The article by Heather J. Cordell, titled "Detecting gene-gene interactions that underlie human diseases," provides a comprehensive survey of current methodological approaches and software packages used to detect interactions between genetic loci contributing to human genetic diseases. The author highlights the importance of identifying interactions, which can increase the power to detect associations and provide insights into biological and biochemical pathways underlying diseases. The review covers various methods, including regression models, data mining/machine learning approaches, and Bayesian model selection techniques. It discusses the challenges of multiple testing and computational efficiency, particularly in large-scale genotyping projects. The article also explores the biological interpretation of statistical interactions and the limitations of current methods in detecting functional interactions. Finally, it concludes by emphasizing the need for efficient computational algorithms and the potential of filtering approaches to pre-select a subset of loci for more intensive analysis.The article by Heather J. Cordell, titled "Detecting gene-gene interactions that underlie human diseases," provides a comprehensive survey of current methodological approaches and software packages used to detect interactions between genetic loci contributing to human genetic diseases. The author highlights the importance of identifying interactions, which can increase the power to detect associations and provide insights into biological and biochemical pathways underlying diseases. The review covers various methods, including regression models, data mining/machine learning approaches, and Bayesian model selection techniques. It discusses the challenges of multiple testing and computational efficiency, particularly in large-scale genotyping projects. The article also explores the biological interpretation of statistical interactions and the limitations of current methods in detecting functional interactions. Finally, it concludes by emphasizing the need for efficient computational algorithms and the potential of filtering approaches to pre-select a subset of loci for more intensive analysis.