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VAMPS: a website for visualization and analysis of microbial population structures

BACKGROUND: The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 10(5)–10(8) reads with...

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Autores principales: Huse, Susan M, Mark Welch, David B, Voorhis, Andy, Shipunova, Anna, Morrison, Hilary G, Eren, A Murat, Sogin, Mitchell L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922339/
https://www.ncbi.nlm.nih.gov/pubmed/24499292
http://dx.doi.org/10.1186/1471-2105-15-41
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author Huse, Susan M
Mark Welch, David B
Voorhis, Andy
Shipunova, Anna
Morrison, Hilary G
Eren, A Murat
Sogin, Mitchell L
author_facet Huse, Susan M
Mark Welch, David B
Voorhis, Andy
Shipunova, Anna
Morrison, Hilary G
Eren, A Murat
Sogin, Mitchell L
author_sort Huse, Susan M
collection PubMed
description BACKGROUND: The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 10(5)–10(8) reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing. RESULTS: We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators’ private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships. CONCLUSIONS: VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next-generation sequence data. Any web-capable device can be used to upload, process, explore, and extract data and results from VAMPS. VAMPS encourages researchers to share sequence and metadata, and fosters collaboration between researchers of disparate biomes who recognize common patterns in shared data.
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spelling pubmed-39223392014-02-13 VAMPS: a website for visualization and analysis of microbial population structures Huse, Susan M Mark Welch, David B Voorhis, Andy Shipunova, Anna Morrison, Hilary G Eren, A Murat Sogin, Mitchell L BMC Bioinformatics Software BACKGROUND: The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 10(5)–10(8) reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing. RESULTS: We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators’ private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships. CONCLUSIONS: VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next-generation sequence data. Any web-capable device can be used to upload, process, explore, and extract data and results from VAMPS. VAMPS encourages researchers to share sequence and metadata, and fosters collaboration between researchers of disparate biomes who recognize common patterns in shared data. BioMed Central 2014-02-05 /pmc/articles/PMC3922339/ /pubmed/24499292 http://dx.doi.org/10.1186/1471-2105-15-41 Text en Copyright © 2014 Huse et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
Huse, Susan M
Mark Welch, David B
Voorhis, Andy
Shipunova, Anna
Morrison, Hilary G
Eren, A Murat
Sogin, Mitchell L
VAMPS: a website for visualization and analysis of microbial population structures
title VAMPS: a website for visualization and analysis of microbial population structures
title_full VAMPS: a website for visualization and analysis of microbial population structures
title_fullStr VAMPS: a website for visualization and analysis of microbial population structures
title_full_unstemmed VAMPS: a website for visualization and analysis of microbial population structures
title_short VAMPS: a website for visualization and analysis of microbial population structures
title_sort vamps: a website for visualization and analysis of microbial population structures
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922339/
https://www.ncbi.nlm.nih.gov/pubmed/24499292
http://dx.doi.org/10.1186/1471-2105-15-41
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