Abstract
AbstractSingle-cell RNA-seq (scRNA-seq) profiles gene expression with high resolution. Here, we develop a stepwise computational method-called SCAPTURE to identify, evaluate, and quantify cleavage and polyadenylation sites (PASs) from 3′ tag-based scRNA-seq. SCAPTURE detects PASs de novo in single cells with high sensitivity and accuracy, enabling detection of previously unannotated PASs. Quantified alternative PAS transcripts refine cell identity analysis beyond gene expression, enriching information extracted from scRNA-seq data. Using SCAPTURE, we show changes of PAS usage in PBMCs from infected versus healthy individuals at single-cell resolution.
Funder
National Natural Science Foundation of China
Ministry of Science and Technology of the People's Republic of China
chinese academy of sciences
National Institutes of Health
howard hughes medical institute
china postdoctoral science foundation
Publisher
Springer Science and Business Media LLC
Cited by
14 articles.
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