Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Adam, Yagoub, Samtal, Chaimae, Brandenburg, Jean-tristan, Falola, Oluwadamilare, Adebiyi, Ezekiel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2021
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
_version_ 1784652106424123392
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
work_keys_str_mv AT adamyagoub performingpostgenomewideassociationstudyanalysisoverviewchallengesandrecommendations
AT samtalchaimae performingpostgenomewideassociationstudyanalysisoverviewchallengesandrecommendations
AT brandenburgjeantristan performingpostgenomewideassociationstudyanalysisoverviewchallengesandrecommendations
AT falolaoluwadamilare performingpostgenomewideassociationstudyanalysisoverviewchallengesandrecommendations
AT adebiyiezekiel performingpostgenomewideassociationstudyanalysisoverviewchallengesandrecommendations