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

Abstract

Multi-omics 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.