Decrease stringency for pan Epi/St generation in Pd and increase min pop downsample for FACS

r.scripts/sc-TissueMapper_RUN.D17_FACS.R

@@ -180,7 +180,7 @@ gene.set <- c(gene.set,gene.set1)
 rm(gene.set1)
 gc()
 min.all <- min(table(sc10x@meta.data[,paste0("res",opt$res.poststress)]))
-results <- scQuSAGE(sc10x,gs=gene.set,res.use=opt$res.poststress,ds=0,nm="Lin",folder="lin")
+results <- scQuSAGE(sc10x,gs=gene.set,res.use=opt$res.poststress,ds=min.all,nm="Lin",folder="lin")
 sc10x <- results[[1]]
 results.cor.Lin <- results[[2]]
 results.clust.Lin.id <- results[[3]]
@@ -254,7 +254,7 @@ gene.set <- c(gene.set,gene.set1)
 rm(gene.set1)
 gc()
 min.epi <- min(table(sc10x.Epi@meta.data[,paste0("res",opt$res.poststress)]))
-results <- scQuSAGE(sc10x.Epi,gs=gene.set,res.use=opt$res.poststress,ds=0,nm="Epi.dws.sc",folder="epi")
+results <- scQuSAGE(sc10x.Epi,gs=gene.set,res.use=opt$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]]
@@ -284,7 +284,7 @@ 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=0,nm="St.dws.sc",folder="st")
+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]]

r.scripts/sc-TissueMapper_RUN.D27_FACS.R

@@ -180,7 +180,7 @@ gene.set <- c(gene.set,gene.set1)
 rm(gene.set1)
 gc()
 min.all <- min(table(sc10x@meta.data[,paste0("res",opt$res.poststress)]))
-results <- scQuSAGE(sc10x,gs=gene.set,res.use=opt$res.poststress,ds=0,nm="Lin",folder="lin")
+results <- scQuSAGE(sc10x,gs=gene.set,res.use=opt$res.poststress,ds=min.all,nm="Lin",folder="lin")
 sc10x <- results[[1]]
 results.cor.Lin <- results[[2]]
 results.clust.Lin.id <- results[[3]]
@@ -254,7 +254,7 @@ gene.set <- c(gene.set,gene.set1)
 rm(gene.set1)
 gc()
 min.epi <- min(table(sc10x.Epi@meta.data[,paste0("res",opt$res.poststress)]))
-results <- scQuSAGE(sc10x.Epi,gs=gene.set,res.use=opt$res.poststress,ds=0,nm="Epi.dws.sc",folder="epi")
+results <- scQuSAGE(sc10x.Epi,gs=gene.set,res.use=opt$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]]
@@ -284,7 +284,7 @@ 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=0,nm="St.dws.sc",folder="st")
+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]]

r.scripts/sc-TissueMapper_RUN.Pd.R

@@ -409,8 +409,8 @@ scTables(sc10x,i.1="Merge_Epi.dws_St.go_NE",i.2="Merge_Epi.dws_St.go")
 
 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.Epi <- scDEG(sc10x,i="Lin",g.1="Epi",g.2="St",t=0)
+genes.deg.St <- scDEG(sc10x,i="Lin",g.1="St",g.2="Epi",t=0)
 
 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","OE1","OE2"),pct=0.25,t=2)