Fig. 1: The BayesSpace workflow. | Nature Biotechnology

Fig. 1: The BayesSpace workflow.

From: Spatial transcriptomics at subspot resolution with BayesSpace

Fig. 1

a, The BayesSpace workflow begins with preprocessed ST or Visium data. Data are spatially clustered to infer regions with similar expression profiles. These clusters can be refined via enhanced clustering to provide a higher-resolution spatial map. Enhanced clustering also provides the basis for predicting gene expression at the higher resolution, which can be used in further differential expression analyses. b, From geometric representations of spatial distribution of spots in the ST and Visium technologies, neighbors can be identified for each spot based on shared edges (top). Each spot can be subdivided into subspots, which again have natural edge-based neighbors (bottom).

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