diff --git a/bash.scripts/sc_FullAnalysis-D17PrF.sh b/bash.scripts/sc_FullAnalysis-D17PrF.sh
index af7d83b9c17b95c2f47636ac3f42f6d81d86adfa..8200e96d107dcbb9605251311ed6dc4bbb8056d7 100755
--- a/bash.scripts/sc_FullAnalysis-D17PrF.sh
+++ b/bash.scripts/sc_FullAnalysis-D17PrF.sh
@@ -14,7 +14,7 @@ Rscript ../r.scripts/sc_Demultiplex.R --p="D17PrF" --d=3
Rscript ../r.scripts/sc_Seurat.Score.CellCycle.R --p="D17PrF"
Rscript ../r.scripts/sc_QC.R --p="D17PrF"
Rscript ../r.scripts/sc_Cluster.R --p="D17PrF" --pc=0
-Rscript ../r.scripts/sc_PC.Score.Stress.R --p="D17PrF" --pc=0
+Rscript ../r.scripts/sc_PC.Score.Stress.R --p="D17PrF" --r=0.5 --pc=0
Rscript ../r.scripts/sc_QuSAGE.Lineage.R --p="D17PrF" --r=0.1 --s=NA
Rscript ../r.scripts/sc_LineageSubClust.R --p="D17PrF" --pc=0
Rscript ../r.scripts/sc_QuSAGE_EpiSubClust.R --p="D17PrF" --r=0.1 --s=NA
diff --git a/r.scripts/sc_LineageSubClust.R b/r.scripts/sc_LineageSubClust.R
index 8707fc2cb70b8d4521165534377fc047702c4c0c..9b6b4bf8f19396ed415f5ed9699bd35c9d759f5a 100755
--- a/r.scripts/sc_LineageSubClust.R
+++ b/r.scripts/sc_LineageSubClust.R
@@ -53,8 +53,8 @@ tryCatch({
rm(sc10x.Group)
#re-detect variable genes in Epi + St subsets
-sc10x.Group.Epi <- FindVariableGenes(object=sc10x.Group.Epi,mean.function=ExpMean,dispersion.function=LogVMR,x.low.cutoff=0.075,x.high.cutoff=3.5,y.cutoff=0.5,do.plot=FALSE)
-sc10x.Group.St <- FindVariableGenes(object=sc10x.Group.St,mean.function=ExpMean,dispersion.function=LogVMR,x.low.cutoff=0.075,x.high.cutoff=3.5,y.cutoff=0.5,do.plot=FALSE)
+sc10x.Group.Epi <- FindVariableGenes(object=sc10x.Group.Epi,mean.function=ExpMean,dispersion.function=LogVMR,x.low.cutoff=0.15,x.high.cutoff=3.5,y.cutoff=0.75,do.plot=FALSE)
+sc10x.Group.St <- FindVariableGenes(object=sc10x.Group.St,mean.function=ExpMean,dispersion.function=LogVMR,x.low.cutoff=0.15,x.high.cutoff=3.5,y.cutoff=0.75,do.plot=FALSE)
genes.var.NoStress.Epi <- sc10x.Group.Epi@var.genes
genes.var.NoStress.St <- sc10x.Group.St@var.genes
diff --git a/r.scripts/sc_PC.Score.NE.R b/r.scripts/sc_PC.Score.NE.R
index 9acccfa62f63f32c0e4a303616c1c685fe5a37de..bf657dcd3f1fd7534f2892ca4104f1b7adbd61ae 100755
--- a/r.scripts/sc_PC.Score.NE.R
+++ b/r.scripts/sc_PC.Score.NE.R
@@ -89,16 +89,16 @@ dev.off()
#find first turning point on a KDE of NE1
#hist(GetCellEmbeddings(object=sc10x.Group.Epi,reduction.type="NE",dims.use=1),prob=TRUE)
-d1 <- density(GetCellEmbeddings(object=sc10x.Group.Epi,reduction.type="NE",dims.use=1),n=1000)
+d1 <- density(GetCellEmbeddings(object=sc10x.Group.Epi,reduction.type="NE",dims.use=1),n=50)
#d2 <- density(GetCellEmbeddings(object=sc10x.Group.Epi,reduction.type="NE",dims.use=2))
-#lines(d1)
+#lines(d1,col="blue")
ts_1 <- ts(d1$y)
#ts_2 <- ts(d2$y)
tp1 <- turnpoints(ts_1)
#tp2 <- turnpoints(ts_2)
pit1 <- min(d1$x[tp1$pits][d1$x[tp1$pits]>d1$x[tp1$peaks][d1$y[tp1$peaks]==max(d1$y[tp1$peaks])]])
#pit2 <- d2$x[tp2$pits][length(d2$x[tp2$pits])]
-#abline(v=pit1)
+#abline(v=pit1,col="red")
ALL <- GetCellEmbeddings(object=sc10x.Group.Epi,reduction.type="NE",dims.use=1:2)
