Duncan NRI Faculty and Staff Publications
Language
English
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
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
Keywords
Polyadenylation, Humans, RNA-Seq, Algorithms, Deep Learning, Sequence Analysis, RNA, Software, bioinformatics, genomics
Published Open-Access
yes
Recommended Citation
Venkata Jonnakuti, Sriya Jonnakuti, and Hari Krishna Yalamanchili, "Protocol for Unlocking Alternative Polyadenylation Insights From Bulk RNA-Seq Data With PolyAMiner-Bulk" (2025). Duncan NRI Faculty and Staff Publications. 108.
https://digitalcommons.library.tmc.edu/duncar_nri_pub/108
Graphical Abstract
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Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Neurology Commons, Neurosciences Commons