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Minireview | Spotlight

Reintroducing mothur: 10 Years Later

Patrick D. Schloss
Andrew J. McBain, Editor
Patrick D. Schloss
aDepartment of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
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Andrew J. McBain
University of Manchester
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DOI: 10.1128/AEM.02343-19
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ABSTRACT

More than 10 years ago, we published the paper describing the mothur software package in Applied and Environmental Microbiology. Our goal was to create a comprehensive package that allowed users to analyze amplicon sequence data using the most robust methods available. mothur has helped lead the community through the ongoing sequencing revolution and continues to provide this service to the microbial ecology community. Beyond its success and impact on the field, mothur’s development exposed a series of observations that are generally translatable across science. Perhaps the observation that stands out the most is that all science is done in the context of prevailing ideas and available technologies. Although it is easy to criticize choices that were made 10 years ago through a modern lens, if we were to wait for all of the possible limitations to be solved before proceeding, science would stall. Even preceding the development of mothur, it was necessary to address the most important problems and work backwards to other problems that limited access to robust sequence analysis tools. At the same time, we strive to expand mothur’s capabilities in a data-driven manner to incorporate new ideas and accommodate changes in data and desires of the research community. It has been edifying to see the benefit that a simple set of tools can bring to so many other researchers.

  • Copyright © 2020 Schloss.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

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Reintroducing mothur: 10 Years Later
Patrick D. Schloss
Applied and Environmental Microbiology Jan 2020, 86 (2) e02343-19; DOI: 10.1128/AEM.02343-19

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Reintroducing mothur: 10 Years Later
Patrick D. Schloss
Applied and Environmental Microbiology Jan 2020, 86 (2) e02343-19; DOI: 10.1128/AEM.02343-19
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KEYWORDS

16S rRNA gene
amplicon
bioinformatics
data analysis
microbial ecology
microbiome

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