Epistasis Blog

From the Artificial Intelligence Innovation Lab at Cedars-Sinai Medical Center (www.epistasis.org)

Friday, November 02, 2007

Bases, Bits and Disease

My short editorial on the use of information theory for the genetic analysis of epistasis has been published in the European Journal of Human Genetics.

Moore JH. Bases, bits and disease: A mathematical theory of human genetics. European Journal of Human Genetics, in press (2007) [PubMed] [PDF]

This editorial comments on a new paper by Dong et al. to appear in the European Journal of Human Genetics.

Dong C, Chu X, Wang Y, Wang Y, Jin L, Shi T, Huang W, Li Y. Exploration of gene-gene interaction effects using entropy-based methods. European Journal of Human Genetics, in press (2007) [PubMed] [PDF]

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


Post a Comment

<< Home