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Performing post-genome-wide association study analysis: overview, challenges and recommendations
Genome-wide association studies (GWAS) provide huge information on statistically significant single-nucleotide polymorphisms (SNPs) associated with various human complex traits and diseases. By performing GWAS studies, scientists have successfully identified the association of hundreds of thousands...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847724/ https://www.ncbi.nlm.nih.gov/pubmed/35222990 http://dx.doi.org/10.12688/f1000research.53962.1 |
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author | Adam, Yagoub Samtal, Chaimae Brandenburg, Jean-tristan Falola, Oluwadamilare Adebiyi, Ezekiel |
author_facet | Adam, Yagoub Samtal, Chaimae Brandenburg, Jean-tristan Falola, Oluwadamilare Adebiyi, Ezekiel |
author_sort | Adam, Yagoub |
collection | PubMed |
description | Genome-wide association studies (GWAS) provide huge information on statistically significant single-nucleotide polymorphisms (SNPs) associated with various human complex traits and diseases. By performing GWAS studies, scientists have successfully identified the association of hundreds of thousands to millions of SNPs to a single phenotype. Moreover, the association of some SNPs with rare diseases has been intensively tested. However, classic GWAS studies have not yet provided solid, knowledgeable insight into functional and biological mechanisms underlying phenotypes or mechanisms of diseases. Therefore, several post-GWAS (pGWAS) methods have been recommended. Currently, there is no simple scientific document to provide a quick guide for performing pGWAS analysis. pGWAS is a crucial step for a better understanding of the biological machinery beyond the SNPs. Here, we provide an overview to performing pGWAS analysis and demonstrate the challenges behind each method. Furthermore, we direct readers to key articles for each pGWAS method and present the overall issues in pGWAS analysis. Finally, we include a custom pGWAS pipeline to guide new users when performing their research. |
format | Online Article Text |
id | pubmed-8847724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-88477242022-02-24 Performing post-genome-wide association study analysis: overview, challenges and recommendations Adam, Yagoub Samtal, Chaimae Brandenburg, Jean-tristan Falola, Oluwadamilare Adebiyi, Ezekiel F1000Res Method Article Genome-wide association studies (GWAS) provide huge information on statistically significant single-nucleotide polymorphisms (SNPs) associated with various human complex traits and diseases. By performing GWAS studies, scientists have successfully identified the association of hundreds of thousands to millions of SNPs to a single phenotype. Moreover, the association of some SNPs with rare diseases has been intensively tested. However, classic GWAS studies have not yet provided solid, knowledgeable insight into functional and biological mechanisms underlying phenotypes or mechanisms of diseases. Therefore, several post-GWAS (pGWAS) methods have been recommended. Currently, there is no simple scientific document to provide a quick guide for performing pGWAS analysis. pGWAS is a crucial step for a better understanding of the biological machinery beyond the SNPs. Here, we provide an overview to performing pGWAS analysis and demonstrate the challenges behind each method. Furthermore, we direct readers to key articles for each pGWAS method and present the overall issues in pGWAS analysis. Finally, we include a custom pGWAS pipeline to guide new users when performing their research. F1000 Research Limited 2021-10-04 /pmc/articles/PMC8847724/ /pubmed/35222990 http://dx.doi.org/10.12688/f1000research.53962.1 Text en Copyright: © 2021 Adam Y et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Method Article Adam, Yagoub Samtal, Chaimae Brandenburg, Jean-tristan Falola, Oluwadamilare Adebiyi, Ezekiel Performing post-genome-wide association study analysis: overview, challenges and recommendations |
title | Performing post-genome-wide association study analysis: overview, challenges and recommendations |
title_full | Performing post-genome-wide association study analysis: overview, challenges and recommendations |
title_fullStr | Performing post-genome-wide association study analysis: overview, challenges and recommendations |
title_full_unstemmed | Performing post-genome-wide association study analysis: overview, challenges and recommendations |
title_short | Performing post-genome-wide association study analysis: overview, challenges and recommendations |
title_sort | performing post-genome-wide association study analysis: overview, challenges and recommendations |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847724/ https://www.ncbi.nlm.nih.gov/pubmed/35222990 http://dx.doi.org/10.12688/f1000research.53962.1 |
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