{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:21:05Z","timestamp":1792783265501,"version":"4.5.0"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T00:00:00Z","timestamp":1790985600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T00:00:00Z","timestamp":1790985600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100018694","name":"HORIZON EUROPE Marie Sklodowska-Curie Actions","doi-asserted-by":"publisher","award":["101073062"],"award-info":[{"award-number":["101073062"]}],"id":[{"id":"10.13039\/100018694","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Autonomous Province of Bolzano","award":["D53C25001030003"],"award-info":[{"award-number":["D53C25001030003"]}],"id":[{"id":"https:\/\/ror.org\/00b61dk18","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Metabolomics"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Two decades after the Metabolomics Standards Initiative, public deposition of raw LC-MS\/MS data into archives such as MetaboLights, Metabolomics Workbench, GNPS and MassBank has matured, but the analyses that turn raw files into reported feature tables remain difficult to share, audit and reuse. The FAIR principles, originally formulated for data, later extended to research software and to workflows, make a strong case that this gap matters; we adopt that view and ask how an educational resource can help researchers cross it.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aim of review<\/jats:title>\n                    <jats:p>\n                      This is an educational review where we describe the principles of FAIR and reproducible analysis as they apply to untargeted LC-MS metabolomics, and we show how those principles are realised in\n                      <jats:italic>Metabonaut<\/jats:italic>\n                      , an open educational resource built on top of the R for Mass Spectrometry\/Bioconductor ecosystem.\n                      <jats:italic>Metabonaut<\/jats:italic>\n                      provides executable example workflows from raw mzML files to annotated feature tables, demonstrates interoperability across programming languages, and is built with and for the community.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key scientific concepts of review<\/jats:title>\n                    <jats:p>\n                      After a brief tour of the underlying software ecosystem and of literate programming, the review discusses three topics, each through one or more\n                      <jats:italic>Metabonaut<\/jats:italic>\n                      vignettes: visual inspection and quality control, reuse of public archives at scale, and cross-language interoperability. Together, they teach how to carry FAIR practice from data to analysis: making the analysis itself, and not only the data it consumes, shareable, auditable and reusable. The source code of Metabonaut and links to pre-rendered workflow documents are available at\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/RforMassSpectrometry\/Metabonaut\" ext-link-type=\"uri\">https:\/\/github.com\/RforMassSpectrometry\/Metabonaut<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11306-026-02538-x","type":"journal-article","created":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T18:16:57Z","timestamp":1791051417000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Metabonaut: an open educational resource for learning reproducible, script-based untargeted LC-MS\/MS metabolomics"],"prefix":"10.1007","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-5429-6846","authenticated-orcid":false,"given":"Philippine","family":"Louail","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6916-401X","authenticated-orcid":false,"given":"Marilyn","family":"De