A semi-automated pipeline for morphological analysis of myonuclei along single muscle fibers

Manual quantitation of skeletal muscle myonuclear number, spatial orientation, and morphology is time consuming and subject to error and bias. To overcome these limitations, we developed and validated a semi-automated, quantitative, and reproducible image analysis pipeline. The workflow combines FIJI-based preprocessing with custom Python scripts to process immunohistological images of individual muscle fibers, enabling high resolution and scalable quantification of nuclei. Analyses incorporate morphometric parameters including nuclear position, shape, and three dimensional orientation, as well as centroid to skeleton distance and nearest neighbor relationships to capture spatial patterns of myonuclear organization along the fiber. Outputs include per fiber and biopsy level summaries integrated with Imaris metrics. This semi-automated approach provides a robust and efficient platform for high throughput analysis of myonuclear number and structural features across large single fiber data..., , # Example Input Data for A semi-automated pipeline for morphological analysis of myonuclei along single muscle fibers

[https://doi.org/10.5061/dryad.ht76hdrwn](https://doi.org/10.5061/dryad.ht76hdrwn)

**Date of Data Collection**: 2025-12-01

**Related Repository**: [https://doi.org/10.5281/zenodo.18395537](https://doi.org/10.5281/zenodo.18395537)

## Contributors

* **Esben Schroeder†**: Department of Human Physiology, University of Oregon, Eugene, OR 97403
* **Helia G. Megowan†**: Department of Human Physiology, University of Oregon, Eugene, OR 97403
* **Madeline Luu†**: Department of Computer Science & Department of Data Science, University of Oregon, Eugene, OR 97403
* **Adam Shuaib**: Department of Neuroscience, University of Oregon, Eugene, OR 97403
* **Adam Fries**: Genomics & Cell Characterization Core Facility, University of Oregon, Eugene, OR 97403
* **Jake Searcy**: Department of Data Science, University of Oregon, Eugene, OR 97403
* **Hans C. Dreyer** (Corresponding Author)..., Our research group received explicit consent from participants to publish de-identified data publicly. This dataset has been de-identified in accordance with HIPAA standards by removing all 18 direct identifiers and specific quasi-identifiers, ensuring no reasonable basis exists to re-identify any individual.