diff --git a/bash.scripts/sc_TissueMapper-Pd.sh b/bash.scripts/sc_TissueMapper-Pd.sh
index 4c4ef806410f3e4bcf5c2f3ea1f5e3138cfcb31c..ba634e4d1d16a18814001c81718de640c0db6f56 100644
--- a/bash.scripts/sc_TissueMapper-Pd.sh
+++ b/bash.scripts/sc_TissueMapper-Pd.sh
@@ -13,3 +13,4 @@ module load R/3.4.1-gccmkl_20181025
 sh ./sc_LinkData.sh Pd
 
 Rscript ../r.scripts/sc-TissueMapper_RUN.Pd.R
+Rscript ../r.scripts/sc-TissueMapper_RUN.Pd.StressCompare.R
diff --git a/r.scripts/sc-TissueMapper_RUN.Pd.StressCompare.R b/r.scripts/sc-TissueMapper_RUN.Pd.StressCompare.R
new file mode 100755
index 0000000000000000000000000000000000000000..fc23ed8ce0e316175feeb4840d48c6b99a85b61e
--- /dev/null
+++ b/r.scripts/sc-TissueMapper_RUN.Pd.StressCompare.R
@@ -0,0 +1,135 @@
+library(methods)
+library(optparse)
+library(Seurat)
+library(readr)
+library(fBasics)
+library(pastecs)
+library(qusage)
+library(RColorBrewer)
+library(VennDiagram)
+library(Cairo)
+
+options(bitmapType="cairo")
+
+if (!dir.exists("../analysis/stress")){
+  dir.create("../analysis/stress")
+}
+
+load("../analysis/sc10x.Stress.Rda")
+sc10x.Stress <- SetAllIdent(object=sc10x.Stress,id="ALL")
+gene.exp <- as.data.frame(as.matrix(sc10x.Stress@raw.data[,colnames(sc10x.Stress@data)]))
+
+genes.stress.go <- read_csv("../genesets/DEG_C2.CGP.M10970.txt")
+genes.stress.go <- genes.stress.go[2:nrow(genes.stress.go),]
+genes.stress.go <- as.list(genes.stress.go)
+
+genes.stress.dws <- read_delim("../genesets/genes.deg.Stress.csv",",",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
+genes.stress.dws <- genes.stress.dws[1]
+colnames(genes.stress.dws) <- "scDWS.Stress"
+genes.stress.dws <- as.list(genes.stress.dws)
+
+#genes.stress.vdb <- read_delim("./vanderBrink.Stress.mus.tsv","\t",escape_double=FALSE,trim_ws=TRUE,col_names=FALSE)
+#colnames(genes.stress.vdb) <- "vdBrink.Stress"
+
+genes.stress.vdb <- c("Actg1__chr11","Ankrd1__chr19","Arid5a__chr1","Atf3__chr1","Atf4__chr15","Bag3__chr7","Bhlhe40__chr6","Brd2__chr17","Btg1__chr10","Btg2__chr1","Ccnl1__chr3","Ccrn4l__chr3","Cebpb__chr2","Cebpd__chr16","Cebpg__chr7","Csrnp1__chr9","Cxcl1__chr5","Cyr61__chr3","Dcn__chr10","Ddx3x__chrX","Ddx5__chr11","Des__chr1","Dnaja1__chr4","Dnajb1__chr8","Dnajb4__chr3","Dusp1__chr17","Dusp8__chr7","Egr1__chr18","Egr2__chr10","Eif1__chr11","Eif5__chr12","Erf__chr7","Errfi1__chr4","Fam132b__chr1","Fos__chr12","Fosb__chr7","Fosl2__chr5","Gadd45a__chr6","Gcc1__chr6","Gem__chr4","H3f3b__chr11","Hipk3__chr2","Hsp90aa1__chr12","Hsp90ab1__chr17","Hspa1a__chr17","Hspa1b__chr17","Hspa5__chr2","Hspa8__chr9","Hspb1__chr5","Hsph1__chr5","Id3__chr4","Idi1__chr13","Ier2__chr8","Ier3__chr17","Ifrd1__chr12","Il6__chr5","Irf1__chr11","Irf8__chr8","Itpkc__chr7","Jun__chr4","Junb__chr8","Jund__chr8","Klf2__chr8","Klf4__chr4","Klf6__chr13","Klf9__chr19","Litaf__chr16","Lmna__chr3","Maff__chr15","Mafk__chr5","Mcl1__chr3","Midn__chr10","Mir22hg__chr11","Mt1__chr8","Mt2__chr8","Myadm__chr7","Myc__chr15","Myd88__chr9","Nckap5l__chr15","