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Meta-analysis for genome-wide association studies using case-control design: application and practice
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Sungryul Shim, Jiyoung Kim, Wonguen Jung, In-Soo Shin, Jong-Myon Bae
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Epidemiol Health. 2016;38:e2016058. Published online December 18, 2016
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DOI: https://doi.org/10.4178/epih.e2016058
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 Abstract
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Abstract
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.
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Summary
Korean summary
오늘날 활발히 수행되고 있는 유전체역학연구는 재현성의 문제, 대상자 크기의 한계 등으로 유전체 메타분석 연구가 요구되고 있다. 유전체 메타분석의 전반적인 수행 단계는 약물, 수술 등의 중개연구의 메타분석처럼 5 단계를 밟아 수행된다. 그러나, 유전체 메타분석은 3번째 과정에서 Hardy–Weinberg equilibrium (HWE) 검정과 4번째 과정에서 5가지 가능한 유전형 모델에 따라 메타분석이 이루어진다는 점에서 중개연구의 메타분석과 차이가 있다.
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Citations
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