Fast multivariate genotype by environment interactions identification algorithm with a linear mixed model/ logistic model framework
Principal Investigator: Dr Wenlong Ren
Approved Research ID: 57968
Approval date: February 26th 2020
People have huge difference in lifestyle, physical activity and other exposures. Genetic and environmental factors could jointly influence the risk of a disease, such as, psychiatric disorder, cancer, diabetes, and etc. Many gene-environment interaction (G × E) models have been established to improve accuracy and precision in the assessment of both genetic and environmental influences. However, there are few models that consider multiple G × Es together with very large samples and relatedness corrections among individuals. Our aims are to propose a fast multiple G × Es detection algorithm to solve the above problem. One disease is often affected by multiple environments, previous researches have showed that multiple G × Es model could better interpret the molecular mechanism of pathogenesis compared with single G × E model. Our project is planned to be completed within two years. And an R package will be developed for publicly available. Our research is expected to discovery more gene-environment interactions in human diseases. And it will provide references for further experimental verification and disease treatment.