Vitessce: integrative visualization of multimodal and spatially resolved single-cell data

被引:0
|
作者
Keller, Mark S. [1 ]
Gold, Ilan [1 ]
McCallum, Chuck [1 ]
Manz, Trevor [1 ]
Kharchenko, Peter V. [1 ,2 ,3 ]
Gehlenborg, Nils [1 ]
机构
[1] Harvard Med Sch, Dept Biomed Informat, Boston, MA 02115 USA
[2] Broad Inst MIT & Harvard, Cambridge, MA USA
[3] Altos Labs, San Diego, CA USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
GENOME-WIDE EXPRESSION;
D O I
10.1038/s41592-024-02436-x
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Multiomics technologies with single-cell and spatial resolution make it possible to measure thousands of features across millions of cells. However, visual analysis of high-dimensional transcriptomic, proteomic, genome-mapped and imaging data types simultaneously remains a challenge. Here we describe Vitessce, an interactive web-based visualization framework for exploration of multimodal and spatially resolved single-cell data. We demonstrate integrative visualization of millions of data points, including cell-type annotations, gene expression quantities, spatially resolved transcripts and cell segmentations, across multiple coordinated views. The open-source software is available at http://vitessce.io. Vitessce is a robust and versatile web-based framework for interactive visualization of large-scale multiomics and spatial data at the single-cell level.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Annotation of spatially resolved single-cell data with STELLAR
    Brbic, Maria
    Cao, Kaidi
    Hickey, John W.
    Tan, Yuqi
    Snyder, Michael P.
    Nolan, Garry P.
    Leskovec, Jure
    [J]. NATURE METHODS, 2022, 19 (11) : 1411 - +
  • [2] Annotation of spatially resolved single-cell data with STELLAR
    Maria Brbić
    Kaidi Cao
    John W. Hickey
    Yuqi Tan
    Michael P. Snyder
    Garry P. Nolan
    Jure Leskovec
    [J]. Nature Methods, 2022, 19 : 1411 - 1418
  • [3] Cobolt: integrative analysis of multimodal single-cell sequencing data
    Gong, Boying
    Zhou, Yun
    Purdom, Elizabeth
    [J]. GENOME BIOLOGY, 2021, 22 (01)
  • [4] Cobolt: integrative analysis of multimodal single-cell sequencing data
    Boying Gong
    Yun Zhou
    Elizabeth Purdom
    [J]. Genome Biology, 22
  • [5] scJVAE: A novel method for integrative analysis of multimodal single-cell data
    Wani, Shahid Ahmad
    Khan, Sumeer Ahmad
    Quadri, S. M. K.
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 158
  • [6] Editorial: Multimodal and Integrative Analysis of Single-Cell or Bulk Sequencing Data
    Chen, Geng
    [J]. FRONTIERS IN GENETICS, 2021, 12
  • [7] Multimodal approach to capture spatially resolved single-cell tumor heterogeneity in breast cancer.
    Cook, Daniel
    Lopez, Dorys
    Antony, Anu K.
    Cole, John A.
    [J]. JOURNAL OF CLINICAL ONCOLOGY, 2022, 40 (16)
  • [8] A single-cell and spatially resolved atlas of human osteosarcomas
    Zheng, Xuejing
    Liu, Xu
    Zhang, Xinxin
    Zhao, Zhenguo
    Wu, Wence
    Yu, Shengji
    [J]. JOURNAL OF HEMATOLOGY & ONCOLOGY, 2024, 17 (01)
  • [9] Single-cell and spatially resolved transcriptomics for liver biology
    Lin, Ping
    Yan, Xi
    Jing, Siyu
    Wu, Yanhong
    Shan, Yiran
    Guo, Wenbo
    Gu, Jin
    Li, Yu
    Zhang, Haibing
    Li, Hong
    [J]. HEPATOLOGY, 2024, 80 (03) : 698 - 720
  • [10] Nanoscale tweezers for spatially resolved single-cell analysis
    Sahota, Annie
    Devine, Michael
    Ivanov, Aleksandar
    Edel, Joshua
    [J]. BIOPHYSICAL JOURNAL, 2023, 122 (03) : 552A - 552A