x@ident <- factor(sc10x@ident,levels=c(bl,rd,gn))
+ } else {
+ sc10x@ident <- factor(sc10x@ident,levels=c(bl,rd,gn,"Unknown"))
+ }
+ postscript(paste0("./analysis/diy/tSNE_",file,".",i,".CustCol.eps"))
+ if (length(bl)==1 & length(rd)==1 & length(gn)==1){
+ if (length(sc10x@ident[sc10x@ident=="Unknown"])>0){
+ plot <- TSNEPlot(object=sc10x,pt.size=2.5,do.label=FALSE,label.size=10,do.return=TRUE,vector.friendly=FALSE,colors.use=c(brewer.pal(5,"Blues")[5],brewer.pal(5,"Reds")[5],brewer.pal(5,"Greens")[5],"grey50"))
+ } else {
+ plot <- TSNEPlot(object=sc10x,pt.size=2.5,do.label=FALSE,label.size=10,do.return=TRUE,vector.friendly=FALSE,colors.use=c(brewer.pal(5,"Blues")[5],brewer.pal(5,"Reds")[5],brewer.pal(5,"Greens")[5]))
+ }
+ plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(size=20),axis.title.x=element_text(size=20),axis.title.y=element_text(size=20),legend.text=element_text(size=20))
+ plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
+ plot(plot)
+ } else {
+ if (bl!=""){
+ plot <- TSNEPlot(object=sc10x,pt.size=2.5,do.label=FALSE,label.size=10,do.return=TRUE,vector.friendly=FALSE,colors.use=c(brewer.pal((length(bl)+1),"Blues")[2:(length(bl)+1)],brewer.pal((length(rd)+1),"Reds")[2:(length(rd)+1)],gn.col))
+ } else {
+ plot <- TSNEPlot(object=sc10x,pt.size=2.5,do.label=FALSE,label.size=10,do.return=TRUE,vector.friendly=FALSE,colors.use=brewer.pal((length(rd)+1),"Reds")[2:(length(rd)+1)])
+ }
+ plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(size=20),axis.title.x=element_text(size=20),axis.title.y=element_text(size=20),legend.text=element_text(size=20))
+ plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
+ plot(plot)
+ }
+ dev.off()
+}
+
sctSNEbwCol <- function(sc10x,i,file,files){
sc10x <- SetAllIdent(object=sc10x,id=i)
sc10x@ident <- factor(sc10x@ident,levels=c("Epi","BE","LE","OE1","OE_SCGB","OE2","OE_KRT13","St","Fib","SM","Endo","Leu","Unknown",1:50))
diff --git a/r.scripts/sc-TissueMapper_RUN.PdPbPc.R b/r.scripts/sc-TissueMapper_RUN.PdPbPc.R
new file mode 100755
index 0000000..43fabef
--- /dev/null
+++ b/r.scripts/sc-TissueMapper_RUN.PdPbPc.R
@@ -0,0 +1,342 @@
+gc()
+library(methods)
+library(optparse)
+library(Seurat)
+library(readr)
+library(fBasics)
+library(pastecs)
+library(qusage)
+library(RColorBrewer)
+library(monocle)
+library(dplyr)
+library(viridis)
+library(readxl)
+
+source("../r.scripts/sc-TissueMapper.R")
+
+#Create folder structure
+setwd("../")
+if (!dir.exists("./analysis")){
+ dir.create("./analysis")
+}
+if (!dir.exists("./analysis/qc")){
+ dir.create("./analysis/qc")
+}
+if (!dir.exists("./analysis/qc/cc")){
+ dir.create("./analysis/qc/cc")
+}
+if (!dir.exists("./analysis/tSNE")){
+ dir.create("./analysis/tSNE")
+}
+if (!dir.exists("./analysis/tSNE/pre.stress")){
+ dir.create("./analysis/tSNE/pre.stress")
+}
+if (!dir.exists("./analysis/pca")){
+ dir.create("./analysis/pca")
+}
+if (!dir.exists("./analysis/pca/stress")){
+ dir.create("./analysis/pca/stress")
+}
+if (!dir.exists("./analysis/violin")){
+ dir.create("./analysis/violin")
+}
+if (!dir.exists("./analysis/violin/stress")){
+ dir.create("./analysis/violin/stress")
+}
+if (!dir.exists("./analysis/table")){
+ dir.create("./analysis/table")
+}
+if (!dir.exists("./analysis/tSNE/post.stress")){
+ dir.create("./analysis/tSNE/post.stress")
+}
+if (!dir.exists("./analysis/cor")){
+ dir.create("./analysis/cor")
+}
+if (!dir.exists("./analysis/tSNE/lin")){
+ dir.create("./analysis/tSNE/lin")
+}
+if (!dir.exists("./analysis/tSNE/epi")){
+ dir.create("./analysis/tSNE/epi")
+}
+if (!dir.exists("./analysis/tSNE/st")){
+ dir.create("./analysis/tSNE/st")
+}
+if (!dir.exists("./analysis/tSNE/leu")){
+ dir.create("./analysis/tSNE/leu")
+}
+if (!dir.exists("./analysis/tSNE/merge")){
+ dir.create("./analysis/tSNE/merge")
+}
+if (!dir.exists("./analysis/pca/ne")){
+ dir.create("./analysis/pca/ne")
+}
+if (!dir.exists("./analysis/tSNE/ne")){
+ dir.create("./analysis/tSNE/ne")
+}
+if (!dir.exists("./analysis/violin/ne")){
+ dir.create("./analysis/violin/ne")
+}
+if (!dir.exists("./analysis/tSNE/FINAL")){
+ dir.create("./analysis/tSNE/FINAL")
+}
+if (!dir.exists("./analysis/deg")){
+ dir.create("./analysis/deg")
+}
+if (!dir.exists("./analysis/cca")){
+ dir.create("./analysis/cca")
+}
+if (!dir.exists("./analysis/diy")){
+ dir.create("./analysis/diy")
+}
+if (!dir.exists("./analysis/pseudotime")){
+ dir.create("./analysis/pseudotime")
+}
+
+#Retrieve command-line options
+option_list=list(
+ make_option("--p",action="store",default="DPrF",type='character',help="Project Name"),
+ make_option("--g",action="store",default="ALL",type='character',help="Group To analyze"),
+ make_option("--lg",action="store",default=500,type='integer',help="Threshold for cells with minimum genes"),
+ make_option("--hg",action="store",default=3000,type='integer',help="Threshold for cells with maximum genes"),
+ make_option("--lm",action="store",default=0,type='numeric',help="Threshold for cells with minimum %mito genes"),
+ make_option("--hm",action="store",default=0.1,type='numeric',help="Threshold for cells with maximum %mito genes"),
+ make_option("--lx",action="store",default=0.2,type='numeric',help="x low threshold for hvg selection"),
+ make_option("--hx",action="store",default=5,type='numeric',help="x high threshold for hvg selection"),
+ make_option("--ly",action="store",default=1,type='numeric',help="y low threshold for hvg selection"),
+ make_option("--cc",action="store",default=TRUE,type='logical',help="Scale cell cycle?"),
+ make_option("--cca",action="store",default=50,type='integer',help="Number of CCAs to cacluate"),
+ make_option("--acca",action="store",default=30,type='integer',help="Number of CCAs to align"),
+ make_option("--pc",action="store",default=50,type='integer',help="Number of PCs to cacluate"),
+ make_option("--res.prestress",action="store",default=1,type='numeric',help="Resolution to cluster, pre-stress"),
+ make_option("--st",action="store",default=TRUE,type='logical',help="Remove stressed cells?"),
+ make_option("--stg",action="store",default="dws",type='character',help="Geneset to use for stress ID"),
+ make_option("--cut.stress",action="store",default=0.9,type='numeric',help="Cutoff for stress score"),
+ make_option("--res.poststress",action="store",default=0.5,type='numeric',help="Resolution to cluster, post-stress"),
+ make_option("--cut.ne",action="store",default=0.999,type='numeric',help="Cutoff for NE score")
+)
+opt=parse_args(OptionParser(option_list=option_list))
+rm(option_list)
+if (opt$lm==0){opt$lm=-Inf}
+
+load("./analysis/sc10x.Rda")
+
+for (i in c("Pb","Pc","Pd")){
+ if (!dir.exists(paste0("./analysis/tSNE/post.stress/",i))){
+ dir.create(paste0("./analysis/tSNE/post.stress/",i))
+ }
+ if (!dir.exists(paste0("./analysis/tSNE/lin/",i))){
+ dir.create(paste0("./analysis/tSNE/lin/",i))
+ }
+ if (!dir.exists(paste0("./analysis/tSNE/epi/",i))){
+ dir.create(paste0("./analysis/tSNE/epi/",i))
+ }
