4.7 Article

SHOGUN: a modular, accurate and scalable framework for microbiome quantification

Journal

BIOINFORMATICS
Volume 36, Issue 13, Pages 4088-4090

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btaa277

Keywords

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Funding

  1. University of Minnesota Masonic Cancer Center
  2. National Institutes of Health [R01AI121383, P01DK078669]
  3. National Science Foundation [1565057]
  4. Alfred P. Sloan Foundation [2017-9838]
  5. Masonic Cancer Center at the University of Minnesota
  6. Direct For Biological Sciences
  7. Div Of Biological Infrastructure [1565057] Funding Source: National Science Foundation

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The software pipeline SHOGUN profiles known taxonomic and gene abundances of short-read shotgun metagenomics sequencing data. The pipeline is scalable, modular and flexible. Data analysis and transformation steps can be run individually or together in an automated workflow. Users can easily create new reference databases and can select one of three DNA alignment tools, ranging from ultra-fast low-RAM k-mer-based database search to fully exhaustive gapped DNA alignment, to best fit their analysis needs and computational resources. The pipeline includes an implementation of a published method for taxonomy assignment disambiguation with empirical Bayesian redistribution. The software is installable via the conda resource management framework, has plugins for the QIIME2 and QIITA packages and produces both taxonomy and gene abundance profile tables with a single command, thus promoting convenient and reproducible metagenomics research.

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