1. Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data
- Author
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Yinan Wan, Daniel P. Mossing, William C. Lemon, Kristin Branson, Fernando Amat, Eugene W. Myers, Katie McDole, and Philipp J. Keller
- Subjects
Image processing ,Computational biology ,Biochemistry ,Sensitivity and Specificity ,Mice ,User-Computer Interface ,Neuroblast ,Image Interpretation, Computer-Assisted ,Animals ,Data Mining ,Segmentation ,Cell Lineage ,Molecular Biology ,Cells, Cultured ,Zebrafish ,biology ,Data curation ,Stem Cells ,Reproducibility of Results ,Cell Biology ,biology.organism_classification ,Visualization ,Multicellular organism ,Microscopy, Fluorescence ,Cell Tracking ,Drosophila ,Drosophila melanogaster ,Developmental biology ,Software ,Biotechnology - Abstract
The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for the segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (i) generality by reconstructing cell lineages in four-dimensional, terabyte-sized image data sets of fruit fly, zebrafish and mouse embryos acquired with three types of fluorescence microscopes, (ii) scalability by analyzing advanced stages of development with up to 20,000 cells per time point at 26,000 cells min(-1) on a single computer workstation and (iii) ease of use by adjusting only two parameters across all data sets and providing visualization and editing tools for efficient data curation. Our approach achieves on average 97.0% linkage accuracy across all species and imaging modalities. Using our system, we performed the first cell lineage reconstruction of early Drosophila melanogaster nervous system development, revealing neuroblast dynamics throughout an entire embryo.
- Published
- 2014