NE <- rownames(ALL[ALL[,1]>pit1,])
diff --git a/r.scripts/sc_PC.Score.Stress.R b/r.scripts/sc_PC.Score.Stress.R
index 9ebbd2803331f5807073ae5996ba6fbebf494da4..c9dd17a1a5455774c7887cda881edd727adc3297 100755
--- a/r.scripts/sc_PC.Score.Stress.R
+++ b/r.scripts/sc_PC.Score.Stress.R
@@ -76,7 +76,7 @@ dev.off()
#find first turning point on a KDE of Stress1
histo <- hist(GetCellEmbeddings(object=sc10x.Group,reduction.type="Stress",dims.use=1),breaks=10,prob=TRUE,plot=TRUE)
-d1 <- density(GetCellEmbeddings(object=sc10x.Group,reduction.type="Stress",dims.use=1),n=1000)
+d1 <- density(GetCellEmbeddings(object=sc10x.Group,reduction.type="Stress",dims.use=1),n=50)
#d2 <- density(GetCellEmbeddings(object=sc10x.Group,reduction.type="Stress",dims.use=2),n=1000)
ts_1 <- ts(d1$y)
#ts_2 <- ts(d2$y)
@@ -99,8 +99,6 @@ plot <- plot+geom_vline(xintercept=pit1,color="red",lwd=2.5)
plot(plot)
dev.off()
-
-
#subsample all cells (+Stress) to better visualize their clustering
if (!is.na(opt$s)){
rnd <- sample(1:ncol(sc10x.Group@data),opt$sv)
@@ -163,16 +161,16 @@ sc10x.Group.subset.FilteredCellCount <- length(sc10x.Group.subset@data@Dimnames[
rm(merge.cluster)
#regenerate tSNEs for range of resolutions
-sc10x.Group.subset <- FindVariableGenes(object=sc10x.Group.subset,mean.function=ExpMean,dispersion.function=LogVMR,x.low.cutoff=0.075,x.high.cutoff=4,y.cutoff=0.075,do.plot=FALSE)
+sc10x.Group.subset <- FindVariableGenes(object=sc10x.Group.subset,mean.function=ExpMean,dispersion.function=LogVMR,x.low.cutoff=0.15,x.high.cutoff=3.5,y.cutoff=0.75,do.plot=FALSE)
sc10x.Group.subset <- RunPCA(object=sc10x.Group.subset,pc.genes=sc10x.Group.subset@var.genes,do.print=FALSE,pcs.compute=50)
PC.var.NoStress <- (sc10x.Group.subset@dr$pca@sdev)^2
PC.var.NoStress <- PC.var.NoStress/sum(PC.var.NoStress)
PC.var.NoStress <- cumsum(PC.var.NoStress)
-PC.var.NoStress.75 <- min(which(PC.var.NoStress>=0.75))
+PC.var.NoStress.95 <- min(which(PC.var.NoStress>=0.95))
if (opt$pc>0){
PC.Max <- opt$pc
} else {
- PC.Max <- PC.var.NoStress.75
+ PC.Max <- PC.var.NoStress.95
}
sc10x.Group.subset <- RunTSNE(object=sc10x.Group.subset,dims.use=1:PC.Max,do.fast=TRUE,force.recalc=TRUE)
postscript(paste0("./analysis/",opt$g,"/global/NoStress/tSNE_Sample.eps"))
diff --git a/r.scripts/sc_QC.R b/r.scripts/sc_QC.R
index d00d7d921e465ed65c0cc0a0b2855b31bcb5e510..3ebd1d43f095a59efaa921129b66ed877da0d2ea 100755
--- a/r.scripts/sc_QC.R
+++ b/r.scripts/sc_QC.R
@@ -73,7 +73,7 @@ dev.off()
sc10x.Group.FilteredCellCount <- length(sc10x.Group@data@Dimnames[[2]])
sc10x.Group.FilteredGeneCount <- length(sc10x.Group@data@Dimnames[[1]])
sc10x.Group@data <- sc10x.Group@data[!rownames(sc10x.Group@data) %in% mito.genes,]
-sc10x.Group <- FindVariableGenes(object=sc10x.Group,mean.function=ExpMean,dispersion.function=LogVMR,x.low.cutoff=0.075,x.high.cutoff=3.5,y.cutoff=0.5,do.plot=FALSE)
+sc10x.Group <- FindVariableGenes(object=sc10x.Group,mean.function=ExpMean,dispersion.function=LogVMR,x.low.cutoff=0.15,x.high.cutoff=3.5,y.cutoff=0.75,do.plot=FALSE)
genes.var <- sc10x.Group@var.genes
if (opt$cc==TRUE){
gc()