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

doi:10.1093/bioinformatics/btaa277

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

Bioinformatics. 2020 Jul 1;36(13):4088-4090. doi: 10.1093/bioinformatics/btaa277.

Authors

Benjamin Hillmann¹, Gabriel A Al-Ghalith², Robin R Shields-Cutler³, Qiyun Zhu⁴, Rob Knight^{4

5

6}, Dan Knights^{1

2

3}

Affiliations

¹ Department of Computer Science and Engineering, University of Minnesota, Minneapolis, 55455 Minnesota, USA.
² Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, 55455 Minnesota, USA.
³ Biotechnology Institute, University of Minnesota, Minneapolis, 55455 Minnesota, USA.
⁴ Department of Pediatrics, University of California San Diego, San Diego, 92161 5 California, USA.
⁵ Department of Computer of Science and Engineering, University of California San Diego, San Diego, 92093 California, USA.
⁶ Center for Microbiome Innovation, University of California San Diego, San Diego, 92093 California, USA.

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.

Publication types

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

MeSH terms

Bayes Theorem
Data Analysis
Metagenomics
Microbiota* / genetics
Software*

Abstract

Publication types

MeSH terms

Grants and funding