Graeve","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3779-492X","authenticated-orcid":false,"given":"Alexandru","family":"Mahmoud","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9674-042X","authenticated-orcid":false,"given":"Daniel","family":"Marques de S\u00e1 e Silva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8501-7319","authenticated-orcid":false,"given":"Kozo","family":"Nishida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1108-518X","authenticated-orcid":false,"given":"Vilhelm","family":"Suksi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4044-4285","authenticated-orcid":false,"given":"Anna","family":"Tagliaferri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3976-6068","authenticated-orcid":false,"given":"Gabriele","family":"Tom\u00e8","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3057-6460","authenticated-orcid":false,"given":"Vinicius","family":"Verri Hernandes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6977-7147","authenticated-orcid":false,"given":"Johannes","family":"Rainer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,3]]},"reference":[{"key":"2538_CR1","doi-asserted-by":"publisher","unstructured":"Allaire, J. J., Teague, C., Scheidegger, C., Xie, Y., Dervieux, C., & Woodhull, G. (2026, March). Quarto. https:\/\/doi.org\/10.5281\/zenodo.5960048","DOI":"10.5281\/zenodo.5960048"},{"issue":"4","key":"2538_CR2","doi-asserted-by":"publisher","first-page":"1309","DOI":"10.1214\/09-AOAS291","volume":"3","author":"KA Baggerly","year":"2009","unstructured":"Baggerly, K. A., & Coombes, K. R. (2009). Deriving chemosensitivity from cell lines: Forensic bioinformatics and reproducible research in high-throughput biology. The Annals of Applied Statistics, 3(4), 1309\u20131334. https:\/\/doi.org\/10.1214\/09-AOAS291","journal-title":"The Annals of Applied Statistics"},{"issue":"1","key":"2538_CR3","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1038\/s41597-022-01710-x","volume":"9","author":"M Barker","year":"2022","unstructured":"Barker, M., Chue Hong, N. P., Katz, D. S., Lamprecht, A. L., Martinez-Ortiz, C., Psomopoulos, F., et al. (2022). Introducing the FAIR Principles for research software. Scientific Data, 9(1), 622. https:\/\/doi.org\/10.1038\/s41597-022-01710-x","journal-title":"Scientific Data"},{"issue":"6","key":"2538_CR4","doi-asserted-by":"publisher","first-page":"752","DOI":"10.1016\/j.cels.2018.05.012","volume":"6","author":"B Batut","year":"2018","unstructured":"Batut, B., Hiltemann, S., Bagnacani, A., Baker, D., Bhardwaj, V., Blank, C., et al. (2018). Community-Driven Data Analysis Training for Biology. Cell Systems, 6(6), 752\u2013758e1. https:\/\/doi.org\/10.1016\/j.cels.2018.05.012","journal-title":"Cell Systems"},{"issue":"1","key":"2538_CR5","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1021\/acs.analchem.9b04884","volume":"92","author":"W Bittremieux","year":"2020","unstructured":"Bittremieux, W. (2020). spectrum_utils: A Python Package for Mass Spectrometry Data Processing and Visualization. Analytical Chemistry, 92(1), 659\u2013661. https:\/\/doi.org\/10.1021\/acs.analchem.9b04884","journal-title":"Analytical Chemistry"},{"issue":"2","key":"2538_CR6","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1093\/bioinformatics\/btn603","volume":"25","author":"S B\u00f6cker","year":"2009","unstructured":"B\u00f6cker, S., Letzel, M. C., Lipt\u00e1k, Z., & Pervukhin, A. (2009). SIRIUS: Decomposing isotope patterns for metabolite identification. Bioinformatics, 25(2), 218\u2013224. https:\/\/doi.org\/10.1093\/bioinformatics\/btn603","journal-title":"Bioinformatics"},{"issue":"1","key":"2538_CR7","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1145\/2723872.2723882","volume":"49","author":"C Boettiger","year":"2015","unstructured":"Boettiger, C. (2015). An introduction to Docker for reproducible research. SIGOPS Oper Syst Rev, 49(1), 71\u201379. https:\/\/doi.org\/10.1145\/2723872.2723882","journal-title":"SIGOPS Oper Syst Rev"},{"issue":"6","key":"2538_CR8","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1007\/s11306-018-1367-3","volume":"14","author":"D Broadhurst","year":"2018","unstructured":"Broadhurst, D., Goodacre, R., Reinke, S. N., Kuligowski, J., Wilson, I. D., Lewis, M. R., & Dunn, W. B. (2018). Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies. Metabolomics: Official Journal of the Metabolomic Society, 14(6), 72. https:\/\/doi.org\/10.1007\/s11306-018-1367-3","journal-title":"Metabolomics: Official Journal of the Metabolomic Society"},{"issue":"10","key":"2538_CR9","doi-asserted-by":"publisher","first-page":"918","DOI":"10.1038\/nbt.2377","volume":"30","author":"MC Chambers","year":"2012","unstructured":"Chambers, M. C., Maclean, B., Burke, R., Amodei, D., Ruderman, D. L., Neumann, S., et al. (2012). A cross-platform toolkit for mass spectrometry and proteomics. Nature Biotechnology, 30(10), 918\u2013920. https:\/\/doi.org\/10.1038\/nbt.2377","journal-title":"Nature Biotechnology"},{"issue":"24","key":"2538_CR10","doi-asserted-by":"publisher","first-page":"4313","DOI":"10.1093\/bioinformatics\/bty528","volume":"34","author":"J Chong","year":"2018","unstructured":"Chong, J., & Xia, J. (2018). MetaboAnalystR: An R package for flexible and reproducible analysis of metabolomics data. Bioinformatics, 34(24), 4313\u20134314. https:\/\/doi.org\/10.1093\/bioinformatics\/bty528","journal-title":"Bioinformatics"},{"issue":"4","key":"2538_CR11","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1038\/s41592-019-0344-8","volume":"16","author":"K D\u00fchrkop","year":"2019","unstructured":"D\u00fchrkop, K., Fleischauer, M., Ludwig, M., Aksenov, A. A., Melnik, A. V., Meusel, M., et al. (2019). SIRIUS 4: A rapid tool for turning tandem mass spectra into metabolite structure information. Nature Methods, 16(4), 299\u2013302. https:\/\/doi.org\/10.1038\/s41592-019-0344-8","journal-title":"Nature Methods"},{"issue":"1","key":"2538_CR12","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1023\/A:1013713905833","volume":"48","author":"O Fiehn","year":"2002","unstructured":"Fiehn, O. (2002). Metabolomics\u2013the link between genotypes and phenotypes. Plant molecular biology, 48(1), 155\u2013171.","journal-title":"Plant molecular biology"},{"issue":"12","key":"2538_CR13","doi-asserted-by":"publisher","first-page":"e1004801","DOI":"10.1371\/journal.pgen.1004801","volume":"10","author":"A Ganna","year":"2014","unstructured":"Ganna, A., Salihovic, S., Sundstr\u00f6m, J., Broeckling, C. D., Hedman, \u00c5. K., Magnusson, P. K. E., et al. (2014). Large-scale Metabolomic Profiling Identifies Novel Biomarkers for Incident Coronary Heart Disease. PLoS Genetics, 10(12), e1004801. https:\/\/doi.org\/10.1371\/journal.pgen.1004801","journal-title":"PLoS Genetics"},{"issue":"10","key":"2538_CR14","doi-asserted-by":"publisher","first-page":"R80","DOI":"10.1186\/gb-2004-5-10-r80","volume":"5","author":"RC Gentleman","year":"2004","unstructured":"Gentleman, R. C., Carey, V. J., Bates, D. M., Bolstad, B., Dettling, M., Dudoit, S., et al. (2004). Bioconductor: Open software development for computational biology and bioinformatics. Genome Biology, 5(10), R80. https:\/\/doi.org\/10.1186\/gb-2004-5-10-r80","journal-title":"Genome