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Qiita: rapid, web-enabled microbiome meta-analysis

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

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Authors

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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Competing interests

The authors declare no competing interests.

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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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