WebAtlas pipeline for integrated single cell and spatial transcriptomic data

Tong Li; Dave Horsfall; Daniela Basurto-Lozada; Kenny Roberts; Martin Prete; John E. G. Lawrence; Peng He; Tuck E; Josh Moore; A. Yoldaş; Kola Babalola; Matthew Hartley; Shila Ghazanfar; Sarah Amalia Teichmann; Muzlifah A. Haniffa; Omer Ali Bayraktar

doi:10.1038/s41592-024-02371-x

BioinformaticsNature MethodsAug 19, 2024

Peer-reviewed journal article

WebAtlas pipeline for integrated single cell and spatial transcriptomic data

Tong Li iD, Dave Horsfall iD, Daniela Basurto-Lozada iD, Kenny Roberts iD, Martin Prete iD, John E. G. Lawrence iD, Peng He iD, Tuck E, Josh Moore iD, A. Yoldaş iD, Kola Babalola iD, Matthew Hartley iD, Shila Ghazanfar iD, Sarah Amalia Teichmann iD, Muzlifah A. Haniffa iD, Omer Ali Bayraktar iD

Abstract

Single cell and spatial transcriptomics illuminate complementary features of tissues. However, online dissemination and exploration of integrated datasets is challenging due to the heterogeneity and scale of data. We introduce the WebAtlas pipeline for user-friendly sharing and interactive navigation of integrated datasets. WebAtlas unifies commonly used atlassing technologies into the cloud-optimised Zarr format and builds on Vitessce to enable remote data navigation. We showcase WebAtlas on the developing human lower limb to cross-query cell types and genes across single cell, sequencing- and imaging-based spatial transcriptomic data.

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