Ncoa7__chr10","Nfkbia__chr12","Nfkbiz__chr16","Nop58__chr1","Nppc__chr1","Nr4a1__chr15","Odc1__chr12","Osgin1__chr8","Oxnad1__chr14","Pcf11__chr7","Pde4b__chr4","Per1__chr11","Phlda1__chr10","Pnp__chr14","Pnrc1__chr4","Ppp1cc__chr5","Ppp1r15a__chr7","Pxdc1__chr13","Rap1b__chr10","Rassf1__chr9","Rhob__chr12","Rhoh__chr5","Ripk1__chr13","Sat1__chrX","Sbno2__chr10","Sdc4__chr2","Serpine1__chr5","Skil__chr3","Slc10a6__chr5","Slc38a2__chr15","Slc41a1__chr1","Socs3__chr11","Sqstm1__chr11","Srf__chr17","Srsf5__chr12","Srsf7__chr17","Stat3__chr11","Tagln2__chr1","Tiparp__chr3","Tnfaip3__chr10","Tnfaip6__chr2","Tpm3__chr3","Tppp3__chr8","Tra2a__chr6","Tra2b__chr16","Trib1__chr15","Tubb4b__chr2","Tubb6__chr18","Ubc__chr5","Usp2__chr9","Wac__chr18","Zc3h12a__chr4","Zfand5__chr19","Zfp36__chr7","Zfp36l1__chr12","Zfp36l2__chr17","Zyx__chr6","Gadd45g__chr13","Hspe1__chr1","Ier5__chr1","Kcne4__chr1")
+genes.stress.vdb <- gsub("\\__.*","",genes.stress.vdb)
+genes.stress.vdb <- data.frame(vdBrink.Stress=genes.stress.vdb)
+genes.homolog <- read_delim("../genesets/Ensemble.mus-hum.txt","\t",escape_double=FALSE,trim_ws=TRUE,col_names=TRUE)
+genes.stress.vdb <- list("vdBrink.Stress"=merge(genes.stress.vdb,genes.homolog[,c(2,4)],by.x="vdBrink.Stress",by.y="Gene name")[,2])
+
+venn.diagram(list(go=unlist(genes.stress.go),dws=unlist(genes.stress.dws),vdb=unlist(genes.stress.vdb)),"../analysis/stress/Venn.tiff")
+
+
+for (i in c("go","dws","vdb")){
+  genes.stress=get(paste0("genes.stress.",i))
+  
+  gene.stress.pct <- apply(gene.exp,2,function(x) sum(x[rownames(gene.exp) %in% unlist(genes.stress)])/sum(x))
+
+  #histo <- hist(gene.stress.pct,breaks=100,prob=TRUE,plot=TRUE,main="Distribution of Stress Gene Expression in Transcriptome",xlab="% of transcriptome associated to stress genes")
+  #abline(v=.0575,col="red")
+
+  sc10x.Stress <- SetAllIdent(object=sc10x.Stress,id="ALL+Stress")
+  cell.index.stress <- names(sc10x.Stress@ident[sc10x.Stress@ident=="Stress"])
+  cell.index.stress <- which(colnames(gene.exp) %in% cell.index.stress)
+  cell.index.ntstress <- names(sc10x.Stress@ident[sc10x.Stress@ident=="ALL"])
+  cell.index.ntstress <- which(colnames(gene.exp) %in% cell.index.ntstress)
+
+  histo.stress <- hist(gene.stress.pct[cell.index.stress],breaks=seq(0,ceiling(max(gene.stress.pct)*100)/100,0.005),main="Distribution of Stress Gene Expression in Transcriptome",xlab="% of transcriptome associated to stress genes",plot=FALSE)
+  #abline(v=.0575,col="red")
+  histo.ntstress <- hist(gene.stress.pct[cell.index.ntstress],breaks=seq(0,ceiling(max(gene.stress.pct)*100)/100,0.005),main="Distribution of Stress Gene Expression in Transcriptome",xlab="% of transcriptome associated to stress genes",plot=FALSE)
+  #abline(v=.0575,col="red")
+  
+  Cairo(paste0("../analysis/stress/Hist.Stress.",i,".png"),width=1000,height=500,bg="white")
