MeTime: an R package for reproducible longitudinal metabolomics data analysis

Abstract

Abstract Summary 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. Availability and implementation 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.