Integrating omics data for identifying disease subtypes: A multiplex network-based approach

It is widely acknowledged that technologies centred on the integration of omics data could play an important role in capturing heterogeneity of phenotypes and identifying disease subtypes. This paper proposed a multiplex network-based approach for integrative analysis of heterogeneous omics data. It represents a useful alternative network-based solution to the problem and a significant step forward to the methods in which each type of data is treated independently. It has been tested on the identification of the subtypes of glioblastoma multiforme. Results obtained have shown that it can achieve comparable performance in comparison to state-of-the-art techniques. The proposed methodology has several advantages. It provides a flexible platform to integrate different types of patient data, potentially from multiple sources, allowing discovering complex disease patterns with multiple facets.