Remove more as.matrix to prevent memory errors

r.scripts/sc-TissueMapper_functions.R

@@ -142,8 +142,8 @@ scQC <- function(sc10x,lg=500,hg=2500,hm=0.1,sub=FALSE){
   plot2 <- ggplot(data.frame(cbind(sc10x$nCount_RNA,sc10x$percent.mito)))+geom_point(aes(x=X1,y=X2,color=density2),size=0.1)+scale_color_viridis(option="inferno")+geom_hline(yintercept=hm,size=1,color="red")+labs(x="nUMI",y="Percent Mitochondrial",color="Count")+cowplot::theme_cowplot()
   grid.arrange(plot1,plot2,nrow=1)
   dev.off()
-  counts.cell.raw <- ncol(as.matrix(GetAssayData(object=sc10x,slot="counts")))
-  counts.gene.raw <- nrow(as.matrix(GetAssayData(object=sc10x,slot="counts")))
+  counts.cell.raw <- ncol(GetAssayData(object=sc10x,slot="counts"))
+  counts.gene.raw <- nrow(GetAssayData(object=sc10x,slot="counts"))
   
   #Filter/normalize data
   sc10x.sub <- subset(x=sc10x,subset=nFeature_RNA > lg)
@@ -168,8 +168,8 @@ scQC <- function(sc10x,lg=500,hg=2500,hm=0.1,sub=FALSE){
   plot2 <- ggplot(data.frame(cbind(sc10x.sub$nCount_RNA,sc10x.sub$percent.mito)))+geom_point(aes(x=X1,y=X2,color=density2),size=0.1)+scale_color_viridis(option="inferno")+labs(x="nUMI",y="Percent Mitochondrial",color="Count")+cowplot::theme_cowplot()
   grid.arrange(plot1,plot2,nrow=1)
   dev.off()
-  counts.cell.filtered <- ncol(as.matrix(GetAssayData(object=sc10x.sub,slot="counts")))
-  counts.gene.filtered <- nrow(as.matrix(GetAssayData(object=sc10x.sub,slot="counts")))
+  counts.cell.filtered <- ncol(GetAssayData(object=sc10x.sub,slot="counts"))
+  counts.gene.filtered <- nrow(rix(GetAssayData(object=sc10x.sub,slot="counts"))
   
   results <- list(
     sc10x=sc10x.sub,