Abstract
Detecting senescent cells from single-cell RNA-seq data remains challenging due to the weak and non-specific expression of canonical markers. Here, we demonstrate that simple expansion of these low-signal marker sets does not improve detection accuracy. To address this limitation, we develop ICE (Imputation-based Cell Enrichment), a computational framework that integrates expression imputation with marker refinement. ICE improves the detection of senescent cells in pancreatic β cells and microglia from Alzheimer's disease samples. This tool enables reliable identification of senescence-associated cell populations, facilitating more detailed analyses of their heterogeneity and temporal dynamics across human tissues and disease contexts.