diff --git a/r.scripts/sc-TissueMapper_RUN.D17_FACS.R b/r.scripts/sc-TissueMapper_RUN.D17_FACS.R
index f884af27dad9681b0f722d3ae5b8f7ee4e7e75f6..c991ebae0218f118363fc41d5031d2f2906a2836 100644
--- a/r.scripts/sc-TissueMapper_RUN.D17_FACS.R
+++ b/r.scripts/sc-TissueMapper_RUN.D17_FACS.R
@@ -107,7 +107,7 @@ option_list=list(
   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=0.2,type='numeric',help="Resolution to cluster, post-stress"),
+  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))
@@ -143,19 +143,6 @@ if (opt$cc==TRUE){
 }
 gc()
 
-#sc10x.D17 <- scSubset(sc10x,"D17","D17")
-#sc10x.D27 <- scSubset(sc10x,"D27","D27")
-#sc10x.D35 <- scSubset(sc10x,"D35","D35")
-
-#results <- sc3CCA(sc10x.D17,sc10x.D27,sc10x.D35,"D17","D27","D35",cc=opt$cc,cca=opt$cca,acca=opt$acca,lx=opt$lx,hx=opt$hx,ly=opt$ly)
-#sc10x <- results[[1]]
-#genes.hvg.cca <- results[[2]]
-#rm(results)
-
-#rm(sc10x.D17)
-#rm(sc10x.D27)
-#rm(sc10x.D35)
-
 results <- scPC(sc10x,lx=opt$lx,hx=opt$hx,ly=opt$ly,cc=opt$cc,pc=50,hpc=0.85,file="pre.stress",cca=FALSE)
 sc10x <- results[[1]]
 genes.hvg.prestress <- results[[2]]
@@ -192,8 +179,8 @@ 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=0.5,ds=min.all,nm="Lin",folder="lin")
+min.all <- min(table(sc10x@meta.data[,paste0("res",opt$res.poststress)]))
+results <- scQuSAGE(sc10x,gs=gene.set,res.use=opt$res.poststress,ds=min.all,nm="Lin",folder="lin")
 sc10x <- results[[1]]
 results.cor.Lin <- results[[2]]
 results.clust.Lin.id <- results[[3]]
@@ -206,12 +193,12 @@ if (any(levels(sc10x@ident)=="Unknown")){
 } else {
   sc10x.St <- scSubset(sc10x,i="Lin",g="St")
 }
-sc10x.Epi <- SetAllIdent(object=sc10x.Epi,id=paste0("res",0.5))
+sc10x.Epi <- SetAllIdent(object=sc10x.Epi,id=paste0("res",opt$res.poststress))
 sc10x.Epi <- BuildClusterTree(sc10x.Epi,do.reorder=TRUE,reorder.numeric=TRUE,do.plot=FALSE)
-sc10x.Epi <- StashIdent(object=sc10x.Epi,save.name=paste0("res",0.5))
-sc10x.St <- SetAllIdent(object=sc10x.St,id=paste0("res",0.5))
+sc10x.Epi <- StashIdent(object=sc10x.Epi,save.name=paste0("res",opt$res.poststress))
+sc10x.St <- SetAllIdent(object=sc10x.St,id=paste0("res",opt$res.poststress))
 sc10x.St <- BuildClusterTree(sc10x.St,do.reorder=TRUE,reorder.numeric=TRUE,do.plot=FALSE)
-sc10x.St <- StashIdent(object=sc10x.St,save.name=paste0("res",0.5))
+sc10x.St <- StashIdent(object=sc10x.St,save.name=paste0("res",opt$res.poststress))
 
 sc10x.Epi <- RunTSNE(object=sc10x.Epi,reduction.use="pca",dims.use=1:pc.use.poststress,do.fast=TRUE)
 postscript(paste0("./analysis/tSNE/epi/tSNE_Sample.eps"))
@@ -220,7 +207,7 @@ plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(si
 plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
 plot(plot)
 dev.off()
-postscript(paste0("./analysis/tSNE/epi/tSNE_res",0.5,".eps"))
