Reference : IMP: a pipeline for reproducible referenceindependent integrated metagenomic and meta...
Scientific journals : Article
Life sciences : Biotechnology
Life sciences : Environmental sciences & ecology
Life sciences : Microbiology
Life sciences : Multidisciplinary, general & others
Systems Biomedicine
http://hdl.handle.net/10993/30495
IMP: a pipeline for reproducible referenceindependent integrated metagenomic and metatranscriptomic analyses
English
Narayanasamy, Shaman mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Jarosz, Yohan mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Muller, Emilie mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Buschart, Anna mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Herold, Malte mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Kaysen, Anne mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Laczny, Cedric Christian mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Pinel, Nicolás mailto [> >]
May, Patrick mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Wilmes, Paul mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Dec-2016
Genome Biology
BioMed Central
17
260
Yes (verified by ORBilu)
International
1474-7596
1474-760X
London
United Kingdom
[en] Multi-omics data integration ; Metagenomics ; Metatranscriptomics ; Microbial ecology ; Microbiome ; Reproducibility ; High-throughput
[en] 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).
Luxembourg Centre for Systems Biomedicine (LCSB): Eco-Systems Biology (Wilmes Group)
Fonds National de la Recherche - FnR
Researchers ; Students ; General public ; Others
http://hdl.handle.net/10993/30495
10.1186/s13059-016-1116-8
http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1116-8
FnR ; FNR3951311 > Paul Wilmes > SYSBIONAMA > Systems Biology of Natural Microbial Assemblages > 01/02/2010 > 31/01/2015 > 2009

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