MAAPER: model-based analysis of alternative polyadenylation using 3′ end-linked reads

Genome Biology

Wei Vivian Li¹  Ruijia Wang²  Dinghai Zheng²  Bin Tian³ 

[1] Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Rutgers, The State University of New Jersey, 08854, Piscataway, NJ, USA;Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, 07103, Newark, NJ, USA;Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, 07103, Newark, NJ, USA;Program in Gene Expression and Regulation, and Center for Systems and Computational Biology, The Wistar Institute, 19104, Philadelphia, PA, USA;

关键词: Alternative polyadenylation;    RNA sequencing;    Bioinformatic tool;    3′ end reads;    Cellular stress;    Trophoblasts;   

DOI  :  10.1186/s13059-021-02429-5

来源: Springer

【 摘 要 】

Most eukaryotic genes express alternative polyadenylation (APA) isoforms. A growing number of RNA sequencing methods, especially those used for single-cell transcriptome analysis, generate reads close to the polyadenylation site (PAS), termed nearSite reads, hence inherently containing information about APA isoform abundance. Here, we present a probabilistic model-based method named MAAPER to utilize nearSite reads for APA analysis. MAAPER predicts PASs with high accuracy and sensitivity and examines different types of APA events with robust statistics. We show MAAPER’s performance with both bulk and single-cell data and its applicability in unpaired or paired experimental designs.

【 授权许可】

CC BY