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

Area of Science:

• Bioinformatics
• Ecology
• Remote Sensing
• Data-intensive scientific research

Background:

• Standardization, accessibility, and reproducibility are key challenges in data-intensive research.
• The Galaxy platform offers a web-based solution for computational workflows.
• Programmatic access to Galaxy has primarily been through Python's BioBlend.

Purpose of the Study:

• To introduce GalaxyR, a native R package for interfacing with the Galaxy platform.
• To enable R users to leverage Galaxy's computational infrastructure for automated and reproducible research.

Main Methods:

• GalaxyR provides a structured interface to the Galaxy API within the R environment.
• It supports managing histories, data transfer (HTTPS/FTP), job execution, and result inspection.
• The package facilitates programmatic workflow orchestration across Galaxy instances.

Main Results:

• Demonstrated large-scale processing of drone-based laser scanning data using GalaxyR.
• Computationally intensive tree-level segmentation was delegated to Galaxy, with R handling control and preprocessing.
• Workflow automation was achieved with minimal R code.

Conclusions:

• GalaxyR bridges a gap for R users, enhancing access to Galaxy-based analyses.
• It promotes scalable and reproducible research in bioinformatics, ecology, remote sensing, and other data-driven fields.
• Facilitates resource-efficient workflows without requiring local high-performance computing.