Figure 3

Principal component analysis used to generate FLEYE built-in statistical model. (A) The first component of a PCA analysis performed with 9 variables discriminates between WT and SCA1 degenerated eyes and shows a polymodal distribution of intermediates. (B) The first PCA factor splits the sample into five different categories, 0 to 4, ranging from a healthy eye (class 0) to a totally degenerated eye (class 4). The classification remains the same even after removing 4 redundant variables among the 9 used (not shown). (C) The first PCA component explains 60% of the total variance and constitutes a clearly discriminating tool (D), whilst the second component explains 20% of the variance, but does not differentiate between healthy and degenerated samples.