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Updated: Jul 14, 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
1Department of Neuromuscular Diseases, UCL Queen Square Motor Neuron Disease Centre, UCL Queen Square Institute of Neurology, UCL, London WC1N 3BG, United Kingdom.
APAeval benchmarks tools for alternative polyadenylation (APA) site analysis in RNA sequencing data. This evaluation assists researchers in selecting optimal tools for accurate APA identification and quantification from RNA-seq experiments.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- The rapid growth of data and analysis methods necessitates robust evaluation of their applicability and accuracy.
- Identifying and quantifying alternative polyadenylation (APA) sites from RNA sequencing (RNA-seq) data is crucial for understanding gene expression regulation.
- Existing tools for APA analysis require standardized benchmarking to ensure reliable results.
Conclusions:
- The APAeval initiative provides essential benchmarks for APA analysis tools in RNA-seq data.
- This work assists researchers in selecting the most appropriate tools for their specific APA analysis needs.
- Reproducible workflows and the OpenEBench platform enable the evaluation of new methods and datasets, fostering continuous improvement in the field.
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