Powerful multi-marker association tests: unifying genomic distance-based regression and logistic regression.

ABSTRACT: To detect genetic association with common and complex diseases, many statistical tests have been proposed for candidate gene or genome-wide association studies with the case-control design. Due to linkage disequilibrium (LD), multi-marker association tests can gain power over single-marker tests with a Bonferroni multiple testing adjustment. Among many existing multi-marker association tests, most target to detect only one of many possible aspects in distributional differences between the genotypes of cases and controls, such as allele frequency differences, while a few new ones aim to target two or three aspects, all of which can be implemented in logistic regression. In contrast to logistic regression, a genomic distance-based regression (GDBR) approach aims to detect some high-order gen

SUBMITTER: Han F 

PROVIDER: S-EPMC3345567 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature