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Mastodon: the Command Center for Large-Scale Lineage-Tracing Microscopy Datasets

Girstmair, J.; Pietzsch, T.; Ulman, V.; Hahmann, S.; Arzt, M.; Handberg-Thorsager, M.; Sugawara, K.; Pantze, S.; Haase, R.; Tinevez, J.-Y.; Tomancak, P.

2025-12-12 bioinformatics
10.64898/2025.12.10.693416 bioRxiv
Show abstract

Understanding development in living organisms requires following the divisions, movements, and fates of cells across developing systems. While advances in microscopy have enabled whole-embryo imaging at the cellular level, extracting and analyzing cell lineages from these massive datasets remains a significant computational challenge. We present Mastodon, a scalable, extensible software platform for manual, semi-automated, and automated cell tracking in large images. A purpose-built graph model supports responsive performance for datasets with millions of annotations, making Mastodon a future-proof platform for cell lineage analysis. Built as a Fiji plugin, Mastodon enables interactive visualization, editing, and analysis of complex lineage trees, seamlessly integrated with the raw image data. Comprehension of cell lineages in complex three-dimensional geometries is facilitated by interoperability with the powerful open-source render engine Blender. In three distinct developmental contexts, we demonstrate how Mastodon will accelerate biological insights by providing user-friendly navigation and explorative analysis in complex lineage datasets.

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