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

Benjamin Hillmann, Gabriel A. Al-Ghalith, Robin R. Shields-Cutler, Qiyun Zhu, Rob Knight, Dan Knights

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

SUMMARY: 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.

AVAILABILITY AND IMPLEMENTATION: https://github.com/knights-lab/SHOGUN.

Original languageEnglish (US)
Pages (from-to)4088-4090
Number of pages3
JournalBioinformatics
Volume36
Issue number13
DOIs
StatePublished - Jul 1 2020

Bibliographical note

Publisher Copyright:
© 2020 The Author(s). Published by Oxford University Press. All rights reserved.

Keywords

  • Bayes Theorem
  • Data Analysis
  • Metagenomics
  • Microbiota/genetics
  • Software

PubMed: MeSH publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Journal Article
  • Research Support, N.I.H., Extramural

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