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Volume 50 Issue 9
Sep.  2023
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Article Navigation >  Journal of Genetics and Genomics  > 2023  >  50(9): 713-719

VT3D: a visualization toolbox for 3D transcriptomic data

doi: 10.1016/j.jgg.2023.04.001 cstr: 32370.14.j.jgg.2023.04.001
  •  

    a. College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China;

  •  

    b. BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China;

  •  

    c. BGI-Shenzhen, Shenzhen, Guangdong 518083, China;

  •  

    d. State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, Guangdong 518083, China

Funds:

We thank Dr. Li Deng, Dr. Hanbo Li, Dr. Xiaoyu Wei, Chao Liu, Chang Shi, and Junfu Guo from the BGI group for the helpful discussion. This work has been supported by the General Program (Key Program, Major Research Plan) of National Natural Science Foundation of China (No. 32170439).

  • Received Date: 2023-01-12
  • Accepted Date: 2023-04-04
  • Rev Recd Date: 2023-04-03
  • Publish Date: 2023-04-11
    Abstract
  • Data visualization empowers researchers to communicate their results that support scientific reasoning in an intuitive way. Three-dimension (3D) spatially resolved transcriptomic atlases constructed from multi-view and high-dimensional data have rapidly emerged as a powerful tool to unravel spatial gene expression patterns and cell type distribution in biological samples, revolutionizing the understanding of gene regulatory interactions and cell niches. However, limited accessible tools for data visualization impede the potential impact and application of this technology. Here we introduce VT3D, a visualization toolbox that allows users to explore 3D transcriptomic data, enabling gene expression projection to any 2D plane of interest, 2D virtual slice creation and visualization, and interactive 3D data browsing with surface model plots. In addition, it can either work on personal devices in standalone mode or be hosted as a web-based server. We apply VT3D to multiple datasets produced by the most popular techniques, including both sequencing-based approaches (Stereo-seq, spatial transcriptomics, and Slide-seq) and imaging-based approaches (MERFISH and STARMap), and successfully build a 3D atlas database that allows interactive data browsing. We demonstrate that VT3D bridges the gap between researchers and spatially resolved transcriptomics, thus accelerating related studies such as embryogenesis and organogenesis processes. The source code of VT3D is available at https://github.com/BGI-Qingdao/VT3D, and the modeled atlas database is available at http://www.bgiocean.com/vt3d_example.
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    • References(39)
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