diff --git a/r.scripts/sc_PC.Score.NE.R b/r.scripts/sc_PC.Score.NE.R
index 42e31962fcc35b57dfae38797de0c0addb2e3139..b9b5ef1d60d4d6f0f401681e1ddd47822eac4cd5 100755
--- a/r.scripts/sc_PC.Score.NE.R
+++ b/r.scripts/sc_PC.Score.NE.R
@@ -105,7 +105,11 @@ plot(plot)
 dev.off()
 
 #subsample all cells (+NE) to better visualize their clustering
-rnd <- sample(1:ncol(sc10x.Group@data),opt$sv)
+if (!is.na(opt$s)){
+  rnd <- sample(1:ncol(sc10x.Group@data),opt$sv)
+} else {
+  rnd <- 1:ncol(sc10x.Group@data)
+}
 sc10x.Group <- SetIdent(object=sc10x.Group,cells.use=sc10x.Group@data@Dimnames[[2]][rnd],ident.use="sample")
 if (clust$size[1]<clust$size[2]){
   clusterCut <- names(clusterCut[clusterCut==1])