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Bridge: a GUI package for genetic risk prediction

Chengyin Ye12 and Qing Lu2*

Author Affiliations

1 Department of Health Management, School of Medicine, Hangzhou Normal University, Hangzhou, China

2 Department of Epidemiology and Biostatistics, Michigan State University, B601 West Fee Hall, 909 Fee Road, 48824 East Lansing, MI, USA

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BMC Genetics 2013, 14:122  doi:10.1186/1471-2156-14-122

Published: 20 December 2013



Risk prediction models capitalizing on genetic and environmental information hold great promise for individualized disease prediction and prevention. Nevertheless, linking the genetic and environmental risk predictors into a useful risk prediction model remains a great challenge. To facilitate risk prediction analyses, we have developed a graphical user interface package, Bridge.


The package is built for both designing and analyzing a risk prediction model. In the design stage, it provides an estimated classification accuracy of the model using essential genetic and environmental information gained from public resources and/or previous studies, and determines the sample size required to verify this accuracy. In the analysis stage, it adopts a robust and powerful algorithm to form the risk prediction model.


The package is developed based on the optimality theory of the likelihood ratio and therefore theoretically could form a model with high performance. It can be used to handle a relatively large number of genetic and environmental predictors, with consideration of their possible interactions, and so is particularly useful for studying risk prediction models for common complex diseases.

Gene-gene interactions; Optimal receiver operating characteristic curve