Multilocus association mapping using generalized ridge logistic regression.

ABSTRACT:

Background

In genome-wide association studies, it is widely accepted that multilocus methods are more powerful than testing single-nucleotide polymorphisms (SNPs) one at a time. Among statistical approaches considering many predictors simultaneously, scan statistics are an effective tool for detecting susceptibility genomic regions and mapping disease genes. In this study, inspired by the idea of scan statistics, we propose a novel sliding window-based method for identifying a parsimonious subset of contiguous SNPs that best predict disease status.

Results

Within each sliding window, we apply a forward model selection procedure using generalized ridge logistic regression for model fitness in each step. In power simulations, we compare the performance of our method with that

SUBMITTER: Liu Z 

PROVIDER: S-EPMC3224109 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature