SigBridgeR

Identifies phenotype-associated cell subpopulations by integrating phenotypic data (e.g., survival, drug sensitivity), bulk gene expression, and single-cell RNA-seq (scRNA-seq) profiles. It employs multiple algorithms to reliably connect cellular features with clinical or functional phenotypes, offering a unified pipeline for multi-modal analysis that uncovers biologically and clinically relevant cell states in heterogeneous datasets.