Disease liability prediction from large scale genotyping data using classifiers with a reject option

José R. Quevedo, Antonio Bahamonde, Miguel Pérez-Enciso, Oscar Luaces

Research output: Contribution to journalArticleResearchpeer-review

6 Citations (Scopus)

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. © 2012 IEEE.
Original languageEnglish
Article number5728945
Pages (from-to)88-97
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume9
Issue number1
DOIs
Publication statusPublished - 1 Jan 2012

Keywords

  • classification with a reject option
  • Genome-wide analysis
  • risk of common human diseases

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