Detalle de: Disease Liability Prediction from Large Scale Genotyping Data Using Classifiers with a Reject Option
| Title | Disease Liability Prediction from Large Scale Genotyping Data Using Classifiers with a Reject Option |
| Abstract |
Genome-wide association studies (GWA) try to identify the genetic polymorphisms associated with variation in phenotypes. However, the most significant genetic variants may have a small predictive power to forecast the future development of common diseases. We study the prediction of the risk of developing a disease given genome-wide genotypic data using classifiers with a reject option, which only make a prediction when they are sufficiently certain, but in doubtful situations may reject making a classification. To test the reliability of our proposal, we used the Wellcome Trust Case Control Consortium (WTCCC) data set, comprising 14,000 cases of seven common human diseases and 3,000 shared controls. |
| Apa Reference | Quevedo, J.R., Bahamonde, A., Perez-Enciso, M. & Luaces, O. (2012). Disease Liability Prediction from Large Scale Genotyping Data Using Classifiers with a Reject Option. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(1), 88-97. 10.1109/TCBB.2011.44 |
| Doi | 10.1109/TCBB.2011.44 |
| Publication Date | Jan 2012 |
| Publication Type | Article |
| Researcher | Miguel Pérez Enciso |
| Ontology | Machine Learning in Biology, Genomics, Population genomics |
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