EmbryoMiner: A new framework for interactive knowledge discovery in large-scale cell tracking data of developing embryos

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Abstract

State-of-the-art light-sheet and confocal microscopes allow recording of entire embryos in 3D and over time (3D+t) for many hours. Fluorescently labeled structures can be segmented and tracked automatically in these terabyte-scale 3D+t images, resulting in thousands of cell migration trajectories that provide detailed insights to large-scale tissue reorganization at the cellular level. Here we present EmbryoMiner, a new interactive open-source framework suitable for in-depth analyses and comparisons of entire embryos, including an extensive set of trajectory features. Starting at the whole-embryo level, the framework can be used to iteratively focus on a region of interest within the embryo, to investigate and test specific trajectory-based hypotheses and to extract quantitative features from the isolated trajectories. Thus, the new framework provides a valuable new way to quantitatively compare corresponding anatomical regions in different embryos that were manually selected based on biological prior knowledge. As a proof of concept, we analyzed 3D+t light-sheet microscopy images of zebrafish embryos, showcasing potential user applications that can be performed using the new framework.

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Schott, B., Traub, M., Schlagenhauf, C., Takamiya, M., Antritter, T., Bartschat, A., … Stegmaier, J. (2018). EmbryoMiner: A new framework for interactive knowledge discovery in large-scale cell tracking data of developing embryos. PLoS Computational Biology, 14(4). https://doi.org/10.1371/journal.pcbi.1006128

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