scHG: A supercell framework with high-order graph learning enables scalable multi-omics analysis
Fig 2
The workflow includes: (1) second-order co-occurrence neighbor extraction from multi-omics data; (2) cross-omics consistency fusion; (3) probabilistic pruning to identify high-order structural units (supercells); (4) supercell clustering via optimization; and (5) visualization and downstream analyses.