News Release
QIIME 2: Re-Engineered System Allows for Reproducibility, Transparency, and Clarity of Microbiome Data Science
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The last two decades have seen a surge in the advancement of DNA sequencing and bioinformatics technology which has greatly contributed to how we now understand the microbiomes of the world. This week the publication Nature Biotechnology featured the correspondence announcing the success of QIIME 2. QIIME 2 was released in January of 2018 and took the learnings from QIIME, originally designed to address the problem of taking sequencing data from raw sequences and bring it to a point of interpretation and database deposition, and combined it with next generation advances. This re-engineered system is based on a plugin architecture, which can be used for the analysis of 16S data, shotgun metagenomics, metabolomics, functional analyses, and soon metatranscriptomics and metaproteomics.
QIIME’s framework was originally built at the Knight Lab, then at the University of Colorado at Boulder and led by postdoctoral scholar Greg Caporaso. 9 years later, QIIME 2’s framework was created by Caporaso’s own lab at Northern Arizona University and the final product was a community effort with 112 collaborators from 77 research institutions in 9 countries - including 28 co-authors from UC San Diego.
Since publication QIIME has had user adoption from around the world with nearly 16,000 citations on Google Scholar. With the expanded multi-omics focus it is expected that QIIME 2 will see faster user adoption rates, having been cited over 75 times prior to publication, and apply to a wider range of end-users from data scientists, biologists, clinicians, and policymakers.
As noted in the supplementary information of the paper, “a core goal of QIIME 2 is to cultivate a diverse and inclusive community of scientists, software engineers, statisticians, educators, students, and other microbiome stakeholders who are openly sharing methods, data, and knowledge to advance microbiome research.” The platform remains, like its predecessor, all open-source and free so anyone can continue to contribute, especially in the form of plugins, making it a living tool which has already seen 46,000 downloads and 13,000 unique visitors to the associated forum.
As paper co-author Antonio Gonzalez puts it, QIIME 2 is “quicker, faster, and better - allowing for users to use any plugin with any parameter in any way they want, or even create their own.” The plugins created by the creators and users are easily found in the QIIME 2 Library.
One of the main differentiators between QIIME 2 and other tools, is the multiple interactive visualizations that can easily be shared by email as a standard zip file with anyone. The recipient of the file does not need QIIME 2 or any coding to be able to review the data. Other tools such as Qiita, which wraps QIIME 2 and provides a graphical way to work with multi-omic microbiome data for those without programming experience, show additional possibilities and the hope is that over time the list will grow to include other tools that are built on top of the platform.
QIIME 2’s guiding principles are reproducibility, transparency, and clarity of microbiome data science. This is accomplished by it detecting corrupted results and indicating that the data is no longer reliable as well as users being able to determine how results are generated. As one user who is a veterinarian from Ithaca, NY explained, “I love how I can save my code and be able to go back to it six months later. Not only do I know exactly what I did but also I’m able to analyze a new dataset with much more ease. QIIME 2 offers an amazing advantage with provenance tracking and UUID identifiers for reproducible identification of sequence variants.”
The creators have also made sure that a support network was available for users by offering workshops (already 25 around the world), creating a well-regarded user forum, and an in-depth Get Started page on the website where users rave about the robust tutorials and superb documentation. As one user stated, “while the learning curve for QIIME could be considered a bit of a climb - once you become familiar with the syntax and utilizing the forum, the curve is less of a climb and more like a steady walk uphill that is not unpleasant.”
“Advances in microbiome research promise to improve many aspects of our health and our world, and QIIME 2 will help drive those advances by enabling accessible, community-driven microbiome data science,” said Caporaso.
To learn more about QIIME 2, visit https://qiime2.org.
Media Contacts
Erin Bateman
Center for Microbiome Innovation
858-408-6610
ebateman@eng.ucsd.edu