+postscript(paste0("./analysis/tSNE/epi/tSNE_res",opt$res.poststress,".eps"))
 plot <- TSNEPlot(object=sc10x.Epi,pt.size=5,do.label=TRUE,label.size=10,do.return=TRUE,vector.friendly=FALSE)
 plot <- plot+theme(axis.text.x=element_text(size=20),axis.text.y=element_text(size=20),axis.title.x=element_text(size=20),axis.title.y=element_text(size=20),legend.text=element_text(size=20))
 plot <- plot+guides(colour=guide_legend(override.aes=list(size=10)))
@@ -248,78 +235,16 @@ gene.set1 <- gene.set1[1]
 gene.set1 <- as.list(gene.set1)
 names(gene.set1) <- "OE_KRT13"
 gene.set <- c(gene.set,gene.set1)
-#gene.set1 <- read_delim("./genesets/genes.deg.NE.csv",",",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
-#gene.set1 <- gene.set1[1]
-#gene.set1 <- as.list(gene.set1)
-#names(gene.set1) <- "NE"
-#gene.set <- c(gene.set,gene.set1)
 rm(gene.set1)
 gc()
-min.epi <- min(table(sc10x.Epi@meta.data[,paste0("res",0.5)]))
-results <- scQuSAGE(sc10x.Epi,gs=gene.set,res.use=0.5,ds=min.epi,nm="Epi.dws.sc",folder="epi")
+min.epi <- min(table(sc10x.Epi@meta.data[,paste0("res",opt$res.poststress)]))
+results <- scQuSAGE(sc10x.Epi,gs=gene.set,res.use=opt$res.poststress,ds=min.epi,nm="Epi.dws.sc",folder="epi")
 sc10x.Epi <- results[[1]]
 results.cor.Epi.dws <- results[[2]]
 results.clust.Epi.dws.id <- results[[3]]
 rm(results)
 rm(gene.set)
 
-#sc10x.Epi <- SetAllIdent(object=sc10x.Epi,id=paste0("res",opt$res.poststress))
-#OE <- levels(factor(sc10x.Epi@ident[sc10x.Epi@meta.data$Epi.dws=="OE"]))
-#OE.cells <- NULL
-#for (i in 1:length(OE)){
-#  OE.cells[i] <- list(names(sc10x.Epi@ident[sc10x.Epi@ident==OE[i]]))
-#}
-#sc10x.Epi <- SetAllIdent(object=sc10x.Epi,id="Epi.dws")
-#for (i in 1:length(OE)){
-#  sc10x.Epi <- SetIdent(object=sc10x.Epi,cells.use=unlist(OE.cells[i]),ident.use=paste0("OE",i))
-#}
-#sc10x.Epi <- StashIdent(object=sc10x.Epi,save.name="Epi.dws.sub")
-#postscript("./analysis/tSNE/epi/tSNE_Epi.dws.sub.eps")
-#plot <- TSNEPlot(object=sc10x.Epi,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()
-#rm(plot)
-#rm(OE)
-#rm(OE.cells)
-#rm(i)
-
-#gene.set1 <- read_csv("./genesets/Basal cells-signature-genes.csv")
-#gene.set1 <- gene.set1[,2]
-#gene.set1 <- as.list(gene.set1)
-#names(gene.set1) <- "BC"
-#gene.set <- c(gene.set1)
-#gene.set1 <- read_csv("./genesets/Normal AT2 cells-signature-genes.csv")
-#gene.set1 <- gene.set1[,2]
-#gene.set1 <- as.list(gene.set1)
-#names(gene.set1) <- "AT2"
-#gene.set <- c(gene.set,gene.set1)
-#gene.set1 <- read_csv("./genesets/Club_Goblet cells-signature-genes.csv")
-#gene.set1 <- gene.set1[,2]
-#gene.set1 <- as.list(gene.set1)
-#names(gene.set1) <- "CGC"
-#gene.set<- c(gene.set,gene.set1)
-#rm(gene.set1)
-#gc()
-#results.cor.Epi.lgea <- scQuSAGEsm(sc10x.Epi,gs=gene.set,ds=min.epi,nm="Epi.dws.sub",folder="lgea")
-#rm(gene.set)
-
-sc10x.St <- RunTSNE(object=sc10x.St,reduction.use="pca",dims.use=1:pc.use.poststress,do.fast=TRUE)
-postscript(paste0("./analysis/tSNE/st/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/tSNE_res",0.5,".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)
@@ -342,8 +267,8 @@ names(gene.set1) <- "Leu"
 gene.set <- c(gene.set,gene.set1)
 rm(gene.set1)
 gc()
-min.st <- min(table(sc10x.St@meta.data[,paste0("res",0.5)]))
-results <- scQuSAGE(sc10x.St,gs=gene.set,res.use=0.5,ds=min.st,nm="St.dws.sc",folder="st")
+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="st")
 sc10x.St <- results[[1]]
 results.cor.St.go <- results[[2]]
 results.clust.St.go.id <- results[[3]]
@@ -352,72 +277,12 @@ rm(gene.set)
 
 sc10x.Epi.NE <- scNE(sc10x.Epi,neg="dws",cut=opt$cut.ne)
 
-#sc10x.Epi <- scMergeSubClust(sc10x.Epi,i="Epi.dws.sub",g=c("BE","LE"),nm="Merge")
-
-#sc10x.St <- scMergeSubClust(sc10x.St,i="St.go",g=c("Endo","SM","Fib","Leu"),nm="Merge")
-
 sc10x <- scMerge(sc10x,sc10x.Epi,sc10x.St,i.1="Epi.dws.sc",i.2="St.dws.sc",nm="Merge_Epi.dws.sc_St.dws.sc")
 
 sc10x <- scMerge(sc10x,sc10x,sc10x.Epi.NE,i.1="Merge_Epi.dws.sc_St.dws.sc",i.2="NE",nm="Merge_Epi.dws.sc_St.dws.sc_NE")
 
 sc10x.Epi <- scMerge(sc10x.Epi,sc10x.Epi,sc10x.Epi.NE,i.1="Epi.dws.sc",i.2="NE",nm="Epi.dws.sc_NE")
 
-#gene.orthog <- read.delim("./genesets/Ensemble.mus-hum.txt")
-#gene.set1 <- read_csv("./genesets/SupTab3_Consensus_Sigs.csv",skip=6)
-#gene.set2 <- as.data.frame(gene.set1$Basal[!is.na(gene.set1$Basal)])
-#colnames(gene.set2) <- "genes"
-#gene.set2 <- as.data.frame(merge(gene.set2,gene.orthog,by.x="genes",by.y="Gene.name")[,4])
-#gene.set2 <- as.list(gene.set2)
-#names(gene.set2) <- "Basal"
-#gene.set <- c(gene.set2)
-#gene.set2 <- as.data.frame(gene.set1$Club[!is.na(gene.set1$Club)])
-#colnames(gene.set2) <- "genes"
-#gene.set2 <- as.data.frame(merge(gene.set2,gene.orthog,by.x="genes",by.y="Gene.name")[,4])
-#gene.set2 <- as.list(gene.set2)
-#names(gene.set2) <- "Club"
-#gene.set <- c(gene.set,gene.set2)
-#gene.set2 <- as.data.frame(gene.set1$Ciliated[!is.na(gene.set1$Ciliated)])
-#colnames(gene.set2) <- "genes"
-#gene.set2 <- as.data.frame(merge(gene.set2,gene.orthog,by.x="genes",by.y="Gene.name")[,4])
-#gene.set2 <- as.list(gene.set2)
-#names(gene.set2) <- "Ciliated"
-#gene.set <- c(gene.set,gene.set2)
-#gene.set2 <- as.data.frame(gene.set1$Tuft[!is.na(gene.set1$Tuft)])
-#colnames(gene.set2) <- "genes"
-#gene.set2 <- as.data.frame(merge(gene.set2,gene.orthog,by.x="genes",by.y="Gene.name")[,4])
-#gene.set2 <- as.list(gene.set2)
-#names(gene.set2) <- "Tuft"
-#gene.set <- c(gene.set,gene.set2)
-#gene.set2 <- as.data.frame(gene.set1$Neuroendocrine[!is.na(gene.set1$Neuroendocrine)])
-#colnames(gene.set2) <- "genes"
-#gene.set2 <- as.data.frame(merge(gene.set2,gene.orthog,by.x="genes",by.y="Gene.name")[,4])
-#gene.set2 <- as.list(gene.set2)
-#names(gene.set2) <- "Neuroendocrine"
-#gene.set <- c(gene.set,gene.set2)
-#gene.set2 <- as.data.frame(gene.set1$Ionocyte[!is.na(gene.set1$Ionocyte)])
-#colnames(gene.set2) <- "genes"
-#gene.set2 <- as.data.frame(merge(gene.set2,gene.orthog,by.x="genes",by.y="Gene.name")[,4])
-#gene.set2 <- as.list(gene.set2)
-#names(gene.set2) <- "Ionocyte"
-#gene.set <- c(gene.set,gene.set2)
-#rm(gene.set2)
-#gene.set1 <- read_csv("./genesets/SupTab6_Krt13_Hillock.csv",skip=6)
-#gene.set1 <- gene.set1[gene.set1$FDR<=0.05 & gene.set1$'log2 fold-change (MAST)'>=1.5,1]
-#colnames(gene.set1) <- "genes"
-#gene.set1 <- as.data.frame(merge(gene.set1,gene.orthog,by.x="genes",by.y="Gene.name")[,4])
-#gene.set1 <- as.list(gene.set1)
-#names(gene.set1) <- "Hillock"
-#gene.set <- c(gene.set,gene.set1)
-#rm(gene.set1)
-#rm(gene.orthog)
-#gene.set <- lapply(gene.set,droplevels)
-#results.cor.Epi.MusLungHierarchy <- scQuSAGEsm(sc10x.Epi,gs=gene.set,ds=min.epi,nm="Epi.dws.sub_NE",folder="MusLungHierarchy")
-#rm(gene.set)
-
-#gene.set.c2.all <- read.gmt("./genesets/c2.all.v6.1.symbols.gmt")
-#results.cor.c2.ALL <- scQuSAGElg(sc10x,gs=gene.set.c2.all,ds=min.all,nm="Merge_Epi.dws_St.go",folder="c2.all")
-#rm(gene.set.c2.all)
-
 sc10x <- SetAllIdent(object=sc10x,id="Merge_Epi.dws.sc_St.dws.sc")
 sc10x@ident <- factor(sc10x@ident,levels=c("BE","LE","OE_SCGB","OE_KRT13","Fib","SM","Endo","Leu"))
 postscript("./analysis/tSNE/FINAL/tSNE_FINAL.eps")
@@ -431,91 +296,14 @@ scTables(sc10x,i.1="samples",i.2="Merge_Epi.dws.sc_St.dws.sc")
 scTables(sc10x,i.1="samples",i.2="Merge_Epi.dws.sc_St.dws.sc_NE")
 scTables(sc10x,i.1="Merge_Epi.dws.sc_St.dws.sc_NE",i.2="Merge_Epi.dws.sc_St.dws.sc")
 
-# genes.deg.Stress <- scDEG(sc10x.Stress,i="Stress",g.1="Stress",g.2="ALL",pct=0.5,t=5)
-# 
-# genes.deg.Epi <- scDEG(sc10x,i="Lin",g.1="Epi",g.2="St",t=2)
-# genes.deg.St <- scDEG(sc10x,i="Lin",g.1="St",g.2="Epi",t=2)
-# 
-# genes.deg.BE <- scDEG(sc10x.Epi.NE,i="Epi.dws.sub",g.1="BE",g.2=c("LE","OE1","OE2"),pct=0.25,t=2)
-# genes.deg.LE <- scDEG(sc10x.Epi.NE,i="Epi.dws.sub",g.1="LE",g.2=c("BE","LE","OE1"),pct=0.25,t=2)
-# genes.deg.OE1 <- scDEG(sc10x.Epi.NE,i="Epi.dws.sub",g.1="OE1",g.2=c("BE","LE","OE2"),pct=0.25,t=2)
-# genes.deg.OE2 <- scDEG(sc10x.Epi.NE,i="Epi.dws.sub",g.1="OE2",g.2=c("BE","LE","OE1"),pct=0.25,t=2)
-# 
-# genes.deg.NE <- scDEG(sc10x.Epi.NE,i="NE",g.1="NE",g.2="ALL",pct=0.01,t=1)
-# 
-# genes.deg.Fib <- scDEG(sc10x.St,i="Merge_Epi.dws_St.go_NE",g.1="Fib",g.2=c("SM","Endo","Leu"),pct=0.25,t=2)
-# genes.deg.SM <- scDEG(sc10x.St,i="Merge_Epi.dws_St.go_NE",g.1="SM",g.2=c("Fib","Endo","Leu"),pct=0.25,t=2)
-# genes.deg.Endo <- scDEG(sc10x.St,i="Merge_Epi.dws_St.go_NE",g.1="Endo",g.2=c("Fib","SM","Leu"),pct=0.25,t=2)
-# genes.deg.Leu <- scDEG(sc10x.St,i="St.go",g.1="Leu",g.2=c("Fib","SM","Endo"),pct=0.25,t=2)
-# 
-# genes.deg.BE.unique <- setdiff(rownames(genes.deg.BE),Reduce(union,list(rownames(genes.deg.LE),rownames(genes.deg.OE1),rownames(genes.deg.OE2),rownames(genes.deg.NE),rownames(genes.deg.Fib),rownames(genes.deg.SM),rownames(genes.deg.Endo),rownames(genes.deg.Leu))))
-# genes.deg.LE.unique <- setdiff(rownames(genes.deg.LE),Reduce(union,list(rownames(genes.deg.BE),rownames(genes.deg.OE1),rownames(genes.deg.OE2),rownames(genes.deg.NE),rownames(genes.deg.Fib),rownames(genes.deg.SM),rownames(genes.deg.Endo),rownames(genes.deg.Leu))))
-# genes.deg.OE1.unique <- setdiff(rownames(genes.deg.OE1),Reduce(union,list(rownames(genes.deg.BE),rownames(genes.deg.LE),rownames(genes.deg.OE2),rownames(genes.deg.NE),rownames(genes.deg.Fib),rownames(genes.deg.SM),rownames(genes.deg.Endo),rownames(genes.deg.Leu))))
-# genes.deg.OE2.unique <- setdiff(rownames(genes.deg.OE2),Reduce(union,list(rownames(genes.deg.BE),rownames(genes.deg.LE),rownames(genes.deg.OE1),rownames(genes.deg.NE),rownames(genes.deg.Fib),rownames(genes.deg.SM),rownames(genes.deg.Endo),rownames(genes.deg.Leu))))
-# genes.deg.NE.unique <- setdiff(rownames(genes.deg.NE),Reduce(union,list(rownames(genes.deg.BE),rownames(genes.deg.LE),rownames(genes.deg.OE1),rownames(genes.deg.OE2),rownames(genes.deg.Fib),rownames(genes.deg.SM),rownames(genes.deg.Endo),rownames(genes.deg.Leu))))
-# genes.deg.Fib.unique <- setdiff(rownames(genes.deg.Fib),Reduce(union,list(rownames(genes.deg.BE),rownames(genes.deg.LE),rownames(genes.deg.OE1),rownames(genes.deg.OE2),rownames(genes.deg.NE),rownames(genes.deg.SM),rownames(genes.deg.Endo),rownames(genes.deg.Leu))))
-# genes.deg.SM.unique <- setdiff(rownames(genes.deg.SM),Reduce(union,list(rownames(genes.deg.BE),rownames(genes.deg.LE),rownames(genes.deg.OE1),rownames(genes.deg.OE2),rownames(genes.deg.NE),rownames(genes.deg.Fib),rownames(genes.deg.Endo),rownames(genes.deg.Leu))))
-# genes.deg.Endo.unique <- setdiff(rownames(genes.deg.Endo),Reduce(union,list(rownames(genes.deg.BE),rownames(genes.deg.LE),rownames(genes.deg.OE1),rownames(genes.deg.OE2),rownames(genes.deg.NE),rownames(genes.deg.Fib),rownames(genes.deg.SM),rownames(genes.deg.Leu))))
-# genes.deg.Leu.unique <- setdiff(rownames(genes.deg.Leu),Reduce(union,list(rownames(genes.deg.BE),rownames(genes.deg.LE),rownames(genes.deg.OE1),rownames(genes.deg.OE2),rownames(genes.deg.NE),rownames(genes.deg.Fib),rownames(genes.deg.SM),rownames(genes.deg.Endo))))
-# 
-# genes.deg.5 <- c(genes.deg.BE.unique[1:5],genes.deg.LE.unique[1:5],genes.deg.OE1.unique[1:5],genes.deg.OE2.unique[1:5],genes.deg.NE.unique[1:5],genes.deg.Fib.unique[1:5],genes.deg.SM.unique[1:5],genes.deg.Endo.unique[1:5],genes.deg.Leu.unique[1:5])
-# genes.deg.5 <- rev(genes.deg.5)
-# genes.deg.10 <- c(genes.deg.BE.unique[1:10],genes.deg.LE.unique[1:10],genes.deg.OE1.unique[1:10],genes.deg.OE2.unique[1:10],genes.deg.NE.unique[1:10],genes.deg.Fib.unique[1:10],genes.deg.SM.unique[1:10],genes.deg.Endo.unique[1:10],genes.deg.Leu.unique[1:10])
-# genes.deg.10 <- rev(genes.deg.10)
-# 
-# sc10x <- SetAllIdent(object=sc10x,id="Merge_Epi.dws_St.go_NE")
-# sc10x <- SetAllIdent(object=sc10x,id="Merge_Epi.dws_St.go_NE")
-# sc10x@ident <- factor(sc10x@ident,levels=c("BE","LE","OE1","OE2","NE","Fib","SM","Endo","Leu"))
-# postscript("./analysis/deg/Dot.DEG.eps",paper="special",width=10,height=5,horizontal=FALSE)
-# DotPlot(sc10x,genes.deg.5,x.lab.rot=TRUE,plot.legend=TRUE,dot.scale=4)
-# dev.off()
-# postscript("./analysis/deg/Heatmap.DEG.eps",paper="special",width=10,height=5,horizontal=FALSE)
-# plot(DoHeatmap(sc10x,genes.use=genes.deg.10,slim.col.label=TRUE,group.label.rot=TRUE,group.spacing=0.25,cex.row=2.5))
-# dev.off()
-# 
-# for (i in ls(pattern="^genes.deg*unique")){
-#   postscript(paste0("./analysis/deg/Violin.",i,".eps"),paper="special",width=10,height=5,horizontal=FALSE)
-#   plot(VlnPlot(sc10x,features.plot=get(i)[1:10],nCol=5,point.size.use=0.1,size.title.use=15,x.lab.rot=TRUE))
-#   dev.off()
-#   postscript(paste0("./analysis/deg/Ridge.",i,".eps"),paper="special",width=10,height=5,horizontal=FALSE)
-#   plot(RidgePlot(sc10x,features.plot=get(i)[1:10],nCol=5,size.x.use=10,size.title.use=15))
-#   dev.off()
-#   postscript(paste0("./analysis/deg/Heatmap.",i,".eps"),paper="special",width=10,height=5,horizontal=FALSE)
-#   plot(DoHeatmap(sc10x,genes.use=get(i),slim.col.label=TRUE,group.label.rot=TRUE,group.spacing=0.25,cex.row=2.5))
-#   dev.off()
-# }
-# 
-# sc10x.Stress <- SetAllIdent(object=sc10x.Stress,id="Stress")
-# postscript("./analysis/deg/Violin.Stress.eps",paper="special",width=10,height=5,horizontal=FALSE)
-# plot(VlnPlot(sc10x.Stress,features.plot=rownames(genes.deg.Stress)[1:10],nCol=5,point.size.use=0.1,size.title.use=15,x.lab.rot=TRUE))
-# dev.off()
-# postscript("./analysis/deg/Ridge.Stress.eps",paper="special",width=10,height=5,horizontal=FALSE)
-# plot(RidgePlot(sc10x.Stress,features.plot=rownames(genes.deg.Stress)[1:10],nCol=5,size.x.use=10,size.title.use=15))
-# dev.off()
-# postscript("./analysis/deg/Heatmap.Stress.eps",paper="special",width=10,height=5,horizontal=FALSE)
-# plot(DoHeatmap(sc10x.Stress,genes.use=rownames(genes.deg.Stress),slim.col.label=TRUE,group.label.rot=TRUE,group.spacing=0.25,cex.row=2.5))
-# dev.off()
-# 
-# sc10x.Epi.NE <- SetAllIdent(object=sc10x.Epi.NE,id="NE")
-# postscript("./analysis/deg/Violin.NE.eps",paper="special",width=10,height=5,horizontal=FALSE)
-# plot(VlnPlot(sc10x.Epi.NE,features.plot=rownames(genes.deg.NE)[1:10],nCol=5,point.size.use=0.1,size.title.use=15,x.lab.rot=TRUE))
-# dev.off()
-# postscript("./analysis/deg/Ridge.NE.eps",paper="special",width=10,height=5,horizontal=FALSE)
-# plot(RidgePlot(sc10x.Epi.NE,features.plot=rownames(genes.deg.NE)[1:10],nCol=5,size.x.use=10,size.title.use=15))
-# dev.off()
-# 
-# for (i in ls(pattern="^genes.deg")){
-#   write.table(get(i),file=paste0("./analysis/deg/",i,".csv"),row.names=TRUE,col.names=NA,append=FALSE,sep=",")
-# }
-
 sctSNECustCol(sc10x,i="Lin",bl="Epi",rd="St",file="D17")
 sctSNECustCol(sc10x,i="Merge_Epi.dws.sc_St.dws.sc",bl=c("BE","LE","OE_SCGB","OE_KRT13"),rd=c("Fib","SM","Endo","Leu"),file="D17")
 sctSNECustCol(sc10x.Epi,i="Epi.dws.sc",bl=c("BE","LE","OE_SCGB","OE_KRT13"),rd="",file="D17")
 sctSNECustCol(sc10x.St,i="St.dws.sc",bl="",rd=c("Fib","SM","Endo","Leu"),file="D17")
 
-sctSNEbwCol(sc10x,i="res0.5",file="ALL",files="D17")
-sctSNEbwCol(sc10x.Epi,i="res0.5",file="Epi",files="D17")
-sctSNEbwCol(sc10x.St,i="res0.5",file="St",files="D17")
+sctSNEbwCol(sc10x,i=paste0("res",opt$res.poststress),file="ALL",files="D17")
+sctSNEbwCol(sc10x.Epi,i=paste0("res",opt$res.poststress),file="Epi",files="D17")
+sctSNEbwCol(sc10x.St,i=paste0("res",opt$res.poststress),file="St",files="D17")
 sctSNEbwCol(sc10x,i="Merge_Epi.dws.sc_St.dws.sc",file="ALL",files="D17")
 sctSNEbwCol(sc10x.Epi,i="Epi.dws.sc",file="Epi",files="D17")
 sctSNEbwCol(sc10x.St,i="St.dws.sc",file="St",files="D17")
@@ -535,24 +323,15 @@ for (g in c("Fib","SM","Endo","Leu")){
 for (g in c("D17PrPzF_BE","D17PrPzF_LE","D17PrPzF_OE","D17PrPzF_FMSt")){
   sctSNEHighlight(sc10x,i="samples",g=g,file="D17")
 }
-#sctSNEHighlight(sc10x,i="Pz",g="Pz",file="D")
-#sctSNEHighlight(sc10x,i="Tz",g="Tz",file="D")
 rm(i)
 rm(g)
 
-#scCustHeatmap(sc10x.Epi,i="Epi.dws.sub",gs=c(genes.deg.BE.unique,genes.deg.LE.unique,genes.deg.OE1.unique,genes.deg.OE2.unique),g=c("BE","LE","OE1","OE2"))
-#scCustHeatmap(sc10x.St,i="St.go",gs=c(genes.deg.Fib.unique,genes.deg.SM.unique,genes.deg.Endo.unique,genes.deg.OE2.unique,genes.deg.Leu.unique),g=c("Fib","SM","Endo","Leu"))
-
 postscript(paste0("./analysis/diy/Feature.eps"))
 FeaturePlot(sc10x,features.plot=c("PECAM1","CD200","PDPN","EPCAM","DPP4","PSCA","VIM","KRT5","KLK3"),cols.use=c("grey","darkred"),reduction.use="tsne")
 dev.off()
 
-#scPseudotime(sc10x.Epi,i="Epi.dws.sub",ds=0)
-
 save(list=ls(pattern="sc10x.Stress"),file="./analysis/sc10x.Stress.Rda")
 rm(list=ls(pattern="sc10x.Stress"))
-save(list=ls(pattern="^genes.deg"),file="./analysis/DEG.Rda")
-rm(list=ls(pattern="^genes.deg"))
 save(list=ls(pattern="sc10x.Epi"),file="./analysis/sc10x.Epi.Rda")
 rm(list=ls(pattern="^sc10x.Epi"))
 save(list=ls(pattern="sc10x.St"),file="./analysis/sc10x.St.Rda")