Incorporating multiple-marker information to detect risk loci for rheumatoid arthritis.

ABSTRACT: In genome-wide association studies, new schemes are needed to incorporate multiple-locus information. In this article, we proposed a two-stage sliding-window approach to detect associations between a disease and multiple genetic polymorphisms. In the proposed approach, we measured the genetic association between a disease and a single-nucleotide polymorphism window by the newly developed likelihood ratio test-principal components statistic, and performed a sliding-window technique to detect disease susceptibility windows. We split the whole sample into two sub-samples, each of which contained a portion of cases and controls. In the first stage, we selected the top R windows by the statistics based on the first sub-sample, and in the second stage, we claimed significant windows by false-dis

SUBMITTER: Wang X 

PROVIDER: S-EPMC2795925 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature