Automated time-lapse data segmentation reveals in vivo cell state dynamics.
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ABSTRACT:
SUBMITTER: Genuth MA
PROVIDER: S-EPMC10413672 | biostudies-literature | 2023 Jun
REPOSITORIES: biostudies-literature
Publications
Automated time-lapse data segmentation reveals in vivo cell state dynamics.
Genuth Miriam A MA Kojima Yasuhiro Y Jülich Dörthe D Kiryu Hisanori H Holley Scott A SA
Science advances 20230602 22
Embryonic development proceeds as a series of orderly cell state transitions built upon noisy molecular processes. We defined gene expression and cell motion states using single-cell RNA sequencing data and in vivo time-lapse cell tracking data of the zebrafish tailbud. We performed a parallel identification of these states using dimensional reduction methods and a change point detection algorithm. Both types of cell states were quantitatively mapped onto embryos, and we used the cell motion sta ...[more]
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