Contextual Differences Between Paired Molecular Representations Encode Cell State

Different molecular measurements can provide complementary views of the same biological element and capture distinct aspects of cellular state. Existing representation learning approaches typically characterize such measurements through individual or integrated representations, while relationships between paired observations of the same biological element are less directly used as representations themselves. This raises the question of whether these relationships can themselves provide a representation of cellular state. We study this question in single cell transcriptomics, where unspliced and spliced RNA provide paired measurements of the same genes in different RNA processing states. We introduce scUS, a pretrained masked Transformer that jointly contextualizes the two RNA states within each cell and produces paired representations for each gene. Differences between these contextual representations define a gene resolved profile for every cell. These profiles retained cell state structure across biological samples, whereas reducing them to a single measure of overall discrepancy substantially weakened this structure. Representation differences also remained sensitive to cellular context even after matching gene identity and local unspliced and spliced input bins. Extending the same analysis to RNA and chromatin accessibility revealed similar organization associated with cell type and distinct patterns across different molecular pairs. Together, our results show that contextual differences between paired molecular representations can themselves form a structured representation of cellular state.