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Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data
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 increasi...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10653393/ https://www.ncbi.nlm.nih.gov/pubmed/37816550 http://dx.doi.org/10.1261/rna.079849.123 |
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author | Bryce-Smith, Sam Burri, Dominik Gazzara, Matthew R. Herrmann, Christina J. 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, Ben Poon, Chi-Lam Rot, Gregor Schärfen, Leonard Wu, Pin-Jou Yoon, Yoseop Barash, Yoseph Zavolan, Mihaela |
author_facet | Bryce-Smith, Sam Burri, Dominik Gazzara, Matthew R. Herrmann, Christina J. 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, Ben Poon, Chi-Lam Rot, Gregor Schärfen, Leonard Wu, Pin-Jou Yoon, Yoseop Barash, Yoseph Zavolan, Mihaela |
author_sort | Bryce-Smith, Sam |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10653393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-106533932023-12-01 Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data Bryce-Smith, Sam Burri, Dominik Gazzara, Matthew R. Herrmann, Christina J. 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, Ben Poon, Chi-Lam Rot, Gregor Schärfen, Leonard Wu, Pin-Jou Yoon, Yoseop Barash, Yoseph Zavolan, Mihaela RNA Bioinformatics: Benchmark 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. Cold Spring Harbor Laboratory Press 2023-12 /pmc/articles/PMC10653393/ /pubmed/37816550 http://dx.doi.org/10.1261/rna.079849.123 Text en © 2023 Bryce-Smith et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society https://creativecommons.org/licenses/by-nc/4.0/This article, published in RNA, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Bioinformatics: Benchmark Bryce-Smith, Sam Burri, Dominik Gazzara, Matthew R. Herrmann, Christina J. 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, Ben Poon, Chi-Lam Rot, Gregor Schärfen, Leonard Wu, Pin-Jou Yoon, Yoseop Barash, Yoseph Zavolan, Mihaela Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data |
title | Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data |
title_full | Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data |
title_fullStr | Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data |
title_full_unstemmed | Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data |
title_short | Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data |
title_sort | extensible benchmarking of methods that identify and quantify polyadenylation sites from rna-seq data |
topic | Bioinformatics: Benchmark |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10653393/ https://www.ncbi.nlm.nih.gov/pubmed/37816550 http://dx.doi.org/10.1261/rna.079849.123 |
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