A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

ABSTRACT: Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease in

SUBMITTER: Staley JR 

PROVIDER: S-EPMC5520083 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature