Quantifying subcellular organization from localization to co-occurrence with InSpace

InSpace quantifies subcellular organization from spatial transcriptomics by mapping transcripts to radial coordinates and measuring distance-dependent co-occurrence, scaling to 275 million transcripts.

• Why it matters: Standard workflows collapse spatial transcriptomics into cell-by-gene counts, losing intracellular localization and molecular pair relationships needed to compare cells with different morphologies.
• What they did: InSpace-R assigns transcripts to a continuous radial axis using nuclear and cell boundaries, while InSpace-C computes distance-dependent RNA–RNA or RNA–DNA co-occurrence/depletion; simulations and biochemical references validate accuracy.
• The result: In B and plasma cells across 58 tumor datasets (12 cancer types), reduced MHC-II transcript abundance is linked to more peripheral localization and stronger mutual co-occurrence, separating MHC-II from an ER-targeted protein–enriched program.

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