Machine learning approaches to explore digenic inheritance

Abstract

Some rare genetic disorders, such as retinitis pigmentosa or Alport syndrome, are caused by the co-inheritance of DNA variants at two different genetic loci (digenic inheritance). To capture the effects of these disease-causing variants and their possible interactive effects, various statistical methods have been developed in human genetics. Analogous developments have taken place in the field of machine learning, particularly for the field that is now called Big Data. In the past, these two areas have grown independently and have started to converge only in recent years. We discuss an overview of each of the two fields, paying special attention to machine learning methods for uncovering the combined effects of pairs of variants on human disease.

Keywords: digenic inheritance; epistasis; machine learning; modifier variants; statistical genetics.