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Qiita: rapid, web-enabled microbiome meta-analysis

Nature Methods volume 15, pages 796–798 (2018)Cite this article

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Abstract

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.

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Fig. 1: Example meta-analysis in Qiita.

Data availability

All data used are available via Qiita and EBI (where applicable). The Human Microbiome Project (HMP) and iHMP data are available via the HMP Data Analysis and Coordination Center (DACC) at https://portal.hmpdacc.org/. Analytical steps for this paper can be found at https://github.com/knightlab-analyses/qiita-paper. Additionally, the Qiita analysis can be found at https://qiita.ucsd.edu/analysis/description/15093/; note that the user must log in to Qiita to access this analysis. Source data for Supplementary Fig. 1 are available online.

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Acknowledgements

We are grateful to J. Debelius, J. Jansson, D. Bazaldua, and J. Kuczynski for their help in improving Qiita via suggestion, code changes, and contributed datasets, or during the preparation of this manuscript; and to J. Gordon and his laboratory for helpful discussions. This work was supported in part by the Alfred P. Sloan Foundation (2017-9838 and 2015-13933 (R.K.)), the NIH/NIDDK (P01DK078669 (R.K.)), the NSF (DBI-1565057 and 1565100 (J.G.C. and R.K.)), the Office of Naval Research (ONR; N00014-15-1-2809 (R.K.)), and the US Army (CDMRP W81XWH-15-1-0653 (R.K.)).

Author information

Author notes

  1. Jose A. Navas-Molina

    Present address: Google LLC, Mountain View, CA, USA

  2. Joshua Shorenstein

    Present address: Inscripta, Inc., Boulder, CO, USA

  3. These authors contributed equally: Antonio Gonzalez and Jose A. Navas-Molina.

Authors and Affiliations

  1. Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA

    Antonio Gonzalez, Jose A. Navas-Molina, Tomasz Kosciolek, Daniel McDonald, Yoshiki Vázquez-Baeza, Gail Ackermann, Jeff DeReus, Stefan Janssen, Jon G. Sanders, Joshua Shorenstein, Hannes Holste, Pieter C. Dorrestein & Rob Knight

  2. Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA

    Jose A. Navas-Molina, Hannes Holste & Rob Knight

  3. Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA

    Austin D. Swafford, Stephanie B. Orchanian, Pieter C. Dorrestein & Rob Knight

  4. Department of Biology, University of California, San Diego, La Jolla, CA, USA

    Semar Petrus

  5. Department of Computer Science, University of Colorado, Boulder, Boulder, CO, USA

    Adam Robbins-Pianka

  6. Earth & Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA

    Colin J. Brislawn

  7. Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA

    Mingxun Wang & Pieter C. Dorrestein

  8. Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, USA

    Jai Ram Rideout, Evan Bolyen, Matthew Dillon & J. Gregory Caporaso

  9. Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA

    J. Gregory Caporaso

Authors
  1. Antonio Gonzalez
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  23. Rob Knight
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Contributions

A.G., J.A.N.-M., T.K., D.M., Y.V.-B., G.A., J.D., S.J., A.D.S., S.B.O., J.G.S., J.S., H.H., S.P., A.R.-P., C.J.B., M.W., J.R.R., E.B., M.D., J.G.C., P.C.D., and R.K. implemented the Qiita main or the Qiita plugins code. A.G., J.A.N.-M., and Y.V.-B. conducted the example meta-analysis. All authors wrote the manuscript.

Corresponding author

Correspondence to Rob Knight.

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The authors declare no competing interests.

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Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Figure 1 Data loaded in Qiita and uploaded to EBI.

A. Monthly studies and sample depositions to EBI-ENA via Qiita. B. Geographical distribution of the samples present in Qiita

Supplementary information

Supplementary Text and Figures

Supplementary Figure 1, Supplementary Tables 1 and 2

Reporting Summary

Supplementary Software

SupplementarySoftware.zip contains two zip files: (1) qiita-master.zip, which is the main code for the Qiita software at the time of publication (latest version: https://github.com/biocore/qiita), and (2) qiita-paper-master.zip, which includes all steps and necessary files to reproduce all panels in Fig. 1 (live repository: https://github.com/knightlab-analyses/qiita-paper).

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Gonzalez, A., Navas-Molina, J.A., Kosciolek, T. et al. Qiita: rapid, web-enabled microbiome meta-analysis. Nat Methods 15, 796–798 (2018). https://doi.org/10.1038/s41592-018-0141-9

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