A novel support vector regression approach for detecting gene-environment interactions and predicting trait values.
A novel statistical framework, iSVR, is presented that incorporates gene-environment interaction terms into a support vector regression model, enabling both modeling of interaction effects and their statistical testing, and provides a powerful approach to characterize the gene-environment interaction landscapes underlying complex traits.