{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T00:14:03Z","timestamp":1789172043948,"version":"build-2803163510"},"reference-count":22,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T00:00:00Z","timestamp":1788134400000},"content-version":"vor","delay-in-days":242,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institutes of Health\/the National Institute on Aging","award":["1RF1AG057452"],"award-info":[{"award-number":["1RF1AG057452"]}]},{"name":"National Institutes of Health\/the National Institute on Aging","award":["R01AG069901"],"award-info":[{"award-number":["R01AG069901"]}]},{"name":"National Institutes of Health\/the National Institute on Aging","award":["U01AG061359"],"award-info":[{"award-number":["U01AG061359"]}]},{"name":"National Institutes of Health\/the National Institute on Aging","award":["R01AG081322"],"award-info":[{"award-number":["R01AG081322"]}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>MeTime is an opensource R package for reproducible analysis of longitudinal metabolomics data. It builds upon a central S4 container, metime_analyser, that stores multiple datasets, associated metadata and analysis outputs, enabling unified handling of complex longitudinal studies. Analyses are constructed by piping modular functions, beginning with data transformations (mod_*), followed by calculations (calc_*), and optional meta-analysis (meta_*), so entire workflows remain transparent and easy to modify. MeTime wraps numerous existing methods within a consistent interface, including sample and metabolite distributions, correlation\/distance matrices, dimensionality reduction (PCA, UMAP, t-SNE), random forest imputation and feature selection via Boruta, eigenmetabolites and WGCNA-based clustering, conservation index analysis, regression models (linear, mixed-effects, and generalized additive), and partial-correlation networks. By retaining all intermediate results and provenance within the container, MeTime facilitates iterative exploration and ensures reproducible reporting via automatically generated HTML\/PDF outputs. Comprehensive user guides, case studies and reference documentation accompany the package, making MeTime a versatile platform for longitudinal omics workflows.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>MeTime is available as an open-source R package and can be installed directly from GitHub (https:\/\/github.com\/compneurobio\/MeTime). Source code, installation instructions, documentation, tutorials, and reproducible case-study workflows are provided within the repository. MeTime has been tested on Microsoft Windows, Unix\/Linux, and macOS. For users requiring a containerized environment, a Docker implementation is additionally provided through the GitHub Container Registry.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioadv\/vbag252","type":"journal-article","created":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T12:27:44Z","timestamp":1788179264000},"source":"Crossref","is-referenced-by-count":0,"title":["MeTime: an R package for reproducible longitudinal metabolomics data analysis"],"prefix":"10.1093","volume":"6","author":[{"given":"Bharadwaj","family":"Marella","sequence":"first","affiliation":[{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, German Research Center for Environmental Health , Neuherberg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick","family":"Weinisch","sequence":"additional","affiliation":[{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, German Research Center for Environmental Health , Neuherberg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lara","family":"Vehovec","sequence":"additional","affiliation":[{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, German Research Center for Environmental Health , Neuherberg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vinh","family":"Tran","sequence":"additional","affiliation":[{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, German Research Center for Environmental Health , Neuherberg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Josef J","family":"Bless","sequence":"additional","affiliation":[{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, German Research Center for Environmental Health , Neuherberg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yacoub A","family":"Njipouombe Nsangou","sequence":"additional","affiliation":[{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, German Research Center for Environmental Health , Neuherberg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabi","family":"Kastenm\u00fcller","sequence":"additional","affiliation":[{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, German Research Center for Environmental Health , Neuherberg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4666-0923","authenticated-orcid":false,"given":"Matthias","family":"Arnold","sequence":"additional","affiliation":[{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, German Research Center for Environmental Health , Neuherberg,","place":["Germany"]},{"name":"Department of Psychiatry and Behavioral Sciences, Duke University , Durham, NC,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,8,31]]},"reference":[{"key":"2026091119515606800_vbag252-B1","author":"Allaire","year":"2023"},{"key":"2026091119515606800_vbag252-B2","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1038\/s41467-020-14959-w","article-title":"Sex and APOE \u03b54 genotype modify the Alzheimer\u2019s disease serum metabolome","volume":"11","author":"Arnold","year":"2020","journal-title":"Nat Commun"},{"key":"2026091119515606800_vbag252-B3","author":"Bache","year":"2022"},{"key":"2026091119515606800_vbag252-B4","doi-asserted-by":"publisher","DOI":"10.1038\/nature.2016.20504","article-title":"Why scientists must share their research code","author":"Baker","year":"2016","journal-title":"Nature"},{"key":"2026091119515606800_vbag252-B5","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1007\/s00216-021-03586-z","article-title":"Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests","volume":"414","author":"Castelli","year":"2022","journal-title":"Anal Bioanal Chem"},{"key":"2026091119515606800_vbag252-B6","doi-asserted-by":"crossref","first-page":"1168","DOI":"10.1093\/bioinformatics\/btab741","article-title":"maplet: an extensible R toolbox for modular and reproducible metabolomics pipelines","volume":"38","author":"Chetnik","year":"2022","journal-title":"Bioinformatics"},{"key":"2026091119515606800_vbag252-B7","doi-asserted-by":"crossref","first-page":"W486","DOI":"10.1093\/nar\/gky310","article-title":"MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis","volume":"46","author":"Chong","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"2026091119515606800_vbag252-B8","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s11306-017-1299-3","article-title":"Critical review of reporting of the data analysis step in metabolomics","volume":"14","author":"Considine","year":"2017","journal-title":"Metabolomics"},{"key":"2026091119515606800_vbag252-B9","doi-asserted-by":"crossref","first-page":"87","DOI":"10.3390\/metabo12010087","article-title":"A checklist for reproducible computational analysis in clinical metabolomics research","volume":"12","author":"Du","year":"2022","journal-title":"Metabolites"},{"key":"2026091119515606800_vbag252-B10","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1080\/00273171.2018.1454823","article-title":"The Gaussian graphical model in cross-sectional and time-series data","volume":"53","author":"Epskamp","year":"2018","journal-title":"Multivariate Behav Res"},{"key":"2026091119515606800_vbag252-B12","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1146\/annurev.clinpsy.032408.153550","article-title":"Advances in analysis of longitudinal data","volume":"6","author":"Gibbons","year":"2010","journal-title":"Annu Rev Clin Psychol"},{"key":"2026091119515606800_vbag252-B13","doi-asserted-by":"crossref","first-page":"vbae178","DOI":"10.1093\/bioadv\/vbae178","article-title":"MeTEor: an R shiny app for exploring longitudinal metabolomics data","volume":"4","author":"Grabert","year":"2024","journal-title":"Bioinform Adv"},{"key":"2026091119515606800_vbag252-B14","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1186\/1752-0509-5-21","article-title":"Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data","volume":"5","author":"Krumsiek","year":"2011","journal-title":"BMC Syst Biol"},{"key":"2026091119515606800_vbag252-B15","doi-asserted-by":"crossref","first-page":"9810","DOI":"10.1038\/s41598-018-27958-1","article-title":"Instability of personal human metabotype is linked to all-cause mortality","volume":"8","author":"Lacruz","year":"2018","journal-title":"Sci Rep"},{"key":"2026091119515606800_vbag252-B16","author":"Marella","year":"2025"},{"key":"2026091119515606800_vbag252-B18","doi-asserted-by":"publisher","author":"Morgan","year":"2023","DOI":"10.18129\/B9.bioc.SummarizedExperiment"},{"key":"2026091119515606800_vbag252-B19","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1007\/s11306-018-1335-y","article-title":"From correlation to causation: analysis of metabolomics data using systems biology approaches","volume":"14","author":"Rosato","year":"2018","journal-title":"Metabolomics"},{"key":"2026091119515606800_vbag252-B20","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.molp.2022.09.007","article-title":"Metabolomics-centered mining of plant metabolic diversity and function: past decade and future perspectives","volume":"16","author":"Shen","year":"2023","journal-title":"Mol Plant"},{"key":"2026091119515606800_vbag252-B22","doi-asserted-by":"crossref","first-page":"67","DOI":"10.3390\/metabo13010067","article-title":"Current state and future perspectives on personalized metabolomics","volume":"13","author":"Trifonova","year":"2023","journal-title":"Metabolites"},{"key":"2026091119515606800_vbag252-B23","doi-asserted-by":"crossref","first-page":"114416","DOI":"10.1016\/j.celrep.2024.114416","article-title":"The HuMet Repository: watching human metabolism at work","volume":"43","author":"Weinisch","year":"2024","journal-title":"Cell Rep"},{"key":"2026091119515606800_vbag252-B24","doi-asserted-by":"crossref","first-page":"D622","DOI":"10.1093\/nar\/gkab1062","article-title":"HMDB 5.0: the human metabolome database for 2022","volume":"50","author":"Wishart","year":"2022","journal-title":"Nucleic Acids Res"},{"key":"2026091119515606800_vbag252-B25","doi-asserted-by":"crossref","first-page":"1005","DOI":"10.1007\/s11306-014-0629-y","article-title":"Long term conservation of human metabolic phenotypes and link to heritability","volume":"10","author":"Yousri","year":"2014","journal-title":"Metabolomics"}],"container-title":["Bioinformatics Advances"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformaticsadvances\/advance-article-pdf\/doi\/10.1093\/bioadv\/vbag252\/70881629\/vbag252.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformaticsadvances\/article-pdf\/6\/1\/vbag252\/70881629\/vbag252.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformaticsadvances\/article-pdf\/6\/1\/vbag252\/70881629\/vbag252.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T23:52:08Z","timestamp":1789170728000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformaticsadvances\/article\/doi\/10.1093\/bioadv\/vbag252\/8776621"}},"subtitle":[],"editor":[{"given":"Reema","family":"Singh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":22,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1,7]]}},"URL":"https:\/\/doi.org\/10.1093\/bioadv\/vbag252","relation":{},"ISSN":["2635-0041"],"issn-type":[{"value":"2635-0041","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026]]},"published":{"date-parts":[[2026]]},"article-number":"vbag252"}}