Fig. 3

Principal Component Analyses (PCA). The first two principal components from a Principal Component Analysis using rlog transformed expression values. a. Principal Component Analysis (PCA) of samples from all four groups described in Table 1. The first principal component (PC1, x-axis) explains 47% of the variation in the data while the second principal component (PC2, y-axis) increases total explained variation to 56%. Confidence ellipsis at 99% is drawn for each group. b. Principal component analysis (PCA) of G23 vs. G16. The first principal component (PC1, x-axis) explains 16% of the variation in the data while the second principal component (PC2, y-axis) increases total explained variation to 30%. Confidence ellipsis at 99% is drawn for each group