Bio Spatial Transcriptomics High Resolution Binning
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).
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryContent & writingStars0
About this skill
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).
Quick start
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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).
About this listing
Category
Content & writing
Reported license
Not specified
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI