Learning Discrete Cell and Niche Codes from Spatial Transcriptomics Using Dual Residual Vector Quantization
Spatially-resolved transcriptomics (SRT) measures gene expression at single-cell resolution while preserving each cell's spatial location, enabling the joint study of cell identity and cellular niche, the recurring microenvironment that organises tissue function. Existing representation-learning methods typically capture only one of these axes at a time. We present SQUINT, a graph vector…
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