title: Prediction of a time-to-event trait using genome wide SNP data.
abstract: BACKGROUND
  A popular objective of many high-throughput genome projects is to discover various genomic markers associated with traits and develop statistical models to predict traits of future patients based on marker values.
  
  
  RESULTS
  In this paper, we present a prediction method for time-to-event traits using genome-wide single-nucleotide polymorphisms (SNPs). We also propose a MaxTest associating between a time-to-event trait and a SNP accounting for its possible genetic models. The proposed MaxTest can help screen out nonprognostic SNPs and identify genetic models of prognostic SNPs. The performance of the proposed method is evaluated through simulations.
  
  
  CONCLUSIONS
  In conjunction with the MaxTest, the proposed method provides more parsimonious prediction models but includes more prognostic SNPs than some naive prediction methods. The proposed method is demonstrated with real GWAS data.
authors: Department of Statistics and Information Science, Dongguk University, Gyeongju 780-714, Korea.
authors: Jinseog
authors: J
authors: Kim
authors: Insuk
authors: I
authors: Sohn
authors: Dae-Soon
authors: DS
authors: Son
authors: Dong Hwan
authors: DH
authors: Kim
authors: Taejin
authors: T
authors: Ahn
authors: Sin-Ho
authors: SH
authors: Jung
mesh_terms: D000465:Algorithms; D055106:Genome-Wide Association Study / Q000379:methods*; D023281:Genomics; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000235:genetics / Q000401:mortality; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D016016:Proportional Hazards Models