Controlling for confounding factors and revealing their interactions in genetic association meta-analyses: a computing method and application for stratification analyses.

ABSTRACT: Subgroup and stratification analyses have been widely applied in genetic association studies to compare the effects of different factors or control for the effects of the confounding variables associated with a disease. However, studies have not systematically provided application standards and computing methods for stratification analyses. Based on the Mantel-Haenszel and Inverse-Variant approaches and two practical computing methods described in previous studies, we propose a standard stratification method for meta-analyses that contains two sequential steps: factorial stratification analysis and confounder-controlling stratification analysis. Examples of genetic association meta-analyses are used to illustrate these points. The standard stratification analysis method identifies interact

SUBMITTER: Lin S 

PROVIDER: S-EPMC5844733 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature