Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data

Author:

Bryce-Smith Sam,Burri Dominik,Gazzara Matthew R.,Herrmann Christina J.ORCID,Danecka Weronika,Fitzsimmons Christina M.,Wan Yuk Kei,Zhuang Farica,Fansler Mervin M.,Fernández José M.,Ferret Meritxell,Gonzalez-Uriarte Asier,Haynes Samuel,Herdman Chelsea,Kanitz Alexander,Katsantoni Maria,Marini Federico,McDonnel Euan,Nicolet BenORCID,Poon Chi-Lam,Rot Gregor,Schärfen Leonard,Wu Pin-Jou,Yoon Yoseop,Barash YosephORCID,Zavolan MihaelaORCID

Abstract

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, limitations, and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3′-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for continuous extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies, while the containers and reproducible workflows could easily be deployed and extended to evaluate new methods or data sets.

Funder

UK Motor Neurone Disease Association and Masonic Charitable Foundation PhD Studentship

American Cancer Society

Blavatnik Family Fellowship in Biomedical Research and by NHLBI of the National Institutes of Health (NIH) under award number

The Emerging Human Brain Cluster (Clúster Emergent del Cervell Humà – CECH) project

European Regional Development Fund of the European Union

Catalan Government

Singapore International Graduate Award. OpenEBench is partly funded by the Horizon 2020 ELIXIR-CONVERGE programme

Swiss National Science Foundation

Publisher

Cold Spring Harbor Laboratory

Subject

Molecular Biology

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