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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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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. |
format | Online Article Text |
id | pubmed-4897896 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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