Exploration of gene-gene interaction effects using entropy-based methods. Commentary

摘要: Gene-gene interaction may play important roles in complex disease studies, which effects coupled with single-gene are active. Many models have been proposed since the beginning of last century. However, existing approaches including statistical and data mining methods rarely consider genetic models, make results lack biological or meaning. In this study, we developed an entropy-based method integrating two-locus to explore such effects. We performed our simulated real for evaluation. Simulation show that is effective detect gene-gene and, furthermore, it able identify best-fit model from various models. Moreover, method, when applied malaria data, successfully revealed negative epistatic effect between sickle cell anemia α + -thalassemia against malaria.