Genetic interactions or epistasis have been thought to play a pivotal role in shaping the formation, development and evolution of life. Previous work focused on lower-order interactions between a pair of genes, but it is obviously inadequate to explain a complex network of genetic interactions and pathways. We review and assess a statistical model for characterizing high-order epistasis among more than two genes or quantitative trait loci (QTLs) that control a complex trait. The model includes a series of start-of-the-art standard procedures for estimating and testing the nature and magnitude of QTL interactions. Results from simulation studies and real data analysis warrant the Xiaoming Pang obtained his PhD in Pomology at Huazhong Agricultural University in 2002. After post-doctoral training and research in China and Japan, he joined Beijing Forestry University as Associate Professor of Tree Breeding in 2006. His research interest focuses on the utilization of molecular genetics and biotechnologies to study population genetic diversity and map quantitative trait loci in fruit trees. Zhong Wang obtained his PhD in Engineering Mechanics at Dalian University of Technology in 2000. He found and managed a software company in Japan from 2000 to 2008. He is Visiting Scholar in the Center for Computational Biology at Beijing Forestry University. He writes computer software for statistical genetic models. John S. Yap obtained his PhD in Statistics at the University of Florida in 2007. He monitors the accuracy and reasonableness of statistical approaches that are used in drug discovery, development and delivery. He also develops new statistical models for genetic mapping.
['Xiaoming Pang', 'Zhong Wang', 'John Stephen Yap', 'Jianxin Wang', 'Junjia Zhu', 'Wenhao Bo', 'Yafei Lv', 'Fang Xu', 'Tao Zhou', 'Shaofeng Peng', 'Dengfeng Shen', 'Rongling Wu']
A statistical procedure to map high-order epistasis for complex traits