Smooth-Threshold Multivariate Genetic Prediction with Unbiased Model Selection.

ABSTRACT: We develop a new genetic prediction method, smooth-threshold multivariate genetic prediction, using single nucleotide polymorphisms (SNPs) data in genome-wide association studies (GWASs). Our method consists of two stages. At the first stage, unlike the usual discontinuous SNP screening as used in the gene score method, our method continuously screens SNPs based on the output from standard univariate analysis for marginal association of each SNP. At the second stage, the predictive model is built by a generalized ridge regression simultaneously using the screened SNPs with SNP weight determined by the strength of marginal association. Continuous SNP screening by the smooth thresholding not only makes prediction stable but also leads to a closed form expression of generalized degrees of fre

SUBMITTER: Ueki M 

PROVIDER: S-EPMC5849235 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature