MeTime: An R package for reproducible longitudinal metabolomics data analysis

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ID: 327087
2026
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Abstract
Abstract 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.
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openalex_W7160895797 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Bharadwaj Marella, Patrick Weinisch, Lara Vehovec, Vinh Tran, Josef J. Bless, Yacoub A. Njipouombe Nsangou, Gabi Kastenmueller, Matthias Arnold
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Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag252
URL
https://academic.oup.com/bioinformaticsadvances/advance-article-pdf/doi/10.1093/bioadv/vbag252/70881629/vbag252.pdf
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