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, "%)")