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ReDU: a framework to find and reanalyze public mass spectrometry data


We present ReDU (, a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one’s own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.

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Fig. 1: ReDU framework and illustrative public ReDU data analyses.
Fig. 2: Repository-scale molecular networking of public data in ReDU.

Data availability

Source data for the results presented in this paper are available on GitHub ( All curated sample information can be downloaded from the ReDU homepage ( by selecting ‘Download Database’. The current version of the ReDU information used to generate the results in this paper is archived in the GNPS/MassIVE repository ( The accession number is MSV000084206 (

Code availability

All software is citable using Up-to-date developments of ReDU are available in GitHub (, with corresponding documentation (


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We thank the individuals involved in the funding, administration, sample collection and data acquisition of the public data used in ReDU. We recognize the financial support of the US National Institutes of Health (P41 GM103484, R03 CA211211, R01 LM013115 and R01 GM107550), the Sloan Foundation (R.K.), the Gordon and Betty Moore Foundation (P.C.D., N.B., K.L.M.), a FAPESP fellowship (2018/24865-4), the American Society for Mass Spectrometry (A.K.J.), NSF grants IOS-1656481 (P.C.D. and A.M.C.R.) and ABI-1759980, Netherlands eScience Center no. ASDI.2017.030 (J.J.J.v.d.H.), the Krupp Endowed Fund (R. Coras), the US Office of Naval Research (N00014-15-1-2809) and the University of California, San Diego, Center for Microbiome Innovation SEED grants.

Author information

Authors and Affiliations



A.K.J., M.W. and P.C.D. developed the ReDU concept. A.K.J., M.W. and C.M.A. wrote code and engineered the ReDU infrastructure. A.K.J., C.M.A., R.S.A., S.A., A.A.A., G.A., A.T.A., A. Bauermeister, S.B., A. Bouslimani, A.M.C.R., R. Chaar, R. Coras, E.O.E., J.J.J.v.d.H., J.M.G., E.C.G., M.H., K.L.J., Z.K., A.L.G., A.L., L.-I.M., K.L.M., M.J.M., A.V.M., R.C.M., Y.A.M.G., N.H.N., L.F.N., M.E., M.N.E., M.P., D.P., R.Q., N.S., F.V., A.V. and K.C.W. curated metadata enabling ReDU. A.K.J., M.W., C.M.A., S.A.J., L.-I.M., M.E., J.J.J.v.d.H., J.M.G., M.P. and P.C.D. tested the ReDU infrastructure and provided feedback. A.K.J., M.W., C.M.A., M.E., J.J.J.v.d.H., R.K., N.B. and P.C.D. wrote and edited the manuscript. R.K., N.B. and P.C.D. provided supervision and funding support.

Corresponding author

Correspondence to Pieter C. Dorrestein.

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Competing interests

P.C.D. is a scientific advisor for Sirenas LLC, Galileio and Cybele Microbiome and scientific advisor and co-founder of Enveda. M.W. is a founder of Ometa Labs LLC. A.A. is a consultant for Ometa Labs LLC.

Additional information

Peer review information Allison Doerr was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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

Extended data

Extended Data Fig. 1 Repository-scale molecular cartography enabled by ReDU.

ReDU samples with latitude and longitude information, n = 34,003, were grouped by latitude and longitude (n = 2068 different locations) and plotted colored by number of annotations per file (log10 scaled).

Extended Data Fig. 2 Comparison of bacterial cultures using Group Comparator in ReDU.

Bacterial cultures of 1280|Staphylococcus aureus (n = 49), 1423|Bacillus subtilis (n = 89), and 1883|Streptomyces (n = 7) were compared and chemical differences are illustrated by pyroGlu-Ile, staurosporine, and surfactin-C14.

Extended Data Fig 3 Repository-scale molecular networking of human blood (n = 711), fecal (n = 5,097), and urine (n = 307) supplemented by MolNetEnhancer.

(a) MolNetEnhancer enhanced molecular network in which components are colored based on Classyfire chemical class prediction. (b) Number of nodes per Classyfire chemical class prediction. Nodes without a match in Classyfire are not displayed.

Extended Data Fig 4 Molecular cartography of the distribution of drugs on the human body visualized using ili.

Descaladinose azithromycin, a drug metabolite of azithromycin, distribution in human (n = 17,117; normalized by the number of files per sample).

Supplementary information

Supplementary Information

Supplementary Discussion, Supplementary Table 1 and Supplementary Figs. 1–5.

Reporting Summary

Supplementary Table 2

Tabulated information for proposed clindamycin metabolites based on repository-scale molecular networking in ReDU.

Supplementary Video 1

The empirically observed UBERON-based location of drugs and drug metabolites observed in metabolomics data 28 August 2019–10 July 2020 processed through ReDU.

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Jarmusch, A.K., Wang, M., Aceves, C.M. et al. ReDU: a framework to find and reanalyze public mass spectrometry data. Nat Methods 17, 901–904 (2020).

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