SenPred: a single-cell RNA sequencing-based machine learning pipeline to classify deeply senescent dermal fibroblast cells for the detection of an in vivo senescent cell burden

Abstract excerpt

BACKGROUND: Senescence classification is an acknowledged challenge within the field, as markers are cell-type and context dependent. Currently, multiple morphological and immunofluorescence markers are required. However, emerging scRNA-seq datasets have enabled an increased understanding of senescent cell heterogeneity. METHODS: Here we present SenPred, a machine-learning pipeline which identifies fibroblast...

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• Share to Epigenetics and DNA Methylation
• Share to Single-cell and spatial transcriptomics
• Share to Telomeres, Telomerase, and Senescence