+  plot(histo.ntstress$mids,histo.ntstress$density,col=rgb(0,1,0,1/5),xlim=c(0,ceiling(max(gene.stress.pct)*100)/100),ylim=c(0,ceiling(max(histo.stress$density,histo.ntstress$density)/10)*10),type="h",lend="square",lwd=10,xlab="Fraction of transcriptome associated to stress genes",ylab="Density")
+  par(new=TRUE)
+  plot(histo.stress$mids,histo.stress$density,col=rgb(1,0,0,1/5),xlim=c(0,ceiling(max(gene.stress.pct)*100)/100),ylim=c(0,ceiling(max(histo.stress$density,histo.ntstress$density)/10)*10),type="h",lend="square",lwd=10,axes=FALSE,xlab="",ylab="")
+  abline(v=0.0575,col="red")
+  text(0.0575+0.01,(ceiling(max(histo.stress$density,histo.ntstress$density)/10)*10)/4*3+2.5,paste0(round(sum(histo.ntstress$counts[histo.ntstress$breaks>0.035][!is.na(histo.ntstress$counts[histo.ntstress$breaks>0.035])])/sum(histo.ntstress$counts[!is.na(histo.ntstress$counts)])*100),"%"),col="green")
+  text(0.0575-0.01,(ceiling(max(histo.stress$density,histo.ntstress$density)/10)*10)/4*3+2.5,paste0(round(sum(histo.ntstress$counts[histo.ntstress$breaks<=0.035][!is.na(histo.ntstress$counts[histo.ntstress$breaks<=0.035])])/sum(histo.ntstress$counts[!is.na(histo.ntstress$counts)])*100),"%"),col="green")
+  text(0.0575+0.01,(ceiling(max(histo.stress$density,histo.ntstress$density)/10)*10)/4*3-2.5,paste0(round(sum(histo.stress$counts[histo.stress$breaks>0.035][!is.na(histo.stress$counts[histo.stress$breaks>0.035])])/sum(histo.stress$counts[!is.na(histo.stress$counts)])*100),"%"),col="red")
+  text(0.0575-0.01,(ceiling(max(histo.stress$density,histo.ntstress$density)/10)*10)/4*3-2.5,paste0(round(sum(histo.stress$counts[histo.stress$breaks<=0.035][!is.na(histo.stress$counts[histo.stress$breaks<=0.035])])/sum(histo.stress$counts[!is.na(histo.stress$counts)])*100),"%"),col="red")
+  text(0.0575+0.05,(ceiling(max(histo.stress$density,histo.ntstress$density)/10)*10)/4*3+2.5,"Not Stressed",col="green")
+  text(0.0575+0.05,(ceiling(max(histo.stress$density,histo.ntstress$density)/10)*10)/4*3-2.5,"Stressed",col="red")
+  dev.off()
+}
+rm(i)
+rm(genes.stress)
+rm(gene.stress.pct)
+rm(cell.index.stress)
+rm(cell.index.ntstress)
+rm(histo.stress)
+rm(histo.ntstress)
+
+for (cut in c(0.9,0.95)){
+  for (i in c("go","dws","vdb")){
+    genes.stress=get(paste0("genes.stress.",i))
+    sc10x.Stress <- SetAllIdent(object=sc10x.Stress,id="ALL")
+    sc10x.Stress.dta <- as.data.frame(as.matrix(sc10x.Stress@data[rownames(sc10x.Stress@scale.data) %in% unlist(genes.stress),]))
+    
+    #Run PCA of subsetted stress genes
+    sc10x.Stress.dta <- t(sc10x.Stress.dta)
+    sc10x.Stress.dta <- sc10x.Stress.dta[,apply(sc10x.Stress.dta,2,var)!=0]
+    sc10x.Stress.dta.pca <- prcomp(sc10x.Stress.dta,center=TRUE,scale.=TRUE)
+    sc10x.Stress.dta.pca <- sc10x.Stress.dta.pca$x[,1:2]
+    colnames(x=sc10x.Stress.dta.pca) <- paste0("Stress",1:2)
+    if (skewness(sc10x.Stress.dta.pca[,1])<0){
+      sc10x.Stress.dta.pca[,1] <- (-sc10x.Stress.dta.pca[,1])
+    }
+    if (skewness(sc10x.Stress.dta.pca[,2])<0){
+      sc10x.Stress.dta.pca[,2] <- (-sc10x.Stress.dta.pca[,2])
+    }
+    sc10x.dta <- sc10x.Stress
