Bridge: a GUI package for genetic risk prediction
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| הוצא לאור ב: | BMC Genetics vol. 14 (2013), p. n/a |
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| מחברים אחרים: | |
| יצא לאור: |
Springer Nature B.V.
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| גישה מקוונת: | Citation/Abstract Full Text Full Text - PDF |
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MARC
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| 024 | 7 | |a 10.1186/1471-2156-14-122 |2 doi | |
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| 045 | 2 | |b d20130101 |b d20131231 | |
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| 100 | 1 | |a Ye, Chengyin | |
| 245 | 1 | |a Bridge: a GUI package for genetic risk prediction | |
| 260 | |b Springer Nature B.V. |c 2013 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 610 | 4 | |a Michigan State University | |
| 650 | 2 | 2 | |a Algorithms |
| 650 | 2 | 2 | |a Area Under Curve |
| 650 | 2 | 2 | |a Crohn Disease |x etiology |
| 650 | 2 | 2 | |a Crohn Disease |x genetics |
| 650 | 2 | 2 | |a Humans |
| 650 | 1 | 2 | |a Models, Genetic |
| 650 | 2 | 2 | |a Polymorphism, Single Nucleotide |
| 650 | 2 | 2 | |a ROC Curve |
| 650 | 2 | 2 | |a Risk Factors |
| 650 | 1 | 2 | |a Software |
| 650 | 2 | 2 | |a User-Computer Interface |
| 653 | |a Studies | ||
| 653 | |a Child abuse & neglect | ||
| 653 | |a Accuracy | ||
| 653 | |a Disease | ||
| 653 | |a Programming languages | ||
| 653 | |a Epidemiology | ||
| 653 | |a User interface | ||
| 653 | |a Operating systems | ||
| 653 | |a Mortality | ||
| 700 | 1 | |a Lu, Qing | |
| 773 | 0 | |t BMC Genetics |g vol. 14 (2013), p. n/a | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1471062696/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/1471062696/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/1471062696/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |