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Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data

Motivation: The characterization of phylogenetic and functional diversity is a key element in the analysis of microbial communities. Amplicon-based sequencing of marker genes, such as 16S rRNA, is a powerful tool for assessing and comparing the structure of microbial communities at a high phylogenet...

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Autores principales: Aßhauer, Kathrin P., Wemheuer, Bernd, Daniel, Rolf, Meinicke, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547618/
https://www.ncbi.nlm.nih.gov/pubmed/25957349
http://dx.doi.org/10.1093/bioinformatics/btv287
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author Aßhauer, Kathrin P.
Wemheuer, Bernd
Daniel, Rolf
Meinicke, Peter
author_facet Aßhauer, Kathrin P.
Wemheuer, Bernd
Daniel, Rolf
Meinicke, Peter
author_sort Aßhauer, Kathrin P.
collection PubMed
description Motivation: The characterization of phylogenetic and functional diversity is a key element in the analysis of microbial communities. Amplicon-based sequencing of marker genes, such as 16S rRNA, is a powerful tool for assessing and comparing the structure of microbial communities at a high phylogenetic resolution. Because 16S rRNA sequencing is more cost-effective than whole metagenome shotgun sequencing, marker gene analysis is frequently used for broad studies that involve a large number of different samples. However, in comparison to shotgun sequencing approaches, insights into the functional capabilities of the community get lost when restricting the analysis to taxonomic assignment of 16S rRNA data. Results: Tax4Fun is a software package that predicts the functional capabilities of microbial communities based on 16S rRNA datasets. We evaluated Tax4Fun on a range of paired metagenome/16S rRNA datasets to assess its performance. Our results indicate that Tax4Fun provides a good approximation to functional profiles obtained from metagenomic shotgun sequencing approaches. Availability and implementation: Tax4Fun is an open-source R package and applicable to output as obtained from the SILVAngs web server or the application of QIIME with a SILVA database extension. Tax4Fun is freely available for download at http://tax4fun.gobics.de/. Contact: kasshau@gwdg.de Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-45476182015-08-25 Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data Aßhauer, Kathrin P. Wemheuer, Bernd Daniel, Rolf Meinicke, Peter Bioinformatics Applications Notes Motivation: The characterization of phylogenetic and functional diversity is a key element in the analysis of microbial communities. Amplicon-based sequencing of marker genes, such as 16S rRNA, is a powerful tool for assessing and comparing the structure of microbial communities at a high phylogenetic resolution. Because 16S rRNA sequencing is more cost-effective than whole metagenome shotgun sequencing, marker gene analysis is frequently used for broad studies that involve a large number of different samples. However, in comparison to shotgun sequencing approaches, insights into the functional capabilities of the community get lost when restricting the analysis to taxonomic assignment of 16S rRNA data. Results: Tax4Fun is a software package that predicts the functional capabilities of microbial communities based on 16S rRNA datasets. We evaluated Tax4Fun on a range of paired metagenome/16S rRNA datasets to assess its performance. Our results indicate that Tax4Fun provides a good approximation to functional profiles obtained from metagenomic shotgun sequencing approaches. Availability and implementation: Tax4Fun is an open-source R package and applicable to output as obtained from the SILVAngs web server or the application of QIIME with a SILVA database extension. Tax4Fun is freely available for download at http://tax4fun.gobics.de/. Contact: kasshau@gwdg.de Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2015-09-01 2015-05-07 /pmc/articles/PMC4547618/ /pubmed/25957349 http://dx.doi.org/10.1093/bioinformatics/btv287 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://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
Aßhauer, Kathrin P.
Wemheuer, Bernd
Daniel, Rolf
Meinicke, Peter
Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data
title Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data
title_full Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data
title_fullStr Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data
title_full_unstemmed Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data
title_short Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data
title_sort tax4fun: predicting functional profiles from metagenomic 16s rrna data
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547618/
https://www.ncbi.nlm.nih.gov/pubmed/25957349
http://dx.doi.org/10.1093/bioinformatics/btv287
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