SFUMATO: Bayesian probabilistic clustering for uncertainty-aware spatialtranscriptomics analysis and mapping
In situ sequencing methods provide subcellular-resolution gene expression data while preserving spatial context, enabling the integrated analysis of genomics and tissue morphology. However, many clustering workflows represent spatial transcriptomic structure through hard labels, imposing sharp boundaries between transcriptional domains and limiting the visualisation of gradual transitions, mixed…
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