Biology"},{"issue":"9","key":"2538_CR15","doi-asserted-by":"publisher","first-page":"1493","DOI":"10.1093\/bioinformatics\/btu813","volume":"31","author":"F Giacomoni","year":"2015","unstructured":"Giacomoni, F., Le Corguill\u00e9, G., Monsoor, M., Landi, M., Pericard, P., P\u00e9t\u00e9ra, M., et al. (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics, 31(9), 1493\u20131495. https:\/\/doi.org\/10.1093\/bioinformatics\/btu813","journal-title":"Bioinformatics"},{"issue":"109","key":"2538_CR16","doi-asserted-by":"publisher","first-page":"8070","DOI":"10.21105\/joss.08070","volume":"10","author":"MD Graeve","year":"2025","unstructured":"Graeve, M. D., Bittremieux, W., Naake, T., Huber, C., Anagho-Mattanovich, M., Hoffmann, N., et al. (2025). SpectriPy: Enhancing Cross-Language Mass Spectrometry Data Analysis with R and Python. Journal of Open Source Software, 10(109), 8070. https:\/\/doi.org\/10.21105\/joss.08070","journal-title":"Journal of Open Source Software"},{"issue":"7","key":"2538_CR17","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1038\/s41592-018-0046-7","volume":"15","author":"B Gr\u00fcning","year":"2018","unstructured":"Gr\u00fcning, B., Dale, R., Sj\u00f6din, A., Chapman, B. A., Rowe, J., Tomkins-Tinch, C. H., et al. (2018). Bioconda: Sustainable and comprehensive software distribution for the life sciences. Nature Methods, 15(7), 475\u2013476. https:\/\/doi.org\/10.1038\/s41592-018-0046-7","journal-title":"Nature Methods"},{"key":"2538_CR18","doi-asserted-by":"publisher","unstructured":"Guitton Y, Tremblay-Franco M, Le Corguill\u00e9 G, Martin JF, P\u00e9t\u00e9ra M, Roger-Mele P,et al. (2017) Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics. Int J Biochem Cell Biol, 93:89-101. https:\/\/doi.org\/10.1016\/j.biocel.2017.07.002","DOI":"10.1016\/j.biocel.2017.07.002"},{"issue":"1","key":"2538_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13321-020-00477-w","volume":"13","author":"R Helmus","year":"2021","unstructured":"Helmus, R., ter Laak, T. L., van Wezel, A. P., de Voogt, P., & Schymanski, E. L. (2021). patRoon: Open source software platform for environmental mass spectrometry based non-target screening. Journal of Cheminformatics, 13(1), 1. https:\/\/doi.org\/10.1186\/s13321-020-00477-w","journal-title":"Journal of Cheminformatics"},{"issue":"3","key":"2538_CR20","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1038\/s41587-021-01045-9","volume":"40","author":"MA Hoffmann","year":"2022","unstructured":"Hoffmann, M. A., Nothias, L. F., Ludwig, M., Fleischauer, M., Gentry, E. C., Witting, M., et al. (2022). High-confidence structural annotation of metabolites absent from spectral libraries. Nature Biotechnology, 40(3), 411\u2013421. https:\/\/doi.org\/10.1038\/s41587-021-01045-9","journal-title":"Nature Biotechnology"},{"issue":"5","key":"2538_CR21","doi-asserted-by":"publisher","first-page":"3302","DOI":"10.1021\/acs.analchem.8b04310","volume":"91","author":"N Hoffmann","year":"2019","unstructured":"Hoffmann, N., Rein, J., Sachsenberg, T., Hartler, J., Haug, K., Mayer, G., et al. (2019). mzTab-M: A Data Standard for Sharing Quantitative Results in Mass Spectrometry Metabolomics. Analytical Chemistry, 91(5), 3302\u20133310. https:\/\/doi.org\/10.1021\/acs.analchem.8b04310","journal-title":"Analytical Chemistry"},{"issue":"7","key":"2538_CR22","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1002\/jms.1777","volume":"45","author":"H Horai","year":"2010","unstructured":"Horai, H., Arita, M., Kanaya, S., Nihei, Y., Ikeda, T., Suwa, K., et al. (2010). MassBank: A public repository for sharing mass spectral data for life sciences. Journal of Mass Spectrometry, 45(7), 