+ if (!dir.exists(paste0("./analysis/tSNE/st/",i))){
+ dir.create(paste0("./analysis/tSNE/st/",i))
+ }
+ if (!dir.exists(paste0("./analysis/tSNE/leu/",i))){
+ dir.create(paste0("./analysis/tSNE/leu/",i))
+ }
+
+ sc10x <- get(paste0("sc10x.",i))
+
+ sc10x <- scCluster(sc10x,pc.use=opt$acca,res.use=0.5,folder=paste0("post.stress/",i),red="cca.aligned")
+
+ gene.set1 <- read_delim("./genesets/DEG_Epi_5FC.txt","\t",escape_double=FALSE,trim_ws=TRUE,col_names=FALSE)
+ gene.set1 <- as.list(gene.set1)
+ names(gene.set1) <- "Epi"
+ gene.set <- c(gene.set1)
+ gene.set1 <- read_delim("./genesets/DEG_FMSt_5FC.txt","\t",escape_double=FALSE,trim_ws=TRUE,col_names=FALSE)
+ gene.set1 <- as.list(gene.set1)
+ names(gene.set1) <- "St"
+ gene.set <- c(gene.set,gene.set1)
+ rm(gene.set1)
+ gc()
+ min.all <- min(table(sc10x@meta.data[,paste0("res",0.5)]))
+ results <- scQuSAGE(sc10x,gs=gene.set,res.use=opt$res.poststress,ds=min.all,nm="Lin",folder=paste0("lin/",i))
+ sc10x <- results[[1]]
+ results.cor.Lin <- results[[2]]
+ results.clust.Lin.id <- results[[3]]
+ rm(results)
+ rm(gene.set)
+
+ sc10x <- SetAllIdent(object=sc10x,id="Lin")
+ sc10x.Epi <- scSubset(sc10x,i="Lin",g="Epi")
+ if (any(levels(sc10x@ident)=="Unknown")){
+ sc10x.St <- scSubset(sc10x,i="Lin",g=c("St","Unknown"))
+ } else {
+ sc10x.St <- scSubset(sc10x,i="Lin",g="St")
+ }
+
+ sc10x.Epi <- scCluster(sc10x.Epi,pc.use=opt$acca,res.use=opt$res.poststress,folder=paste0("epi/",i),red="cca.aligned")
+
+ #sc10x.Epi <- SetAllIdent(object=sc10x.Epi,id=paste0("res",opt$res.poststress))
+ #sc10x.Epi <- BuildClusterTree(sc10x.Epi,do.reorder=TRUE,reorder.numeric=TRUE,do.plot=FALSE)
+ sc10x.Epi <- StashIdent(object=sc10x.Epi,save.name=paste0("res",opt$res.poststress))
+
+ sc10x.Epi <- RunTSNE(object=sc10x.Epi,reduction.use="cca.aligned",dims.use=1:opt$acca,do.fast=TRUE)
+ postscript(paste0("./analysis/tSNE/epi/",i,"/tSNE_Sample.eps"))
+ plot <- TSNEPlot(object=sc10x.Epi,group.by="samples",pt.size=2.5,do.return=TRUE,vector.friendly=FALSE)
+ plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(size=20),axis.title.x=element_text(size=20),axis.title.y=element_text(size=20),legend.text=element_text(size=20))
+ plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
+ plot(plot)
+ dev.off()
+ postscript(paste0("./analysis/tSNE/epi/",i,"/tSNE_res",opt$res.poststress,".eps"))
+ plot <- TSNEPlot(object=sc10x.Epi,pt.size=5,do.label=TRUE,label.size=10,do.return=TRUE,vector.friendly=FALSE)
+ plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(size=20),axis.title.x=element_text(size=20),axis.title.y=element_text(size=20),legend.text=element_text(size=20))
+ plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
+ plot(plot)
+ dev.off()
+ rm(plot)
+
+ gene.set1 <- read_delim("./genesets/genes.deg.BE.csv",",",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
+ gene.set1 <- gene.set1[1]
+ gene.set1 <- as.list(gene.set1)
+ names(gene.set1) <- "BE"
+ gene.set <- c(gene.set1)
+ gene.set1 <- read_delim("./genesets/genes.deg.LE.csv",",",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
+ gene.set1 <- gene.set1[1]
+ gene.set1 <- as.list(gene.set1)
+ names(gene.set1) <- "LE"
+ gene.set <- c(gene.set,gene.set1)
+ gene.set1 <- read_delim("./genesets/genes.deg.OE1.csv",",",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
+ gene.set1 <- gene.set1[1]
+ gene.set1 <- as.list(gene.set1)
+ names(gene.set1) <- "Club"
+ gene.set <- c(gene.set,gene.set1)
