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

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 .

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Publication Details

Journal
Nature Methods
Published
2024-09-27
DOI
https://doi.org/10.1038/s41592-024-02436-x
Citations
52
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
10.99

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article

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

Peter V. Kharchenko, Trevor Manz, Nils Gehlenborg, Chuck McCallum et al.
52 citations
Nature Methods
Single-cell and spatial transcriptomics
10.99
article

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

Peter V. Kharchenko, Trevor Manz, Nils Gehlenborg, Chuck McCallum, Mark S. Keller, Ilan Gold
article en
52 citations

Abstract

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 .

Nature MethodsVol. 22(1)
Broad Institute (US), Harvard University (US), Altos Labs
National Science Foundation, National Institutes of Health, Harvard Stem Cell Institute, Division of Chemical, Bioengineering, Environmental, and Transport Systems
Openalex Percentile: Top 1%
Single-cell and spatial transcriptomics
10.99
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Vitessce: integrative visualization of multimodal and spatially resolved single-cell data — Peter V. Kharchenko, Trevor Manz, et al. · Nature Methods (2024) | TGRS Research Map | TGRS