703\u2013714. https:\/\/doi.org\/10.1002\/jms.1777","journal-title":"Journal of Mass Spectrometry"},{"issue":"52","key":"2538_CR23","doi-asserted-by":"publisher","first-page":"2411","DOI":"10.21105\/joss.02411","volume":"5","author":"F Huber","year":"2020","unstructured":"Huber, F., Verhoeven, S., Meijer, C., Spreeuw, H., Castilla, E. M. V., Geng, C., et al. (2020). matchms - processing and similarity evaluation of mass spectrometry data. Journal of Open Source Software, 5(52), 2411. https:\/\/doi.org\/10.21105\/joss.02411","journal-title":"Journal of Open Source Software"},{"issue":"9","key":"2538_CR24","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1007\/s11306-022-01926-3","volume":"18","author":"JA Kirwan","year":"2022","unstructured":"Kirwan, J. A., Gika, H., Beger, R. D., Bearden, D., Dunn, W. B., Goodacre, R., et al. (2022). Quality assurance and quality control reporting in untargeted metabolic phenotyping: MQACC recommendations for analytical quality management. Metabolomics, 18(9), 70. https:\/\/doi.org\/10.1007\/s11306-022-01926-3","journal-title":"Metabolomics"},{"issue":"4","key":"2538_CR25","doi-asserted-by":"publisher","first-page":"135","DOI":"10.3390\/metabo10040135","volume":"10","author":"A Kl\u00e5vus","year":"2020","unstructured":"Kl\u00e5vus, A., Kokla, M., Noerman, S., Koistinen, V. M., Tuomainen, M., Zarei, I., et al. (2020). Notame: Workflow for Non-Targeted LC\u2013MS Metabolic Profiling. Metabolites, 10(4), 135. https:\/\/doi.org\/10.3390\/metabo10040135","journal-title":"Metabolites"},{"key":"2538_CR26","unstructured":"Knuth, D. E. (1992). Literate programming. Stanford."},{"issue":"1","key":"2538_CR27","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1186\/s12859-019-3110-0","volume":"20","author":"M Kokla","year":"2019","unstructured":"Kokla, M., Virtanen, J., Kolehmainen, M., Paananen, J., & Hanhineva, K. (2019). Random forest-based imputation outperforms other methods for imputing LC-MS metabolomics data: A comparative study. Bmc Bioinformatics, 20(1), 492. https:\/\/doi.org\/10.1186\/s12859-019-3110-0","journal-title":"Bmc Bioinformatics"},{"issue":"50","key":"2538_CR28","doi-asserted-by":"publisher","first-page":"27639","DOI":"10.1021\/acs.analchem.5c04338","volume":"97","author":"P Louail","year":"2025","unstructured":"Louail, P., Brunius, C., Garcia-Aloy, M., Kumler, W., Storz, N., Stanstrup, J., et al. (2025). xcms in Peak Form: Now Anchoring a Complete Metabolomics Data Preprocessing and Analysis Software Ecosystem. Analytical Chemistry, 97(50), 27639\u201327645. https:\/\/doi.org\/10.1021\/acs.analchem.5c04338","journal-title":"Analytical Chemistry"},{"key":"2538_CR29","doi-asserted-by":"publisher","unstructured":"Louail, P., Gatto, L., Gibb, S., & Rainer, J. (2026). Chromatograms: A modular infrastructure for scalable chromatographic data handling in R. Anal. Chem. . https:\/\/doi.org\/10.1021\/acs.analchem.6c03926","DOI":"10.1021\/acs.analchem.6c03926"},{"issue":"1","key":"2538_CR30","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1186\/s13059-015-0850-7","volume":"16","author":"F Markowetz","year":"2015","unstructured":"Markowetz, F. (2015). Five selfish reasons to work reproducibly. Genome Biology, 16(1), 274. https:\/\/doi.org\/10.1186\/s13059-015-0850-7","journal-title":"Genome Biology"},{"key":"2538_CR31","doi-asserted-by":"publisher","DOI":"10.18129\/B9.BIOC.SUMMARIZEDEXPERIMENT","author":"VO Martin Morgan","year":"2017","unstructured":"Martin Morgan, V. O. (2017). SummarizedExperiment. Bioconductor. https:\/\/doi.org\/10.18129\/B9.BIOC.SUMMARIZEDEXPERIMENT","journal-title":"Bioconductor"},{"issue":"10","key":"2538_CR32","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1007\/s11306-019-1588-0","volume":"15","author":"KM