A Simple Continuum Approach for Canonical Correlation Analysis; Applications to “Omics” Data

A continuum approach for canonical correlation analysis based on a single tuning parameter is proposed. One of its noteworthy features is that it is straightforward and simple. It establishes a bridge between unfold Principal Components Analysis and Canonical Correlation Analysis. Interesting properties related to the method of analysis are also discussed. This makes it possible to highlight the rationale behind the continuum approach by showing that it aims at realizing a compromise between achieving the investigation of the relationships between two datasets and setting up a stable model. The strategy of analysis is exemplified on the basis of a case study aiming at linking metabolomics and proteomics data, on the one hand, and discriminating groups of individuals using metabolomics data, on the other hand.