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 .
Authors
- Peter V. Kharchenko (ORCID: https://orcid.org/0000-0002-6036-5875)
- Trevor Manz (ORCID: https://orcid.org/0000-0001-7694-5164)
- Nils Gehlenborg (ORCID: https://orcid.org/0000-0003-0327-8297)
- Chuck McCallum (ORCID: https://orcid.org/0000-0003-4039-9768)
- Mark S. Keller (ORCID: https://orcid.org/0000-0003-3003-874X)
- Ilan Gold (ORCID: https://orcid.org/0000-0002-5823-1026)
Institutions
- Broad Institute (US)
- Harvard University (US)
- Altos Labs
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
Funders
- National Science Foundation
- National Institutes of Health
- Harvard Stem Cell Institute
- Division of Chemical, Bioengineering, Environmental, and Transport Systems