It extracts the fundamental structure of the data without the need to build any model to represent it. It was initially developed to analyse large volumes of data in order to tease out the differences/relationships between the logical entities being analysed. Principal Component Analysis (PCA) is a very powerful technique that has wide applicability in data science, bioinformatics, and further afield.
5.2.4 Change shape based on tumour grade, remove connectors, and add titles.5.2.2 Supply custom colours and encircle variables by group.