Mendez","year":"2019","unstructured":"Mendez, K. M., Pritchard, L., Reinke, S. N., & Broadhurst, D. I. (2019). Toward collaborative open data science in metabolomics using Jupyter Notebooks and cloud computing. Metabolomics, 15(10), 125. https:\/\/doi.org\/10.1007\/s11306-019-1588-0","journal-title":"Metabolomics"},{"key":"2538_CR33","doi-asserted-by":"publisher","unstructured":"Rainer, J., De Graeve, M., Louail, P., Gibb, S., & Gatto, L. (2025, October 27). An Open Infrastructure for Mass Spectrometry Data in R. Open Science Framework. https:\/\/doi.org\/10.31219\/osf.io\/cwt2v_v2","DOI":"10.31219\/osf.io\/cwt2v_v2"},{"issue":"2","key":"2538_CR34","doi-asserted-by":"publisher","first-page":"173","DOI":"10.3390\/metabo12020173","volume":"12","author":"J Rainer","year":"2022","unstructured":"Rainer, J., Vicini, A., Salzer, L., Stanstrup, J., Badia, J. M., Neumann, S., et al. (2022). A Modular and Expandable Ecosystem for Metabolomics Data Annotation in R. Metabolites, 12(2), 173. https:\/\/doi.org\/10.3390\/metabo12020173","journal-title":"Metabolites"},{"issue":"7","key":"2538_CR35","doi-asserted-by":"publisher","first-page":"e47","DOI":"10.1093\/nar\/gkv007","volume":"43","author":"ME Ritchie","year":"2015","unstructured":"Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research, 43(7), e47. https:\/\/doi.org\/10.1093\/nar\/gkv007","journal-title":"Nucleic Acids Research"},{"issue":"10","key":"2538_CR36","doi-asserted-by":"publisher","first-page":"e1003285","DOI":"10.1371\/journal.pcbi.1003285","volume":"9","author":"GK Sandve","year":"2013","unstructured":"Sandve, G. K., Nekrutenko, A., Taylor, J., & Hovig, E. (2013). Ten Simple Rules for Reproducible Computational Research. PLoS Computational Biology, 9(10), e1003285. https:\/\/doi.org\/10.1371\/journal.pcbi.1003285","journal-title":"PLoS Computational Biology"},{"issue":"4","key":"2538_CR37","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1038\/s41587-023-01690-2","volume":"41","author":"R Schmid","year":"2023","unstructured":"Schmid, R., Heuckeroth, S., Korf, A., Smirnov, A., Myers, O., Dyrlund, T. S., et al. (2023). Integrative analysis of multimodal mass spectrometry data in MZmine 3. Nature Biotechnology, 41(4), 447\u2013449. https:\/\/doi.org\/10.1038\/s41587-023-01690-2","journal-title":"Nature Biotechnology"},{"issue":"1","key":"2538_CR38","doi-asserted-by":"publisher","first-page":"170138","DOI":"10.1038\/sdata.2017.138","volume":"4","author":"RA Spicer","year":"2017","unstructured":"Spicer, R. A., Salek, R., & Steinbeck, C. (2017). A decade after the metabolomics standards initiative it\u2019s time for a revision. Scientific Data, 4(1), 170138. https:\/\/doi.org\/10.1038\/sdata.2017.138","journal-title":"Scientific Data"},{"issue":"10","key":"2538_CR39","doi-asserted-by":"publisher","first-page":"200","DOI":"10.3390\/metabo9100200","volume":"9","author":"J Stanstrup","year":"2019","unstructured":"Stanstrup, J., Broeckling, C., Helmus, R., Hoffmann, N., Math\u00e9, E., Naake, T., et al. (2019). The metaRbolomics Toolbox in Bioconductor and beyond. Metabolites, 9(10), 200. https:\/\/doi.org\/10.3390\/metabo9100200","journal-title":"Metabolites"},{"issue":"7","key":"2538_CR40","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1038\/s41592-022-01486-3","volume":"19","author":"MA Stravs","year":"2022","unstructured":"Stravs, M. A., D\u00fchrkop, K., B\u00f6cker, S., & Zamboni, N. (2022). MSNovelist: De novo structure generation from mass spectra. Nature Methods, 19(7), 865\u2013870. https:\/\/doi.org\/10.1038\/s41592-022-01486-3","journal-title":"Nature Methods"},{"issue":"D1","key":"2538_CR41","doi-asserted-by":"publisher","first-page":"D463","DOI":"10.1093\/nar\/gkv1042","volume":"44","author":"M Sud","year":"2016","unstructured":"Sud, M., Fahy, E., Cotter, D., Azam, K., Vadivelu, I., Burant, C., et al. (2016). Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic acids research, 44(D1), D463\u2013D470. https:\/\/doi.org\/10.1093\/nar\/gkv1042","journal-title":"Nucleic acids research"},{"issue":"3","key":"2538_CR42","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11306-007-0082-2","volume":"3","author":"LW Sumner","year":"2007","unstructured":"Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., et al. (2007). Proposed minimum reporting standards for chemical analysis: Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI). Metabolomics, 3(3), 211\u2013221. https:\/\/doi.org\/10.1007\/s11306-007-0082-2","journal-title":"Metabolomics"},{"issue":"8","key":"2538_CR43","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1038\/nbt.3597","volume":"34","author":"M Wang","year":"2016","unstructured":"Wang, M., Carver, J. J., Phelan, V. V., Sanchez, L. M., Garg, N., Peng, Y., et al. (2016). Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nature Biotechnology, 34(8), 828\u2013837. https:\/\/doi.org\/10.1038\/nbt.3597","journal-title":"Nature Biotechnology"},{"key":"2538_CR44","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.18","author":"MD Wilkinson","year":"2016","unstructured":"Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., et al. (2016). The FAIR guiding principles for scientific data management and stewardship. Scientific Data, https:\/\/doi.org\/10.1038\/sdata.2016.18","journal-title":"Scientific Data"},{"issue":"D1","key":"2538_CR45","doi-asserted-by":"publisher","first-page":"D622","DOI":"10.1093\/nar\/gkab1062","volume":"50","author":"DS Wishart","year":"2022","unstructured":"Wishart, D. S., Guo, A., Oler, E., Wang, F., Anjum, A., Peters, H., et al. (2022). HMDB 5.0: The Human Metabolome Database for 2022. Nucleic Acids Research, 50(D1), D622\u2013D631. https:\/\/doi.org\/10.1093\/nar\/gkab1062","journal-title":"Nucleic Acids Research"},{"issue":"D1","key":"2538_CR46","doi-asserted-by":"publisher","first-page":"D640","DOI":"10.1093\/nar\/gkad1045","volume":"52","author":"O Yurekten","year":"2024","unstructured":"Yurekten, O., Payne, T., Tejera, N., Amaladoss, F. X., Martin, C., Williams, M., & O\u2019Donovan, C. (2024). MetaboLights: Open data repository for metabolomics. Nucleic Acids Research, 52(D1), D640\u2013D646. https:\/\/doi.org\/10.1093\/nar\/gkad1045","journal-title":"Nucleic Acids Research"}],"container-title":["Metabolomics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11306-026-02538-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11306-026-02538-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11306-026-02538-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T17:32:04Z","timestamp":1791826324000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11306-026-02538-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,3]]},"references-count":46,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2026,10]]}},"alternative-id":["2538"],"URL":"https:\/\/doi.org\/10.1007\/s11306-026-02538-x","relation":{},"ISSN":["1573-3890"],"issn-type":[{"value":"1573-3890","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,3]]},"assertion":[{"value":"28 July 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 September 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This article does not contain any studies with human and\/or animal participants performed by any of the authors.","order":2,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"165"}}