Learning multi-cellular representations of single-cell transcriptomics data enables characterization of patient-level disease states (opens in new tab)

Single-cell foundation models fail to represent multi-cellular phenotypes such as disease severity and drug response. Liu et al. introduce PaSCient, a foundation model that learns to embed single-cell RNA sequencing samples across many disease and tissue contexts, highlighting cells and genes that predict these patient-level phenotypes.