+ gene.set1 <- read_delim("./genesets/genes.deg.OE2.csv",",",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
+ gene.set1 <- gene.set1[1]
+ gene.set1 <- as.list(gene.set1)
+ names(gene.set1) <- "Hillock"
+ gene.set <- c(gene.set,gene.set1)
+ rm(gene.set1)
+ gc()
+ min.epi <- min(table(sc10x.Epi@meta.data[,paste0("res",opt$res.poststress)]))
+ results <- scQuSAGE(sc10x.Epi,gs=gene.set,res.use=opt$res.poststress,ds=min.epi,nm="Epi.dws.sc",folder=paste0("epi/",i))
+ sc10x.Epi <- results[[1]]
+ results.cor.Epi <- results[[2]]
+ results.clust.Epi.id <- results[[3]]
+ rm(results)
+ rm(gene.set)
+
+
+ sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=opt$res.poststress,folder=paste0("st/",i),red="cca.aligned")
+
+ #sc10x.St <- SetAllIdent(object=sc10x.St,id=paste0("res",opt$res.poststress))
+ #sc10x.St <- BuildClusterTree(sc10x.St,do.reorder=TRUE,reorder.numeric=TRUE,do.plot=FALSE)
+ sc10x.St <- StashIdent(object=sc10x.St,save.name=paste0("res",opt$res.poststress))
+
+ sc10x.St <- RunTSNE(object=sc10x.St,reduction.use="cca.aligned",dims.use=1:opt$acca,do.fast=TRUE)
+ postscript(paste0("./analysis/tSNE/st/",i,"/tSNE_Sample.eps"))
+ plot <- TSNEPlot(object=sc10x.St,group.by="samples",pt.size=2.5,do.return=TRUE,vector.friendly=FALSE)
+ plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(size=20),axis.title.x=element_text(size=20),axis.title.y=element_text(size=20),legend.text=element_text(size=20))
+ plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
+ plot(plot)
+ dev.off()
+ postscript(paste0("./analysis/tSNE/st/",i,"/tSNE_res",opt$res.poststress,".eps"))
+ plot <- TSNEPlot(object=sc10x.St,pt.size=5,do.label=TRUE,label.size=10,do.return=TRUE,vector.friendly=FALSE)
+ plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(size=20),axis.title.x=element_text(size=20),axis.title.y=element_text(size=20),legend.text=element_text(size=20))
+ plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
+ plot(plot)
+ dev.off()
+ rm(plot)
+
+ gene.set1 <- read_delim("./genesets/genes.deg.Endo.csv",",",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
+ gene.set1 <- gene.set1[1]
+ gene.set1 <- as.list(gene.set1)
+ names(gene.set1) <- "Endo"
+ gene.set <- c(gene.set1)
+ gene.set1 <- read_delim("./genesets/genes.deg.SM.csv",",",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
+ gene.set1 <- gene.set1[1]
+ gene.set1 <- as.list(gene.set1)
+ names(gene.set1) <- "SM"
+ gene.set <- c(gene.set,gene.set1)
+ gene.set1 <- read_delim("./genesets/genes.deg.Fib.csv",",",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
+ gene.set1 <- gene.set1[1]
+ gene.set1 <- as.list(gene.set1)
+ names(gene.set1) <- "Fib"
+ gene.set <- c(gene.set,gene.set1)
+
+ genes.leu <- read_excel("genesets/40425_2017_215_MOESM1_ESM.xlsx",sheet="S3. Candidate markers")
+ leu <- as.list(unique(genes.leu[,2]))$Cell
+ leu <- leu[-c(1,3,4,7:9,14,15,17:18,20:21,23:30)]
+ genes.leu <- genes.leu[genes.leu$Selected==1,]
+ genes.leu <- genes.leu[unlist(genes.leu[,2]) %in% unlist(leu),]
+ gene.set1 <- split(genes.leu[,1], genes.leu[,2])
+ gene.set1 <- lapply(gene.set1,unname)
+ gene.set1 <- lapply(gene.set1,unlist)
+ gene.set <- c(gene.set,gene.set1)
+
+ rm(gene.set1)
+ gc()
+ min.st <- min(table(sc10x.St@meta.data[,paste0("res",opt$res.poststress)]))
+ results <- scQuSAGE(sc10x.St,gs=gene.set,res.use=opt$res.poststress,ds=min.st,nm="St.dws.sc",folder=paste0("st/",i))
+ sc10x.St <- results[[1]]
+ results.cor.St <- results[[2]]
+ results.clust.St.id <- results[[3]]
+ rm(results)
+ rm(gene.set)
+
+ sc10x.St <- SetAllIdent(object=sc10x.St,id="St.dws.sc")
+ sc10x.Leu <- scSubset(sc10x.St,i="St.dws.sc",g=leu[leu %in% unique(sc10x.St@ident)])
+
+ sc10x.Leu <- RunTSNE(object=sc10x.Leu,reduction.use="cca.aligned",dims.use=1:opt$acca,do.fast=TRUE)
+ postscript(paste0("./analysis/tSNE/leu/",i,"/tSNE_Sample.eps"))
+ plot <- TSNEPlot(object=sc10x.Leu,group.by="samples",pt.size=2.5,do.return=TRUE,vector.friendly=FALSE)
+ plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(size=20),axis.title.x=element_text(size=20),axis.title.y=element_text(size=20),legend.text=element_text(size=20))
+ plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
+ plot(plot)
+ dev.off()
+ postscript(paste0("./analysis/tSNE/leu/",i,"/tSNE_LeuLin.eps"))
+ plot <- TSNEPlot(object=sc10x.Leu,pt.size=5,do.label=TRUE,label.size=10,do.return=TRUE,vector.friendly=FALSE)
+ plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(size=20),axis.title.x=element_text(size=20),axis.title.y=element_text(size=20),legend.text=element_text(size=20))
+ plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
+ plot(plot)
+ dev.off()
+ rm(plot)
+
+ sc10x <- scMerge(sc10x,sc10x.Epi,sc10x.St,i.1="Epi.dws.sc",i.2="St.dws.sc",nm="Merge")
+
+ sc10x@ident <- factor(sc10x@ident,levels=c("BE","LE","Hillock","Club","Fib","SM","Endo","B-cells","T-cells","Macrophages","Mast cells"))
+ sctSNE3CustCol(sc10x,i="Merge",bl=c("BE","LE","Hillock","Club"),rd=c("Fib","SM","Endo"),gn=c("B-cells","T-cells","Macrophages","Mast cells"),file=i)
+
+ if (i=="Pd"){
+ for (j in list(c("D17PrPzF_Via","D27PrPzF_Via","D35PrPzF_Via"),c("D17PrTzF_Via","D27PrTzF_Via","D35PrTzF_Via"))){
+ sc10x.sub <- scSubset(sc10x,"samples",j)
+ sc10x.sub <- SetAllIdent(object=sc10x.sub,id="Merge")
+ sc10x.sub@ident <- factor(sc10x.sub@ident,levels=c("BE","LE","Hillock","Club","Fib","SM","Endo","B-cells","T-cells","Macrophages","Mast cells"))
+ sctSNE3CustCol(sc10x.sub,i="Merge",bl=c("BE","LE","Hillock","Club"),rd=c("Fib","SM","Endo"),gn=c("B-cells","T-cells","Macrophages","Mast cells"),file=paste0(i,".",substr(j[1],6,7)))
+ }
+ rm(sc10x.sub)
+ }
+
+ write.table(table(sc10x@meta.data[,"samples"],sc10x@meta.data[,"Merge"]),file=paste0("./analysis/table/Table_samples_Merge",i,".csv"),row.names=TRUE,col.names=NA,append=FALSE,sep=",")
+ write.table(round(prop.table(table(sc10x@meta.data[,"samples"],sc10x@meta.data[,"Merge"]),1)*100,1),file=paste0("./analysis/table/ProbTable_samples_Merge",i,".csv"),row.names=TRUE,col.names=NA,append=FALSE,sep=",")
+
+ assign(paste0("sc10x.",i,".analized"),sc10x)
+ assign(paste0("sc10x.Epi.",i,".analized"),sc10x.Epi)
+ assign(paste0("sc10x.St.",i,".analized"),sc10x.St)
+ assign(paste0("sc10x.Leu.",i,".analized"),sc10x.Leu)
+ assign(paste0("results.cor.Lin.",i),results.cor.Lin)
+ assign(paste0("results.clust.Lin.id.",i),results.clust.Lin.id)
+ assign(paste0("results.cor.Epi.",i),results.cor.Epi)
+ assign(paste0("results.clust.Epi.id.",i),results.clust.Epi.id)
+ assign(paste0("results.cor.St.",i),results.cor.St)
+ assign(paste0("results.clust.St.id.",i),results.clust.St.id)
+ rm(sc10x.sub)
+ rm(sc10x)
+ rm(sc10x.Epi)
+ rm(sc10x.St)
+ rm(sc10x.Leu)
+ rm(results.cor.Lin)
+ rm(results.cor.Epi)
+ rm(results.cor.St)
+ rm(results.clust.Lin.id)
+ rm(results.clust.Epi.id)
+ rm(results.clust.St.id)
+ rm(min.all)
+ rm(min.epi)
+ rm(min.st)
+ rm(i)
+}
+save.image(file="./analysis/sc10x.analized.RData")
+
--
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