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IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses

Existing workflows for the analysis of multi-omic microbiome datasets are lab-specific and often result in sub-optimal data usage. Here we present IMP, a reproducible and modular pipeline for the integrated and reference-independent analysis of coupled metagenomic and metatranscriptomic data. IMP in...

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Autores principales: Narayanasamy, Shaman, Jarosz, Yohan, Muller, Emilie E. L., Heintz-Buschart, Anna, Herold, Malte, Kaysen, Anne, Laczny, Cédric C., Pinel, Nicolás, May, Patrick, Wilmes, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5159968/
https://www.ncbi.nlm.nih.gov/pubmed/27986083
http://dx.doi.org/10.1186/s13059-016-1116-8
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author Narayanasamy, Shaman
Jarosz, Yohan
Muller, Emilie E. L.
Heintz-Buschart, Anna
Herold, Malte
Kaysen, Anne
Laczny, Cédric C.
Pinel, Nicolás
May, Patrick
Wilmes, Paul
author_facet Narayanasamy, Shaman
Jarosz, Yohan
Muller, Emilie E. L.
Heintz-Buschart, Anna
Herold, Malte
Kaysen, Anne
Laczny, Cédric C.
Pinel, Nicolás
May, Patrick
Wilmes, Paul
author_sort Narayanasamy, Shaman
collection PubMed
description Existing workflows for the analysis of multi-omic microbiome datasets are lab-specific and often result in sub-optimal data usage. Here we present IMP, a reproducible and modular pipeline for the integrated and reference-independent analysis of coupled metagenomic and metatranscriptomic data. IMP incorporates robust read preprocessing, iterative co-assembly, analyses of microbial community structure and function, automated binning, as well as genomic signature-based visualizations. The IMP-based data integration strategy enhances data usage, output volume, and output quality as demonstrated using relevant use-cases. Finally, IMP is encapsulated within a user-friendly implementation using Python and Docker. IMP is available at http://r3lab.uni.lu/web/imp/ (MIT license). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1116-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-51599682016-12-23 IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses Narayanasamy, Shaman Jarosz, Yohan Muller, Emilie E. L. Heintz-Buschart, Anna Herold, Malte Kaysen, Anne Laczny, Cédric C. Pinel, Nicolás May, Patrick Wilmes, Paul Genome Biol Software Existing workflows for the analysis of multi-omic microbiome datasets are lab-specific and often result in sub-optimal data usage. Here we present IMP, a reproducible and modular pipeline for the integrated and reference-independent analysis of coupled metagenomic and metatranscriptomic data. IMP incorporates robust read preprocessing, iterative co-assembly, analyses of microbial community structure and function, automated binning, as well as genomic signature-based visualizations. The IMP-based data integration strategy enhances data usage, output volume, and output quality as demonstrated using relevant use-cases. Finally, IMP is encapsulated within a user-friendly implementation using Python and Docker. IMP is available at http://r3lab.uni.lu/web/imp/ (MIT license). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1116-8) contains supplementary material, which is available to authorized users. BioMed Central 2016-12-16 /pmc/articles/PMC5159968/ /pubmed/27986083 http://dx.doi.org/10.1186/s13059-016-1116-8 Text en © The Author(s). 2016 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
Narayanasamy, Shaman
Jarosz, Yohan
Muller, Emilie E. L.
Heintz-Buschart, Anna
Herold, Malte
Kaysen, Anne
Laczny, Cédric C.
Pinel, Nicolás
May, Patrick
Wilmes, Paul
IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses
title IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses
title_full IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses
title_fullStr IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses
title_full_unstemmed IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses
title_short IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses
title_sort imp: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5159968/
https://www.ncbi.nlm.nih.gov/pubmed/27986083
http://dx.doi.org/10.1186/s13059-016-1116-8
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