From Abandoned Scripts to FAIR Community Pipelines: Rescuing Orphan Bioinformatics Workflows with nf-core - Lessons from Light-Sheet Fluorescence Microscopy
Abstract Background Research software is essential for modern data analysis but is often developed and maintained by a small number of researchers. When developers leave, software may become orphaned, limiting reuse and risking the loss of valuable domain knowledge and computational methods. While the FAIR Principles for Research Software (FAIR4RS) provide an essential foundation for improving…
The research software landscape is fraught with challenges, chief among them being the development, maintenance, and eventual abandonment of software tools by a select few researchers. This leaves valuable domain knowledge and computational methods at risk of being lost. The FAIR Principles for Research Software (FAIR4RS) offer a foundation for enhancing software reuse, yet mere compliance falls short of ensuring practical reusability.
In this study, the authors addressed the issue of orphaned scientific software by taking the abandoned MATLAB-based NuMorph toolkit, originally designed for large-scale light-sheet microscopy image analysis, and transforming it into nf-core/lsmquant, a Nextflow-based workflow. This re-engineering process adhered to nf-core community guidelines, preserving the original scientific methods while improving the software's FAIRness, portability, and reproducibility.
The resulting nf-core/lsmquant workflow not only retained the original methods but did so at a comparable computational cost. Importantly, its integration into the nf-core ecosystem provided a community-driven framework for sustaining the software through distributed maintenance and shared development practices. Additionally, the modular workflow architecture facilitated easy adaptation of nf-core/lsmquant to additional light-sheet microscopy datasets, extending its utility beyond its original application.
This case study demonstrates that orphaned scientific software can be effectively rescued through systematic re-engineering, guided by FAIR and software sustainability principles. By converting a legacy codebase into a community-maintained workflow, the study preserves valuable domain-specific methods, enhances usability, maintainability, and reproducibility, and illustrates a practical strategy for integrating orphan research software into modern, reusable research ecosystems.
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