diff --git a/r.scripts/sc_QC.R b/r.scripts/sc_QC.R
index e458b1a7e99b5c93af4e999029c03935a8063e97..103016653d5ba194b2b9593ab2338547e9bfbeac 100755
--- a/r.scripts/sc_QC.R
+++ b/r.scripts/sc_QC.R
@@ -75,7 +75,7 @@ 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=0.0125,x.high.cutoff=3,y.cutoff=0.5,do.plot=FALSE)
 if (opt$cc==TRUE){
   gc()
-  sc10x.Group <- ScaleData(object=sc10x.Group,vars.to.regress=c("nUMI","percent.mito","S.Score","G2M.Score"),display.progress=FALSE,do.par=TRUE,num.cores=40)
+  sc10x.Group <- ScaleData(object=sc10x.Group,vars.to.regress=c("nUMI","percent.mito","S.Score","G2M.Score"),display.progress=FALSE,do.par=TRUE,num.cores=50)
   gc()
   sc10x.Group <- RunPCA(object=sc10x.Group,pc.genes=c(s.genes,g2m.genes),do.print=FALSE,pcs.store=2)
   sc10x.Group <- SetAllIdent(object=sc10x.Group,id="Phase")
@@ -87,7 +87,7 @@ if (opt$cc==TRUE){
   dev.off()
 } else {
   gc()
-  sc10x.Group <- ScaleData(object=sc10x.Group,vars.to.regress=c("nUMI","percent.mito"),display.progress=FALSE,do.par=TRUE,num.cores=40)
+  sc10x.Group <- ScaleData(object=sc10x.Group,vars.to.regress=c("nUMI","percent.mito"),display.progress=FALSE,do.par=TRUE,num.cores=50)
   gc()
 }
 sc10x.Group <- SetAllIdent(object=sc10x.Group,id="ALL")
diff --git a/r.scripts/sc_Seurat.Score.CellCycle.R b/r.scripts/sc_Seurat.Score.CellCycle.R
index a60fc2700a5032dc96a88199ee9d923a1c5f4070..4cf22d50d7d43eaac96d62e3700d0ad2cea537e0 100755
--- a/r.scripts/sc_Seurat.Score.CellCycle.R
+++ b/r.scripts/sc_Seurat.Score.CellCycle.R
@@ -33,7 +33,7 @@ cc.genes <- readLines(con="./genesets/regev_lab_cell_cycle_genes.txt")
 s.genes <- cc.genes[1:43]
 g2m.genes <- cc.genes[44:97]
 sc10x.Group <- NormalizeData(object=sc10x.Group)
-sc10x.Group <- ScaleData(object=sc10x.Group,display.progress=FALSE,do.par=TRUE,num.cores=40)
+sc10x.Group <- ScaleData(object=sc10x.Group,display.progress=FALSE,do.par=TRUE,num.cores=50)
 sc10x.Group <- CellCycleScoring(object=sc10x.Group,s.genes=s.genes,g2m.genes=g2m.genes,set.ident=TRUE)
 postscript(paste0("./analysis/",opt$g,"/cc/Ridge_cc.Raw.eps"))
 plot <- RidgePlot(object=sc10x.Group,features.plot=c("PCNA","TOP2A","MCM6","MKI67"),y.log=TRUE,nCol=2,do.return=TRUE)