In this review we provide an overview of recent data analysis approaches to integrate various omics layers to understand epigenetic mechanisms of complex diseases, such as obesity and cancer. Furthermore, due to the dynamic nature of the epigenome, it is critical to determine causal relationships from the many correlated associations. The epigenomic profile for a certain disease is often a result of the complex interplay between multiple genetic and environmental factors, which poses an enormous challenge to visualize and interpret these data. Recent technical advances such as whole-genome bisulfite sequencing and affordable epigenomic array-based technologies, allow researchers to measure epigenetic profiles of large cohorts at a genome-wide level, generating comprehensive high-dimensional datasets that may contain important information for disease development and treatment opportunities. 4Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, FinlandĮpigenetic research involves examining the mitotically heritable processes that regulate gene expression, independent of changes in the DNA sequence.3Department of Mathematics and Statistics, University of Turku, Turku, Finland.2Department of Public Health, University of Helsinki, Helsinki, Finland.1Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland.Emma Cazaly 1, Joseph Saad 1, Wenyu Wang 1, Caroline Heckman 1, Miina Ollikainen 1,2* and Jing Tang 1,3,4*