4.7 Article

movAPA: modeling and visualization of dynamics of alternative polyadenylation across biological samples

Journal

BIOINFORMATICS
Volume 37, Issue 16, Pages 2470-2472

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btaa997

Keywords

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Funding

  1. National Natural Science Foundation of China [61871463, 61573296, 61802323]

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movAPA is an R package for modeling and visualizing alternative polyadenylation dynamics across different biological samples, providing functions for preprocessing, annotation, and statistical analysis of poly(A) sites, as well as identification of poly(A) signals, profiling of APA dynamics, and visualization. It offers seven metrics for measuring tissue-specificity or usages of APA sites across samples, and uses three methods for identifying 3' UTR shortening/lengthening events. It also allows exploration of APA site switching involving non-3' UTR polyadenylation.
Motivation:Alternative polyadenylation (APA) has been widely recognized as a widespread mechanism modulated dynamically. Studies based on 3' end sequencing and/or RNA-seq have profiled poly(A) sites in various species with diverse pipelines, yet no unified and easy-to-use toolkit is available for comprehensive APA analyses. Results: We developed an R package called movAPA for modeling and visualization of dynamics of alternative polyadenylation across biological samples. movAPA incorporates rich functions for preprocessing, annotation and statistical analyses of poly(A) sites, identification of poly(A) signals, profiling of APA dynamics and visualization. Particularly, seven metrics are provided for measuring the tissue-specificity or usages of APA sites across samples. Three methods are used for identifying 3' UTR shortening/lengthening events between conditions. APA site switching involving non-3' UTR polyadenylation can also be explored. Using poly(A) site data from rice and mouse sperm cells, we demonstrated the high scalability and flexibility of movAPA in profiling APA dynamics across tissues and single cells.

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