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Gigwa—Genotype investigator for genome-wide analyses

BACKGROUND: Exploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing...

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Autores principales: Sempéré, Guilhem, Philippe, Florian, Dereeper, Alexis, Ruiz, Manuel, Sarah, Gautier, Larmande, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897896/
https://www.ncbi.nlm.nih.gov/pubmed/27267926
http://dx.doi.org/10.1186/s13742-016-0131-8
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author Sempéré, Guilhem
Philippe, Florian
Dereeper, Alexis
Ruiz, Manuel
Sarah, Gautier
Larmande, Pierre
author_facet Sempéré, Guilhem
Philippe, Florian
Dereeper, Alexis
Ruiz, Manuel
Sarah, Gautier
Larmande, Pierre
author_sort Sempéré, Guilhem
collection PubMed
description BACKGROUND: Exploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions. DESCRIPTION: Here we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats. CONCLUSIONS: The Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13742-016-0131-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-48978962016-06-09 Gigwa—Genotype investigator for genome-wide analyses Sempéré, Guilhem Philippe, Florian Dereeper, Alexis Ruiz, Manuel Sarah, Gautier Larmande, Pierre Gigascience Technical Note BACKGROUND: Exploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions. DESCRIPTION: Here we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats. CONCLUSIONS: The Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13742-016-0131-8) contains supplementary material, which is available to authorized users. BioMed Central 2016-06-06 /pmc/articles/PMC4897896/ /pubmed/27267926 http://dx.doi.org/10.1186/s13742-016-0131-8 Text en © The Author(s). 2016 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 Technical Note
Sempéré, Guilhem
Philippe, Florian
Dereeper, Alexis
Ruiz, Manuel
Sarah, Gautier
Larmande, Pierre
Gigwa—Genotype investigator for genome-wide analyses
title Gigwa—Genotype investigator for genome-wide analyses
title_full Gigwa—Genotype investigator for genome-wide analyses
title_fullStr Gigwa—Genotype investigator for genome-wide analyses
title_full_unstemmed Gigwa—Genotype investigator for genome-wide analyses
title_short Gigwa—Genotype investigator for genome-wide analyses
title_sort gigwa—genotype investigator for genome-wide analyses
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897896/
https://www.ncbi.nlm.nih.gov/pubmed/27267926
http://dx.doi.org/10.1186/s13742-016-0131-8
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