Stanford University researchers have developed a computational method for identifying where cells are situated in a sample when capturing spatial transcriptomics. The method combines data from spatial transcriptions and a reference single-cell RNA atlas to create modeling outputs. The resulting models can be used to view cellular substructures, identify colocalization patterns and analyze differential expression within a cell type by location.
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Source: Phys.org