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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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Detalles Bibliográficos
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
Descripción
Sumario: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.