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

Genome Biol. 2016 Dec 16;17(1):260. doi: 10.1186/s13059-016-1116-8.


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 (MIT license).

Keywords: Metagenomics; Metatranscriptomics; Microbial ecology; Microbiome; Multi-omics data integration; Reproducibility.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology
  • Genomics
  • Metagenome / genetics*
  • Microbiota / genetics*
  • Software*
  • Transcriptome / genetics*
  • Workflow