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mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes
: Profiling the taxonomic composition of microbial communities commonly involves the classification of ribosomal RNA gene fragments. As a trade-off to maintain high classification accuracy, existing tools are typically limited to the genus level. Here, we present mTAGs, a taxonomic profiling tool t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8696115/ https://www.ncbi.nlm.nih.gov/pubmed/34260698 http://dx.doi.org/10.1093/bioinformatics/btab465 |
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author | Salazar, Guillem Ruscheweyh, Hans-Joachim Hildebrand, Falk Acinas, Silvia G Sunagawa, Shinichi |
author_facet | Salazar, Guillem Ruscheweyh, Hans-Joachim Hildebrand, Falk Acinas, Silvia G Sunagawa, Shinichi |
author_sort | Salazar, Guillem |
collection | PubMed |
description | : Profiling the taxonomic composition of microbial communities commonly involves the classification of ribosomal RNA gene fragments. As a trade-off to maintain high classification accuracy, existing tools are typically limited to the genus level. Here, we present mTAGs, a taxonomic profiling tool that implements the alignment of metagenomic sequencing reads to degenerate consensus reference sequences of small subunit ribosomal RNA genes. It uses DNA fragments, that is, paired-end sequencing reads, as count units and provides relative abundance profiles at multiple taxonomic ranks, including operational taxonomic units based on a 97% sequence identity cutoff. At the genus rank, mTAGs outperformed other tools across several metrics, such as the F(1) score by >11% across data from different environments, and achieved competitive (F(1) score) or better results (Bray–Curtis dissimilarity) at the sub-genus level. AVAILABILITY AND IMPLEMENTATION: The software tool mTAGs is implemented in Python. The source code and binaries are freely available (https://github.com/SushiLab/mTAGs). The data underlying this article are available in Zenodo, at https://doi.org/10.5281/zenodo.4352762. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8696115 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-86961152022-01-04 mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes Salazar, Guillem Ruscheweyh, Hans-Joachim Hildebrand, Falk Acinas, Silvia G Sunagawa, Shinichi Bioinformatics Applications Notes : Profiling the taxonomic composition of microbial communities commonly involves the classification of ribosomal RNA gene fragments. As a trade-off to maintain high classification accuracy, existing tools are typically limited to the genus level. Here, we present mTAGs, a taxonomic profiling tool that implements the alignment of metagenomic sequencing reads to degenerate consensus reference sequences of small subunit ribosomal RNA genes. It uses DNA fragments, that is, paired-end sequencing reads, as count units and provides relative abundance profiles at multiple taxonomic ranks, including operational taxonomic units based on a 97% sequence identity cutoff. At the genus rank, mTAGs outperformed other tools across several metrics, such as the F(1) score by >11% across data from different environments, and achieved competitive (F(1) score) or better results (Bray–Curtis dissimilarity) at the sub-genus level. AVAILABILITY AND IMPLEMENTATION: The software tool mTAGs is implemented in Python. The source code and binaries are freely available (https://github.com/SushiLab/mTAGs). The data underlying this article are available in Zenodo, at https://doi.org/10.5281/zenodo.4352762. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-07-13 /pmc/articles/PMC8696115/ /pubmed/34260698 http://dx.doi.org/10.1093/bioinformatics/btab465 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Salazar, Guillem Ruscheweyh, Hans-Joachim Hildebrand, Falk Acinas, Silvia G Sunagawa, Shinichi mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes |
title | mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes |
title_full | mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes |
title_fullStr | mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes |
title_full_unstemmed | mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes |
title_short | mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes |
title_sort | mtags: taxonomic profiling using degenerate consensus reference sequences of ribosomal rna genes |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8696115/ https://www.ncbi.nlm.nih.gov/pubmed/34260698 http://dx.doi.org/10.1093/bioinformatics/btab465 |
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