Article

SpatialMap: A Scalable Deep Learning Method for Cell Typing in Subcellular Spatial Transcriptomics

2025-07-05

Abstract excerpt

Subcellular imaging transcriptomics has offered unprecedented resolution of spatial mapping of gene expressions at subcellular level. However, accurate and robust cell type annotation at cellular level remains a challenge. Here we present SpatialMap, a deep weakly supervised cell typing framework that combines graph neural networks (GNN) with transfer learning to annotate cellular identities in subcellular spatial...

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Literature Corpus work: 2d7763d3-9b30-5b0a-aa2e-d177372c4b5b
DOI: 10.1101/2025.07.03.662904

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