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SPINGO: a rapid species-classifier for microbial amplicon sequences

BACKGROUND: Taxonomic classification is a corner stone for the characterisation and comparison of microbial communities. Currently, most existing methods are either slow, restricted to specific communities, highly sensitive to taxonomic inconsistencies, or limited to genus level classification. As c...

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Detalles Bibliográficos
Autores principales: Allard, Guy, Ryan, Feargal J., Jeffery, Ian B., Claesson, Marcus J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4599320/
https://www.ncbi.nlm.nih.gov/pubmed/26450747
http://dx.doi.org/10.1186/s12859-015-0747-1
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author Allard, Guy
Ryan, Feargal J.
Jeffery, Ian B.
Claesson, Marcus J.
author_facet Allard, Guy
Ryan, Feargal J.
Jeffery, Ian B.
Claesson, Marcus J.
author_sort Allard, Guy
collection PubMed
description BACKGROUND: Taxonomic classification is a corner stone for the characterisation and comparison of microbial communities. Currently, most existing methods are either slow, restricted to specific communities, highly sensitive to taxonomic inconsistencies, or limited to genus level classification. As crucial microbiota information is hinging on high-level resolution it is imperative to increase taxonomic resolution to species level wherever possible. RESULTS: In response to this need we developed SPINGO, a flexible and stand-alone software dedicated to high-resolution assignment of sequences to species level using partial 16S rRNA gene sequences from any environment. SPINGO compares favourably to other methods in terms of classification accuracy, and is as fast or faster than those that have higher error rates. As a demonstration of its flexibility for other types of target genes we successfully applied SPINGO also on cpn60 amplicon sequences. CONCLUSIONS: SPINGO is an accurate, flexible and fast method for low-level taxonomic assignment. This combination is becoming increasingly important for rapid and accurate processing of amplicon data generated by newer next generation sequencing technologies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0747-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-45993202015-10-10 SPINGO: a rapid species-classifier for microbial amplicon sequences Allard, Guy Ryan, Feargal J. Jeffery, Ian B. Claesson, Marcus J. BMC Bioinformatics Software BACKGROUND: Taxonomic classification is a corner stone for the characterisation and comparison of microbial communities. Currently, most existing methods are either slow, restricted to specific communities, highly sensitive to taxonomic inconsistencies, or limited to genus level classification. As crucial microbiota information is hinging on high-level resolution it is imperative to increase taxonomic resolution to species level wherever possible. RESULTS: In response to this need we developed SPINGO, a flexible and stand-alone software dedicated to high-resolution assignment of sequences to species level using partial 16S rRNA gene sequences from any environment. SPINGO compares favourably to other methods in terms of classification accuracy, and is as fast or faster than those that have higher error rates. As a demonstration of its flexibility for other types of target genes we successfully applied SPINGO also on cpn60 amplicon sequences. CONCLUSIONS: SPINGO is an accurate, flexible and fast method for low-level taxonomic assignment. This combination is becoming increasingly important for rapid and accurate processing of amplicon data generated by newer next generation sequencing technologies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0747-1) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-08 /pmc/articles/PMC4599320/ /pubmed/26450747 http://dx.doi.org/10.1186/s12859-015-0747-1 Text en © Allard et al. 2015 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
Allard, Guy
Ryan, Feargal J.
Jeffery, Ian B.
Claesson, Marcus J.
SPINGO: a rapid species-classifier for microbial amplicon sequences
title SPINGO: a rapid species-classifier for microbial amplicon sequences
title_full SPINGO: a rapid species-classifier for microbial amplicon sequences
title_fullStr SPINGO: a rapid species-classifier for microbial amplicon sequences
title_full_unstemmed SPINGO: a rapid species-classifier for microbial amplicon sequences
title_short SPINGO: a rapid species-classifier for microbial amplicon sequences
title_sort spingo: a rapid species-classifier for microbial amplicon sequences
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4599320/
https://www.ncbi.nlm.nih.gov/pubmed/26450747
http://dx.doi.org/10.1186/s12859-015-0747-1
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