PCA; overviewing how the expression profiles vary among sample groups.
Principal component analysis (PCA) visualizes similarity of expression profiles by distances and directions. Closely located plots (samples) share similar expression profiles. If the plots are split over 0 toward positive and negative side, it means they have opposite expression profiles.
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