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Meta-analysis for genome-wide association studies using case-control design: application and practice

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-analy...

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Detalles Bibliográficos
Autores principales: Shim, Sungryul, Kim, Jiyoung, Jung, Wonguen, Shin, In-Soo, Bae, Jong-Myon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Epidemiology 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309730/
https://www.ncbi.nlm.nih.gov/pubmed/28092928
http://dx.doi.org/10.4178/epih.e2016058
Descripción
Sumario: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.