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Updated: Aug 6, 2026

Techniques to Induce and Quantify Cellular Senescence
Published on: May 1, 2017
Protocol for classifying cellular senescence from single-cell and single-nucleus RNA sequencing data
Anina N Lund1, Ryan C Thompson1, Brian H Kopell2
1Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Abstract:
Cellular senescence is a cell state characterized by stable cell-cycle arrest accompanied by coordinated molecular, metabolic, and functional changes. Here, we present a protocol to classify senescent cells from single-cell or single-nucleus RNA sequencing data using gene expression activity scoring of a senescence gene set provided by the user. We describe steps for data-driven optimization of estimated proportion of senescent cells per cell type via enrichment testing. We then detail procedures for differential expression analysis to define senescence-associated transcriptional programs. For complete details on the use and execution of this protocol, please refer to Lund et al.1.
