séminaire BioInformatique "AMARETTO: Multi-omics data fusion for cancer data"

Integrating the increasing number of available multi-omics cancer data remains one of the main challenges to improve our understanding of cancer. Our approach is based on AMARETTO, an algorithm that integrates DNA methylation, DNA copy number and gene expression data to identify cancer driver genes and associates them to modules of co-expressed genes. We then propose a pancancer version of AMARETTO by connecting all modules in pancancer communities. This leads to the identification of major oncogenic pathways and master regulators involved in different cancers.