Protocol for Unlocking Alternative Polyadenylation Insights From Bulk RNA-Seq Data With PolyAMiner-Bulk

Authors

Venkata Jonnakuti
Sriya Jonnakuti
Hari Krishna Yalamanchili

Publication Date

3-21-2025

Journal

STAR Protocols

DOI

10.1016/j.xpro.2025.103664

PMID

40022739

PMCID

PMC11919574

PubMedCentral® Posted Date

2-28-2025

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes

Keywords

Polyadenylation, Humans, RNA-Seq, Algorithms, Deep Learning, Sequence Analysis, RNA, Software, bioinformatics, genomics

Abstract

PolyAMiner-Bulk, a deep-learning-based algorithm to decode alternative polyadenylation (APA) dynamics from bulk RNA sequencing (RNA-seq) data, enables scientists to identify and quantify APA events from processed bulk RNA-seq data. The protocol allows researchers to explore differential APA usage between two conditions and gain a better understanding of post-transcriptional regulatory mechanisms. The major steps involve input data preparation, executing PolyAMiner-Bulk, and interpreting the results. A basic familiarity with pre-processing bulk RNA-seq data and command-line tools is suggested.

For complete details on the use and execution of this protocol, please refer to Jonnakuti et al.¹