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. © 2012 IEEE.
|Journal||IEEE/ACM Transactions on Computational Biology and Bioinformatics|
|Publication status||Published - 1 Jan 2012|
- classification with a reject option
- Genome-wide analysis
- risk of common human diseases
Quevedo, J. R., Bahamonde, A., Pérez-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. . https://doi.org/10.1109/TCBB.2011.44