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bioRxiv · 10.1101/2025.11.26.690896

LorMe: a streamlined and interoperable R framework for end-to-end microbiome analysis

Wang, N.·Zhang, Y.·Yang, X.·Gao, Y.·Xia, H.·Xu, Y.·Shen, Q.·Jousset, A.·Jiang, G.·Wei, Z.
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Abstract

Microbiome research is rapidly evolving accompanied by increasingly diverse analytical strategies and visualization formats. However, existing R-based tools remain fragmented, differ in data structures, and often require extensive package-specific pre-processing. This increases command-line complexity and limits both interoperability and reproducibility across packages. Here, we present LorMe (Lightweight One-line Resolving Microbial Ecology), an R package that provides a unified, interoperable, and user-friendly framework for microbiome data analysis. LorMe incorporates a standardized S4 object system with fully bidirectional compatibility with phyloseq and microeco, which enables seamless data exchange across major microbial analysis packages. A global configuration system ensures consistent parameter control and visualization standards, and a modular architecture supports both complete end-to-end workflows and flexible execution of individual analytical components. Based on these, LorMe further offers an one-command pipeline that conducts the full spectrum of microbial community analyses, including alpha and beta diversity, differential abundance testing, co-occurrence network inference, and meta-network construction, while archiving all intermediate objects and source data to ensure complete reproducibility. Demonstrations using sample datasets show that LorMe performs comprehensive analyses within minute, produces publication-ready outputs, and maintains methodological transparency. Application to a real rhizosphere dataset revealed biologically coherent patterns across diversity metrics, differential taxa, and network modules, highlighting the capacity of LorMe to support robust ecological interpretation. Collectively, LorMe provides a lightweight, extensible, and flexible solution that reduces technical barriers and enhances reproducibility in microbiome research. LorMe package is freely accessible from both CRAN (https://cran.r-project.org/web/packages/LorMe) and github (https://github.com/wangnq111/LorMe)

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Wang, N., Zhang, Y., Yang, X., Gao, Y., Xia, H., Xu, Y., Shen, Q., Jousset, A., Jiang, G., Wei, Z.. 2025-11-29. LorMe: a streamlined and interoperable R framework for end-to-end microbiome analysis. https://doi.org/10.1101/2025.11.26.690896

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