The number of orthogonal components was then based on meaningful orthogonal variation pertaining to e.g. cores in OPLS-DA models for plaques vs non-plaque. Finally, the correlation scaled loadings, p(corr), were examined in order to identify differences in the lipidomic profiles between areas of interest. Post hoc power analyses were performed in Matlab using the sampsizepwr function (Statistics and Machine Learning Toolbox).