Cargando…

MetaGenyo: a web tool for meta-analysis of genetic association studies

BACKGROUND: Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and o...

Descripción completa

Detalles Bibliográficos
Autores principales: Martorell-Marugan, Jordi, Toro-Dominguez, Daniel, Alarcon-Riquelme, Marta E., Carmona-Saez, Pedro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732412/
https://www.ncbi.nlm.nih.gov/pubmed/29246109
http://dx.doi.org/10.1186/s12859-017-1990-4
_version_ 1783286691275997184
author Martorell-Marugan, Jordi
Toro-Dominguez, Daniel
Alarcon-Riquelme, Marta E.
Carmona-Saez, Pedro
author_facet Martorell-Marugan, Jordi
Toro-Dominguez, Daniel
Alarcon-Riquelme, Marta E.
Carmona-Saez, Pedro
author_sort Martorell-Marugan, Jordi
collection PubMed
description BACKGROUND: Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise. RESULTS: We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results. CONCLUSIONS: MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-017-1990-4) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5732412
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-57324122017-12-21 MetaGenyo: a web tool for meta-analysis of genetic association studies Martorell-Marugan, Jordi Toro-Dominguez, Daniel Alarcon-Riquelme, Marta E. Carmona-Saez, Pedro BMC Bioinformatics Software BACKGROUND: Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise. RESULTS: We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results. CONCLUSIONS: MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-017-1990-4) contains supplementary material, which is available to authorized users. BioMed Central 2017-12-16 /pmc/articles/PMC5732412/ /pubmed/29246109 http://dx.doi.org/10.1186/s12859-017-1990-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Martorell-Marugan, Jordi
Toro-Dominguez, Daniel
Alarcon-Riquelme, Marta E.
Carmona-Saez, Pedro
MetaGenyo: a web tool for meta-analysis of genetic association studies
title MetaGenyo: a web tool for meta-analysis of genetic association studies
title_full MetaGenyo: a web tool for meta-analysis of genetic association studies
title_fullStr MetaGenyo: a web tool for meta-analysis of genetic association studies
title_full_unstemmed MetaGenyo: a web tool for meta-analysis of genetic association studies
title_short MetaGenyo: a web tool for meta-analysis of genetic association studies
title_sort metagenyo: a web tool for meta-analysis of genetic association studies
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732412/
https://www.ncbi.nlm.nih.gov/pubmed/29246109
http://dx.doi.org/10.1186/s12859-017-1990-4
work_keys_str_mv AT martorellmaruganjordi metagenyoawebtoolformetaanalysisofgeneticassociationstudies
AT torodominguezdaniel metagenyoawebtoolformetaanalysisofgeneticassociationstudies
AT alarconriquelmemartae metagenyoawebtoolformetaanalysisofgeneticassociationstudies
AT carmonasaezpedro metagenyoawebtoolformetaanalysisofgeneticassociationstudies