diff --git a/_reader/RNAseqWorkshop.pdf b/_reader/RNAseqWorkshop.pdf
index 880d75f5b3142d42f261f281882ed0a52cba3ba8..80271f0ab4d2431219219bcf46f1e362d09a7669 100644
Binary files a/_reader/RNAseqWorkshop.pdf and b/_reader/RNAseqWorkshop.pdf differ
diff --git a/workflows/clustering_PCA_HCL.R b/workflows/clustering_PCA_HCL.R
index bda8dec4ac6e659f59981febefaae19967700f85..a4cdaa88104d41b7d448015a962c72ebbf23b151 100644
--- a/workflows/clustering_PCA_HCL.R
+++ b/workflows/clustering_PCA_HCL.R
@@ -1,6 +1,6 @@
 ## PCA
 # we need a few plotting-related libraries we have not used before
-library(ggrepel)
+library(ggplot2)
 
 load(file = "runs/kallisto_combined/mothertableV2.Rdata")
 
@@ -43,7 +43,7 @@ scores
 pca12 <- ggplot(data = scores, aes(x = PC1, y = PC2)) +
   theme_bw() +
   geom_point(aes(color = treatment), size = 2.5) +
-  geom_text_repel(aes(label = treatment), size = 3) +
+  geom_text(aes(label = treatment), vjust = 1.5, size = 3) +
   labs(
     x = paste0("PCA1 (", s$importance[2, 1] * 100, "%)"),
     y = paste0("PCA2 (", s$importance[2, 2] * 100, "%)")