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high-resolution-binning

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Reconstructs single cells from sub-cellular spatial capture units (Visium HD 2um bins, Stereo-seq DNB spots, Slide-seqV2 beads) by aggregating bins UP into cells rather than deconvolving a mixture DOWN. Use when choosing a bin size and recognizing the sparsity-vs-mixture dilemma (2um bins are too sparse to cluster, but binning to 8/16um re-creates the multi-cell mixture deconvolution was meant to escape); deciding between morphology-driven cell reconstruction (Bin2cell -- StarDist/Cellpose nuclei on a registered H&E/DAPI image, then assign 2um bins to nuclei) and fixed-bin aggregation by whether a co-registered cell image exists; recognizing this as the INVERSE of deconvolution (bin UP, not mix DOWN -- this is the AMBIGUOUS regime of the resolution fork); and handling each platform (Visium HD has an image so reconstruct, Slide-seqV2 has no per-bead image so aggregate or deconvolve, Stereo-seq depends on a registered stain).

When to use

• Reconstructing single cells from Visium HD 2um bins
• Aggregating Stereo-seq DNB spots into cells
• Aggregating Slide-seqV2 beads into cells
• Morphology-driven cell reconstruction using registered images
• Fixed-bin aggregation when no cell image exists
• Choosing bin size to avoid sparsity or mixture dilemmas

When not to use

• Deconvolving multi-cell mixtures in large spots
• Clustering sparse 2um bins directly
• Reconstructing cells from Slide-seqV2 without a registered image

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