Chapter 4: Genetic-Epigenetic Interplay Discovery

A biological system is very complex, in which different components interplay all the time. The interactions include gene-gene interaction, gene-metabolite interaction, pathway interaction and genetic-epigenetic interaction. It has been found in several studies that the genetic-epigenetic interplay may contribute to the development of several diseases. How the genetic-epigenetic interplay contributes to the disease development thus requires descent research about how genetic signatures and epigenetic signatures interplay. To determine how thousands of epigenetic signatures are associated with a genetic signature and to determine how thousands of genetic signatures are associated with an epigenetic signature is a regression problem. Importantly, the genetic-epigenetic interplay may happen between local or remote contributing components. Therefore, it is desirable to discover and focus on the most important signatures among thousands of signatures instead of scanning every contributing signature. In this way, whether the interplay happens locally or remotely can be discovered. Therefore, a regression analysis algorithm with well-equipped variable ranking mechanism is desirable. Only in such models, the quantitative evidence of local interplay or remote interplay between genetic signatures and epigenetic signatures can be well-researched. This chapter will introduce several regression algorithms which can rank variables for genetic-epigenetic interplay pattern discovery.