title: Bridge: a GUI package for genetic risk prediction.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.forename: Chengyin
authors.initials: C
authors.lastname: Ye
authors.affiliation: Department of Epidemiology and Biostatistics, Michigan State University, B601 West Fee Hall, 909 Fee Road, 48824 East Lansing, MI, USA. qlu@epi.msu.edu.
authors.forename: Qing
authors.initials: Q
authors.lastname: Lu
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D003424:Crohn Disease / Q000209:etiology / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D012372:ROC Curve; D012307:Risk Factors; D012984:Software; D014584:User-Computer Interface