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Updated: Jul 24, 2025
Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
Published on: June 24, 2021
Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data.
Sam Bryce-Smith1, Dominik Burri2,3, Matthew R Gazzara4
1UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK.
This study benchmarks tools for alternative polyadenylation (APA) site analysis in RNA sequencing data. It provides a platform for continuous evaluation, aiding researchers in selecting optimal methods for APA identification and quantification.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- The rapid growth of data and analysis methods necessitates robust evaluation frameworks.
- Accurate identification and quantification of alternative polyadenylation (APA) sites are crucial for understanding gene expression regulation.
Conclusions:
- The study assists researchers in selecting appropriate tools for APA analysis in RNA-seq studies.
- The developed platform and workflows facilitate the continuous evaluation and extension of APA analysis methods.
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