Introducing GalaxyR: an easy-to-use R implementation of the Galaxy API.

BACKGROUND: Standardisation, accessibility, and reproducibility remain persistent challenges in data‑intensive scientific research. The Galaxy platform addresses these issues by providing a web-based environment for executing, sharing, and publishing computational workflows, yet programmatic access has been largely centred on the Python ecosystem through BioBlend. METHODS: Here, we introduce GalaxyR, a native R package that provides a comprehensive and structured interface to the Galaxy application programming interface. GalaxyR enables users to manage histories, upload and retrieve data, execute tools and workflows, monitor jobs, and inspect results directly from within the R environment. By integrating Galaxy's scalable computational infrastructure with R's widely adopted data analysis ecosystem, GalaxyR facilitates automated, reproducible, and resource‑efficient workflows without requiring local high‑performance computing resources. The package supports both HTTPS‑ and FTP‑based data transfer, robust history and dataset management, and programmatic workflow orchestration across Galaxy instances. RESULTS: An application example demonstrates the use of GalaxyR for large-scale processing of drone-based laser scanning data, where computationally intensive tree‑level segmentation was delegated to the Galaxy infrastructure, while workflow control and preprocessing were handled in R within a few lines of code. CONCLUSIONS: GalaxyR thus bridges a critical gap for R users, significantly expanding access to Galaxy‑based analyses and enabling scalable, reproducible research across bioinformatics, ecology, remote sensing, and related data-driven disciplines.