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Meta-Analysis of Genetic Association Studies
The object of this review is to help readers to understand meta-analysis of genetic association study. Genetic association studies are a powerful approach to identify susceptibility genes for common diseases. However, the results of these studies are not consistently reproducible. In order to overco...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society for Laboratory Medicine
2015
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390695/ https://www.ncbi.nlm.nih.gov/pubmed/25932435 http://dx.doi.org/10.3343/alm.2015.35.3.283 |
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author | Lee, Young Ho |
author_facet | Lee, Young Ho |
author_sort | Lee, Young Ho |
collection | PubMed |
description | The object of this review is to help readers to understand meta-analysis of genetic association study. Genetic association studies are a powerful approach to identify susceptibility genes for common diseases. However, the results of these studies are not consistently reproducible. In order to overcome the limitations of individual studies, larger sample sizes or meta-analysis is required. Meta-analysis is a statistical tool for combining results of different studies on the same topic, thus increasing statistical strength and precision. Meta-analysis of genetic association studies combines the results from independent studies, explores the sources of heterogeneity, and identifies subgroups associated with the factor of interest. Meta-analysis of genetic association studies is an effective tool for garnering a greater understanding of complex diseases and potentially provides new insights into gene-disease associations. |
format | Online Article Text |
id | pubmed-4390695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | The Korean Society for Laboratory Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-43906952015-05-01 Meta-Analysis of Genetic Association Studies Lee, Young Ho Ann Lab Med Review Article The object of this review is to help readers to understand meta-analysis of genetic association study. Genetic association studies are a powerful approach to identify susceptibility genes for common diseases. However, the results of these studies are not consistently reproducible. In order to overcome the limitations of individual studies, larger sample sizes or meta-analysis is required. Meta-analysis is a statistical tool for combining results of different studies on the same topic, thus increasing statistical strength and precision. Meta-analysis of genetic association studies combines the results from independent studies, explores the sources of heterogeneity, and identifies subgroups associated with the factor of interest. Meta-analysis of genetic association studies is an effective tool for garnering a greater understanding of complex diseases and potentially provides new insights into gene-disease associations. The Korean Society for Laboratory Medicine 2015-05 2015-04-01 /pmc/articles/PMC4390695/ /pubmed/25932435 http://dx.doi.org/10.3343/alm.2015.35.3.283 Text en © The Korean Society for Laboratory Medicine. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Lee, Young Ho Meta-Analysis of Genetic Association Studies |
title | Meta-Analysis of Genetic Association Studies |
title_full | Meta-Analysis of Genetic Association Studies |
title_fullStr | Meta-Analysis of Genetic Association Studies |
title_full_unstemmed | Meta-Analysis of Genetic Association Studies |
title_short | Meta-Analysis of Genetic Association Studies |
title_sort | meta-analysis of genetic association studies |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390695/ https://www.ncbi.nlm.nih.gov/pubmed/25932435 http://dx.doi.org/10.3343/alm.2015.35.3.283 |
work_keys_str_mv | AT leeyoungho metaanalysisofgeneticassociationstudies |