Principal components analysis (PCA) is commonly used for clustering gene expression data. It allows us to cluster genes based on the different conditions, such as treatment and control, drug responses, time points etc. With new Array Suite 9.0 release, we improve our PCA visualization by adding PCA ellipse to display PCA confidence level.
As an example, let's look at the gene expression data from two different case and control groups. A 2D PCA on the dataset:
The confidence level indicated by the ellipse helps user to better "visualize" the confidence of the clustering.