Quantifying Cross-Modality Concordance and Genome-wide Feature Linkages in Single-Cell Multiome Data

Thomas M. Menino Convention & Exhibition Center 

Single-cell multiome assays jointly profile gene expression (GEX) and chromatin accessibility (ATAC) in the same cell, enabling direct interrogation of chromatin-to-transcription relationships. Yet GEX and ATAC can partially decouple at the cell level, motivating open questions about how to characterize cross-modality concordance and leverage paired measurements for downstream analyses. Here we present POLARIS, a principled spectral framework with three main outputs: (i) cell-specific cross-modality concordance scores whose regimes correspond to agreement versus divergence between GEX and ATAC neighborhood structure, (ii) a joint cell embedding that refines cell type and state structure by combining separations from either modality, and (iii) a joint feature embedding that enables efficient genome-wide peak-gene association mapping. Together, POLARIS detects low-concordance cell populations enriched for modality-specific structure and recovers long-range peak-gene linkages that correlation-based screens often miss, while remaining computationally efficient and scalable to consortium-scale multiome datasets.

single-cell multiome

multimodal integration

gene-peak joint embedding

cross modality concordance

spectral method

regulatory element to gene mapping 

Section on Statistics in Genomics and Genetics