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

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Journal

Bioinformatics - July 1, 2020

Authors

Benjamin Hillmann (Ph.D. student), Gabriel A Al-Ghalith, Robin R Shields-Cutler, Qiyun Zhu, Rob Knight, Dan Knights (professor)

Abstract

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.

Link to full paper

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

Keywords

bioinformatics, computational biology