Bridge: a GUI package for genetic risk prediction
में बचाया:
| में प्रकाशित: | BMC Genetics vol. 14 (2013), p. n/a |
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| मुख्य लेखक: | |
| अन्य लेखक: | |
| प्रकाशित: |
Springer Nature B.V.
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| विषय: | |
| ऑनलाइन पहुंच: | Citation/Abstract Full Text Full Text - PDF |
| टैग: |
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| सार: | Doc number: 122 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. 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. |
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| आईएसएसएन: | 1471-2156 2730-6844 |
| डिजिटल ऑब्जेक्ट पहचानकर्ता: | 10.1186/1471-2156-14-122 |
| स्रोत: | Health & Medical Collection |