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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Epidemiology
2016
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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 |
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author | Shim, Sungryul Kim, Jiyoung Jung, Wonguen Shin, In-Soo Bae, Jong-Myon |
author_facet | Shim, Sungryul Kim, Jiyoung Jung, Wonguen Shin, In-Soo Bae, Jong-Myon |
author_sort | Shim, Sungryul |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5309730 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Korean Society of Epidemiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-53097302017-02-28 Meta-analysis for genome-wide association studies using case-control design: application and practice Shim, Sungryul Kim, Jiyoung Jung, Wonguen Shin, In-Soo Bae, Jong-Myon Epidemiol Health Methods 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. Korean Society of Epidemiology 2016-12-18 /pmc/articles/PMC5309730/ /pubmed/28092928 http://dx.doi.org/10.4178/epih.e2016058 Text en ©2016, Korean Society of Epidemiology This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Shim, Sungryul Kim, Jiyoung Jung, Wonguen Shin, In-Soo Bae, Jong-Myon Meta-analysis for genome-wide association studies using case-control design: application and practice |
title | Meta-analysis for genome-wide association studies using case-control design: application and practice |
title_full | Meta-analysis for genome-wide association studies using case-control design: application and practice |
title_fullStr | Meta-analysis for genome-wide association studies using case-control design: application and practice |
title_full_unstemmed | Meta-analysis for genome-wide association studies using case-control design: application and practice |
title_short | Meta-analysis for genome-wide association studies using case-control design: application and practice |
title_sort | meta-analysis for genome-wide association studies using case-control design: application and practice |
topic | Methods |
url | 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 |
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