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


ABSTRACT: 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).

SUBMITTER: Narayanasamy S 

PROVIDER: S-EPMC5159968 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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

Narayanasamy Shaman S   Jarosz Yohan Y   Muller Emilie E L EE   Heintz-Buschart Anna A   Herold Malte M   Kaysen Anne A   Laczny Cédric C CC   Pinel Nicolás N   May Patrick P   Wilmes Paul P  

Genome biology 20161216 1


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  ...[more]

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