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BioinformaticsCell Genomics
Peer-reviewed journal article

Single-cell and spatial detection of senescent cells using DeepScence

Yilong Qu, Bing JiiD, Runze DongiD, Liangcai GuiD, Cliburn C. W. ChaniD, Jichun XieiD, Carolyn GlassiD, Xiao‐Fan WangiD, Andrew B. NixoniD, Zhicheng JiiD

Abstract

Accurately identifying senescent cells is essential for studying their spatial and molecular features. We developed DeepScence, a method based on deep neural networks, to identify senescent cells in single-cell and spatial transcriptomics data. DeepScence is based on CoreScence, a senescence-associated gene set we curated that incorporates information from multiple published gene sets. We demonstrate that DeepScence can accurately identify senescent cells in single-cell gene expression data collected both in vitro and in vivo, as well as in spatial transcriptomics data generated by different platforms, substantially outperforming existing methods.

02 /Specification & Classification

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