25 Meta-dimensional omics integration
In meta-dimensional analysis all omic datasets are analysed in a single, simultaneous analysis. This kind of approach typically avoids using domain knowledge-based procedures to independently reduce features in single omic datasets, and aims at integrating multi-omic datasets in their whole complexity. Meta-dimensional integration methods can be grouped following several criteria but here we briefly summarise the classification first coined by Ritchie et al. (2015) [57] and recently reviewed by Reel et al. (2021) [58] (we refer interested readers to those publications for a more in depth treatment of the topic), which classifies the methods into concatenation-based, model-based and transformation-based integration methods. The three kinds of integration methods can be used for unsupervised and supervised analysis of multi-omic data, including classification and regression tasks.