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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.

SUBMITTER: Kim J

PROVIDER: S-EPMC3651372 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Prediction of a time-to-event trait using genome wide SNP data.

Kim Jinseog J Sohn Insuk I Son Dae-Soon DS Kim Dong Hwan DH Ahn Taejin T Jung Sin-Ho SH

BMC bioinformatics 20130219

<h4>Background</h4>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.<h4>Results</h4>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. T ...[more]

PMID: 23418752

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