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.
| Reference Key |
openalex_W7160895797
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| Authors | Bharadwaj Marella, Patrick Weinisch, Lara Vehovec, Vinh Tran, Josef J. Bless, Yacoub A. Njipouombe Nsangou, Gabi Kastenmueller, Matthias Arnold |
| Journal | Bioinformatics advances |
| Year | 2026 |
| DOI |
10.1093/bioadv/vbag252
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| URL | |
| Keywords | Keywords not found |
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