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MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling
BACKGROUND: Many metagenome analysis tools are presently available to classify sequences and profile environmental samples. In particular, taxonomic profiling and binning methods are commonly used for such tasks. Tools available among these two categories make use of several techniques, e.g., read m...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5557516/ https://www.ncbi.nlm.nih.gov/pubmed/28807044 http://dx.doi.org/10.1186/s40168-017-0318-y |
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author | Piro, Vitor C. Matschkowski, Marcel Renard, Bernhard Y. |
author_facet | Piro, Vitor C. Matschkowski, Marcel Renard, Bernhard Y. |
author_sort | Piro, Vitor C. |
collection | PubMed |
description | BACKGROUND: Many metagenome analysis tools are presently available to classify sequences and profile environmental samples. In particular, taxonomic profiling and binning methods are commonly used for such tasks. Tools available among these two categories make use of several techniques, e.g., read mapping, k-mer alignment, and composition analysis. Variations on the construction of the corresponding reference sequence databases are also common. In addition, different tools provide good results in different datasets and configurations. All this variation creates a complicated scenario to researchers to decide which methods to use. Installation, configuration and execution can also be difficult especially when dealing with multiple datasets and tools. RESULTS: We propose MetaMeta: a pipeline to execute and integrate results from metagenome analysis tools. MetaMeta provides an easy workflow to run multiple tools with multiple samples, producing a single enhanced output profile for each sample. MetaMeta includes a database generation, pre-processing, execution, and integration steps, allowing easy execution and parallelization. The integration relies on the co-occurrence of organisms from different methods as the main feature to improve community profiling while accounting for differences in their databases. CONCLUSIONS: In a controlled case with simulated and real data, we show that the integrated profiles of MetaMeta overcome the best single profile. Using the same input data, it provides more sensitive and reliable results with the presence of each organism being supported by several methods. MetaMeta uses Snakemake and has six pre-configured tools, all available at BioConda channel for easy installation (conda install -c bioconda metameta). The MetaMeta pipeline is open-source and can be downloaded at: https://gitlab.com/rki_bioinformatics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-017-0318-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5557516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55575162017-08-16 MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling Piro, Vitor C. Matschkowski, Marcel Renard, Bernhard Y. Microbiome Software BACKGROUND: Many metagenome analysis tools are presently available to classify sequences and profile environmental samples. In particular, taxonomic profiling and binning methods are commonly used for such tasks. Tools available among these two categories make use of several techniques, e.g., read mapping, k-mer alignment, and composition analysis. Variations on the construction of the corresponding reference sequence databases are also common. In addition, different tools provide good results in different datasets and configurations. All this variation creates a complicated scenario to researchers to decide which methods to use. Installation, configuration and execution can also be difficult especially when dealing with multiple datasets and tools. RESULTS: We propose MetaMeta: a pipeline to execute and integrate results from metagenome analysis tools. MetaMeta provides an easy workflow to run multiple tools with multiple samples, producing a single enhanced output profile for each sample. MetaMeta includes a database generation, pre-processing, execution, and integration steps, allowing easy execution and parallelization. The integration relies on the co-occurrence of organisms from different methods as the main feature to improve community profiling while accounting for differences in their databases. CONCLUSIONS: In a controlled case with simulated and real data, we show that the integrated profiles of MetaMeta overcome the best single profile. Using the same input data, it provides more sensitive and reliable results with the presence of each organism being supported by several methods. MetaMeta uses Snakemake and has six pre-configured tools, all available at BioConda channel for easy installation (conda install -c bioconda metameta). The MetaMeta pipeline is open-source and can be downloaded at: https://gitlab.com/rki_bioinformatics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-017-0318-y) contains supplementary material, which is available to authorized users. BioMed Central 2017-08-14 /pmc/articles/PMC5557516/ /pubmed/28807044 http://dx.doi.org/10.1186/s40168-017-0318-y Text en © The Author(s) 2017 Open Access This 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 Piro, Vitor C. Matschkowski, Marcel Renard, Bernhard Y. MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling |
title | MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling |
title_full | MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling |
title_fullStr | MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling |
title_full_unstemmed | MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling |
title_short | MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling |
title_sort | metameta: integrating metagenome analysis tools to improve taxonomic profiling |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5557516/ https://www.ncbi.nlm.nih.gov/pubmed/28807044 http://dx.doi.org/10.1186/s40168-017-0318-y |
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