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Protein signature-based estimation of metagenomic abundances including all domains of life and viruses
Motivation: Metagenome analysis requires tools that can estimate the taxonomic abundances in anonymous sequence data over the whole range of biological entities. Because there is usually no prior knowledge about the data composition, not only all domains of life but also viruses have to be included...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3624802/ https://www.ncbi.nlm.nih.gov/pubmed/23418187 http://dx.doi.org/10.1093/bioinformatics/btt077 |
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author | Klingenberg, Heiner Aßhauer, Kathrin Petra Lingner, Thomas Meinicke, Peter |
author_facet | Klingenberg, Heiner Aßhauer, Kathrin Petra Lingner, Thomas Meinicke, Peter |
author_sort | Klingenberg, Heiner |
collection | PubMed |
description | Motivation: Metagenome analysis requires tools that can estimate the taxonomic abundances in anonymous sequence data over the whole range of biological entities. Because there is usually no prior knowledge about the data composition, not only all domains of life but also viruses have to be included in taxonomic profiling. Such a full-range approach, however, is difficult to realize owing to the limited coverage of available reference data. In particular, archaea and viruses are generally not well represented by current genome databases. Results: We introduce a novel approach to taxonomic profiling of metagenomes that is based on mixture model analysis of protein signatures. Our results on simulated and real data reveal the difficulties of the existing methods when measuring achaeal or viral abundances and show the overall good profiling performance of the protein-based mixture model. As an application example, we provide a large-scale analysis of data from the Human Microbiome Project. This demonstrates the utility of our method as a first instance profiling tool for a fast estimate of the community structure. Availability: http://gobics.de/TaxyPro. Contact: pmeinic@gwdg.de Supplementary information: Supplementary Material is available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-3624802 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-36248022013-04-12 Protein signature-based estimation of metagenomic abundances including all domains of life and viruses Klingenberg, Heiner Aßhauer, Kathrin Petra Lingner, Thomas Meinicke, Peter Bioinformatics Original Papers Motivation: Metagenome analysis requires tools that can estimate the taxonomic abundances in anonymous sequence data over the whole range of biological entities. Because there is usually no prior knowledge about the data composition, not only all domains of life but also viruses have to be included in taxonomic profiling. Such a full-range approach, however, is difficult to realize owing to the limited coverage of available reference data. In particular, archaea and viruses are generally not well represented by current genome databases. Results: We introduce a novel approach to taxonomic profiling of metagenomes that is based on mixture model analysis of protein signatures. Our results on simulated and real data reveal the difficulties of the existing methods when measuring achaeal or viral abundances and show the overall good profiling performance of the protein-based mixture model. As an application example, we provide a large-scale analysis of data from the Human Microbiome Project. This demonstrates the utility of our method as a first instance profiling tool for a fast estimate of the community structure. Availability: http://gobics.de/TaxyPro. Contact: pmeinic@gwdg.de Supplementary information: Supplementary Material is available at Bioinformatics online. Oxford University Press 2013-04-15 2013-02-15 /pmc/articles/PMC3624802/ /pubmed/23418187 http://dx.doi.org/10.1093/bioinformatics/btt077 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Klingenberg, Heiner Aßhauer, Kathrin Petra Lingner, Thomas Meinicke, Peter Protein signature-based estimation of metagenomic abundances including all domains of life and viruses |
title | Protein signature-based estimation of metagenomic abundances including all domains of life and viruses |
title_full | Protein signature-based estimation of metagenomic abundances including all domains of life and viruses |
title_fullStr | Protein signature-based estimation of metagenomic abundances including all domains of life and viruses |
title_full_unstemmed | Protein signature-based estimation of metagenomic abundances including all domains of life and viruses |
title_short | Protein signature-based estimation of metagenomic abundances including all domains of life and viruses |
title_sort | protein signature-based estimation of metagenomic abundances including all domains of life and viruses |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3624802/ https://www.ncbi.nlm.nih.gov/pubmed/23418187 http://dx.doi.org/10.1093/bioinformatics/btt077 |
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