The PCAGCA toolbox contains MATLAB code to separate common and distinct variation in multiple data blocks using the method PCA-GCA. PCA-GCA is a combination of Principal Component Analysis (PCA) and Generalized Canonical Correlation Analysis (GCA), and the method is described in:
Smilde AK, Måge I, Næs T, et al. Common and Distinct Components in Data Fusion. J Chemom. 2017;31(7). doi:10.1002/cem.2900.