SCAPTURE: a deep learning-embedded pipeline that captures polyadenylation information from 3′ tag-based RNA-seq of single cells

SCAPTURE: a deep learning-embedded pipeline that captures polyadenylation information from 3′ tag-based RNA-seq of single cells

Abstract Single-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...

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Bibliographic Details
Main Authors: Guo-Wei Li, Fang Nan, Guo-Hua Yuan, Chu-Xiao Liu, Xindong Liu, Ling-Ling Chen, Bin Tian, Li Yang
Format: Article
Language:English
Published: BMC 2021-08-01
Series:Genome Biology
Subjects:
scRNA-seq
PAS
APA
Deep learning
Peak calling
Transcript quantification
Online Access:https://doi.org/10.1186/s13059-021-02437-5

Internet

https://doi.org/10.1186/s13059-021-02437-5

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