Shim Sungryul, Kim Jiyoung, Jung Wonguen, Shin In-Soo, Bae Jong-Myon
Institute for Clinical Molecular Biology Research, Soonchunhyang University Hospital, Seoul, Korea.
Department of Radiation Oncology, Ewha Womans University School of Medicine, Seoul, Korea.
Epidemiol Health. 2016 Dec 18;38:e2016058. doi: 10.4178/epih.e2016058. eCollection 2016.
This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy-Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The 'genhwcci' and 'metan' commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the 'metareg' command of STATA should be conducted to evaluate related factors of heterogeneities.
本综述旨在梳理全基因组关联研究的系统综述流程,以便实践和应用全基因组荟萃分析(GWMA)。该流程包含一系列五个步骤:检索与筛选、相关信息提取、有效性评估、按遗传模型类型进行荟萃分析以及异质性评估。与干预荟萃分析不同,GWMA必须在第三步评估哈迪 - 温伯格平衡(HWE),并在第四步按五种潜在遗传模型进行荟萃分析,这五种模型包括显性、隐性、纯合子对比、杂合子对比和等位基因对比。STATA软件的“genhwcci”和“metan”命令分别用于评估HWE和计算效应量汇总值。应使用STATA的“metareg”命令进行荟萃回归,以评估异质性的相关因素。