+    sc10x.dta <- SetDimReduction(object=sc10x.dta,reduction.type="Stress",slot="cell.embeddings",new.data=sc10x.Stress.dta.pca)
+    sc10x.dta <- SetDimReduction(object=sc10x.dta,reduction.type="Stress",slot="key",new.data="Stress")
+    
+    #CDS
+    cdf <- ecdf(GetCellEmbeddings(object=sc10x.dta,reduction.type="Stress",dims.use=1))
+    cut.x <- quantile(cdf,probs=cut)
+    
+    assign(i,GetCellEmbeddings(object=sc10x.dta,reduction.type="Stress",dims.use=1))
+    assign(paste0("cut.",i,".",cut),cut.x)
+}}
+rm(cut)
+rm(i)
+rm(genes.stress)
+rm(sc10x.Stress.dta)
+rm(sc10x.Stress.dta.pca)
+rm(sc10x.dta)
+rm(cdf)
+rm(cut.x)  
+
+comp <- cbind(vdb,go[match(rownames(vdb),rownames(go))],dws[match(rownames(vdb),rownames(dws))])
+colnames(comp) <- c("vdb","go","dws")
+comp <- data.frame(comp)
+
+Cairo(paste0("../analysis/stress/Stress.vdb.vs.go.png"),width=1000,height=500,bg="white")
+ggplot(comp,aes(x=vdb,y=go))+geom_point(size=0.01)+geom_vline(xintercept=cut.vdb.0.95)+geom_hline(yintercept=cut.go.0.95)+annotate("text",x=max(comp$vdb)/4*3,y=max(comp$go)/4*3,col="red",size=10,fontface=2,label=paste0(round(nrow(comp[comp$vdb>cut.vdb.0.95,][comp[comp$vdb>cut.vdb.0.95,"go"]>cut.go.0.95,])/nrow(comp[comp$vdb>cut.vdb.0.95,])*100,1),"%"))+annotate("text",x=max(comp$vdb)/100,y=max(comp$go)/100,col="green",size=10,fontface=2,label=paste0(round(nrow(comp[comp$vdb<=cut.vdb.0.95,][comp[comp$vdb<=cut.vdb.0.95,"go"]<=cut.go.0.95,])/nrow(comp[comp$vdb<=cut.vdb.0.95,])*100,1),"%"))
+dev.off()
+Cairo(paste0("../analysis/stress/Stress.vdb.vs.dws.png"),width=1000,height=500,bg="white")
+ggplot(comp,aes(x=vdb,y=dws))+geom_point(size=0.01)+geom_vline(xintercept=cut.vdb.0.95)+geom_hline(yintercept=cut.dws.0.95)+annotate("text",x=max(comp$vdb)/4*3,y=max(comp$dws)/4*3,col="red",size=10,fontface=2,label=paste0(round(nrow(comp[comp$vdb>cut.vdb.0.95,][comp[comp$vdb>cut.vdb.0.95,"dws"]>cut.dws.0.95,])/nrow(comp[comp$vdb>cut.vdb.0.95,])*100,1),"%"))+annotate("text",x=max(comp$vdb)/100,y=max(comp$dws)/100,col="green",size=10,fontface=2,label=paste0(round(nrow(comp[comp$vdb<=cut.vdb.0.95,][comp[comp$vdb<=cut.vdb.0.95,"dws"]<=cut.dws.0.95,])/nrow(comp[comp$vdb<=cut.vdb.0.95,])*100,1),"%"))
+dev.off()
+Cairo(paste0("../analysis/stress/Stress.go.vs.dws.png"),width=1000,height=500,bg="white")
+ggplot(comp,aes(x=go,y=dws))+geom_point(size=0.01)+geom_vline(xintercept=cut.go.0.95)+geom_hline(yintercept=cut.dws.0.95)+annotate("text",x=max(comp$go)/4*3,y=max(comp$dws)/4*3,col="red",size=10,fontface=2,label=paste0(round(nrow(comp[comp$go>cut.go.0.95,][comp[comp$go>cut.go.0.95,"dws"]>cut.dws.0.95,])/nrow(comp[comp$go>cut.go.0.95,])*100,1),"%"))+annotate("text",x=max(comp$go)/100,y=max(comp$dws)/100,col="green",size=10,fontface=2,label=paste0(round(nrow(comp[comp$go<=cut.go.0.95,][comp[comp$go<=cut.go.0.95,"dws"]<=cut.dws.0.95,])/nrow(comp[comp$go<=cut.go.0.95,])*100,1),"%"))
+dev.off()
+
+rm(comp)
diff --git a/stress/.gitkeep b/stress/.gitkeep
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391