SC-Framework: A robust and FAIR semi-interactive environment for single-cell resolution datasets

Schultheis, H.; Detleffsen, J.; Wiegandt, R.; Bentsen, M.; Alayoubi, Y.; Valente, G.; Kessler, M. F.; Bruns, B.; Mirza, D.; Usanayo, A.; Walter, J.; Goymann, P.; Hobein, M.; Kuenne, C.; Looso, M.

doi:10.1101/2025.11.11.687874

bioRxiv · 10.1101/2025.11.11.687874

SC-Framework: A robust and FAIR semi-interactive environment for single-cell resolution datasets

Schultheis, H.·Detleffsen, J.·Wiegandt, R.·Bentsen, M.·Alayoubi, Y.·Valente, G.·Kessler, M. F.·Bruns, B.·Mirza, D.·Usanayo, A.·Walter, J.·Goymann, P.·Hobein, M.·Kuenne, C.·Looso, M.

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Abstract

The accelerated development of single-cell technologies has profoundly impacted the field of biological research, facilitating unparalleled insights into cellular heterogeneity. However, this progress has also produced new computational challenges in the field of bioinformatics: single-cell datasets are increasingly high-dimensional, multimodal, and large-scale, while analysis workflows often remain fragmented, data type specific, ad hoc, and difficult to reproduce. The prevailing methodologies are dependent on a combination of public tools, which hinders the reproducibility of results, limits scalability, and complicates the efforts to establish benchmarks. The necessity for a higher-level, unified framework for single-cell data analysis is paramount to address these inherent limitations. Here, we introduce the SC-Framework, providing the integration of standardized data structures, declarative workflows and standardized computational backends in a containerized environment, enabling analysts to focus on biological interpretation rather than technical overhead. SC-Framework is available at GitHub (https://github.com/loosolab/SC-Framework).

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Schultheis, H., Detleffsen, J., Wiegandt, R., Bentsen, M., Alayoubi, Y., Valente, G., Kessler, M. F., Bruns, B., Mirza, D., Usanayo, A., Walter, J., Goymann, P., Hobein, M., Kuenne, C., Looso, M.. 2025-11-13. SC-Framework: A robust and FAIR semi-interactive environment for single-cell resolution datasets. https://doi.org/10.1101/2025.11.11.687874

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