Mastodon: the command center for large-scale lineage-tracing microscopy datasets
Understanding development in living organisms requires following the divisions, movements, and fates of cells. 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 scalable 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.
Authors
- Mette Handberg-Thorsager (ORCID: https://orcid.org/0000-0002-3908-7233)
- Matthias Arzt
- Shuichi Onami (ORCID: https://orcid.org/0000-0002-8255-1724)
- Johannes Girstmair (ORCID: https://orcid.org/0000-0001-9029-3625)
- Pavel Tomančák (ORCID: https://orcid.org/0000-0002-2222-9370)
- Vladimír Ulman (ORCID: https://orcid.org/0000-0002-4270-7982)
- Robert Haase (ORCID: https://orcid.org/0000-0001-5949-2327)
- Jean-Yves Tinévez (ORCID: https://orcid.org/0000-0002-0998-4718)
- Stefan Hahmann (ORCID: https://orcid.org/0000-0002-8145-7090)
- Tobias Pietzsch (ORCID: https://orcid.org/0000-0002-9477-3957)
- Ko Sugawara (ORCID: https://orcid.org/0000-0002-1392-9340)
- Samuel Pantze (ORCID: https://orcid.org/0009-0000-1388-8959)
Institutions
- Central European Institute of Technology (CZ)
- VSB - Technical University of Ostrava (CZ)
- Institut Pasteur (FR)
- Université Paris Cité (FR)
- Central European Institute of Technology – Masaryk University (CZ)
- RIKEN Center for Biosystems Dynamics Research (JP)
- Center for Advanced Systems Understanding (DE)
- Center for Systems Biology Dresden (DE)
- Max Planck Institute of Molecular Cell Biology and Genetics (DE)
- University of Göttingen (DE)
- Technische Universität Dresden (DE)
Publication Details
- Journal
- Development
- Published
- 2026-10-07
- DOI
- https://doi.org/10.1242/dev.205569
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00