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

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

doi:https://doi.org/10.1261/rna.079849.123

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

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

Landsteiner Laboratory (AMC)

Research output: Contribution to journal › Article › Academic › peer-review

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.

Original language	English
Pages (from-to)	1839-1855
Number of pages	17
Journal	RNA (New York, N.Y.)
Volume	29
Issue number	12
DOIs	https://doi.org/10.1261/rna.079849.123
Publication status	Published - Dec 2023

Keywords

Benchmarking
Polyadenylation
RNA-Seq
RNA/genetics
Sequence Analysis, RNA/methods

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Bryce-Smith, S., Burri, D., Gazzara, M. R., Herrmann, C. J., Danecka, W., Fitzsimmons, C. M., Wan, Y. K., Zhuang, F., Fansler, M. M., Fernández, J. M., Ferret, M., Gonzalez-Uriarte, A., Haynes, S., Herdman, C., Kanitz, A., Katsantoni, M., Marini, F., McDonnel, E., Nicolet, B., ... Nicolet, B. P. (2023). Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data. RNA (New York, N.Y.), 29(12), 1839-1855. https://doi.org/10.1261/rna.079849.123

@article{6cae9e870e1a4ab396c220a258cac965,

title = "Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data",

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.",

keywords = "Benchmarking, Polyadenylation, RNA-Seq, RNA/genetics, Sequence Analysis, RNA/methods",

author = "Sam Bryce-Smith and Dominik Burri and Gazzara, {Matthew R} and Herrmann, {Christina J} and Weronika Danecka and Fitzsimmons, {Christina M} and Wan, {Yuk Kei} and Farica Zhuang and Fansler, {Mervin M} and Fern{\'a}ndez, {Jos{\'e} M} and Meritxell Ferret and Asier Gonzalez-Uriarte and Samuel Haynes and Chelsea Herdman and Alexander Kanitz and Maria Katsantoni and Federico Marini and Euan McDonnel and Ben Nicolet and Chi-Lam Poon and Gregor Rot and Leonard Sch{\"a}rfen and Pin-Jou Wu and Yoseop Yoon and Yoseph Barash and Mihaela Zavolan and B.P. Nicolet",

note = "Funding Information: We thank the RNA Society for making the hackathon possible and bringing together people from various disciplines. We thank the OpenEBench platform (https://openebench.bsc.es/) for hosting the APAeval benchmark. We thank OEB members Anna Redondo, Laura Portell, Laura Rodriguez-Navas, and Salvador Capella for help and contributions. We thank Seqera Labs (https://seqera.io/) for kindly hosting a workshop regarding the use of Nextflow and Nextflow Tower during the RNA Society 2021 meeting, and Amazon Web Services for providing us with credits for the use of their cloud platform. We are grateful to host the source code on the iRNA COSI (https:// irnacosi .org/) GitHub account. S.B.-S. was supported by a UK Motor Neurone Disease Association and Masonic Charitable Foundation PhD Studentship (893-792). C.M.F. was partially supported by a postdoctoral fellowship from the American Cancer Society (PF-19-157-01-RMC). M.R.G. was supported by the Blavatnik Family Fellowship in Biomedical Research and by NHLBI of the National Institutes of Health (NIH) under award number F31 HL162546. A.G.-U. was supported by the The Emerging Human Brain Cluster (Cl{\'u}ster Emergent del Cervell Hum{\`a} – CECH) project, number 001-P-001682, 50% cofunded by the European Regional Development Fund of the European Union (Programa Operatiu FEDER Catalunya 2014–2020), with the support of the Catalan Government. Y.K.W. was supported by the Singapore International Graduate Award. OpenEBench is partly funded by the Horizon 2020 ELIXIR-CONVERGE programme, grant agreement number 871075. The work of Y.B. was supported by R01 GM128096, R01 GM147739, and R01 LM013437. D.B. and C.J.H. were partially supported by the Swiss National Science Foundation grant number 310030_189063 to M.Z. Publisher Copyright: {\textcopyright} 2023 Bryce-Smith et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.",

year = "2023",

month = dec,

doi = "https://doi.org/10.1261/rna.079849.123",

language = "English",

volume = "29",

pages = "1839--1855",

journal = "RNA (New York, N.Y.)",

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Bryce-Smith, S, Burri, D, Gazzara, MR, Herrmann, CJ, Danecka, W, Fitzsimmons, CM, Wan, YK, Zhuang, F, Fansler, MM, Fernández, JM, Ferret, M, Gonzalez-Uriarte, A, Haynes, S, Herdman, C, Kanitz, A, Katsantoni, M, Marini, F, McDonnel, E, Nicolet, B, Poon, C-L, Rot, G, Schärfen, L, Wu, P-J, Yoon, Y, Barash, Y, Zavolan, M & Nicolet, BP 2023, 'Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data', RNA (New York, N.Y.), vol. 29, no. 12, pp. 1839-1855. https://doi.org/10.1261/rna.079849.123

TY - JOUR

T1 - Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data

AU - Bryce-Smith, Sam

AU - Burri, Dominik

AU - Gazzara, Matthew R

AU - Herrmann, Christina J

AU - Danecka, Weronika

AU - Fitzsimmons, Christina M

AU - Wan, Yuk Kei

AU - Zhuang, Farica

AU - Fansler, Mervin M

AU - Fernández, José M

AU - Ferret, Meritxell

AU - Gonzalez-Uriarte, Asier

AU - Haynes, Samuel

AU - Herdman, Chelsea

AU - Kanitz, Alexander

AU - Katsantoni, Maria

AU - Marini, Federico

AU - McDonnel, Euan

AU - Nicolet, Ben

AU - Poon, Chi-Lam

AU - Rot, Gregor

AU - Schärfen, Leonard

AU - Wu, Pin-Jou

AU - Yoon, Yoseop

AU - Barash, Yoseph

AU - Zavolan, Mihaela

AU - Nicolet, B.P.

N1 - Funding Information: We thank the RNA Society for making the hackathon possible and bringing together people from various disciplines. We thank the OpenEBench platform (https://openebench.bsc.es/) for hosting the APAeval benchmark. We thank OEB members Anna Redondo, Laura Portell, Laura Rodriguez-Navas, and Salvador Capella for help and contributions. We thank Seqera Labs (https://seqera.io/) for kindly hosting a workshop regarding the use of Nextflow and Nextflow Tower during the RNA Society 2021 meeting, and Amazon Web Services for providing us with credits for the use of their cloud platform. We are grateful to host the source code on the iRNA COSI (https:// irnacosi .org/) GitHub account. S.B.-S. was supported by a UK Motor Neurone Disease Association and Masonic Charitable Foundation PhD Studentship (893-792). C.M.F. was partially supported by a postdoctoral fellowship from the American Cancer Society (PF-19-157-01-RMC). M.R.G. was supported by the Blavatnik Family Fellowship in Biomedical Research and by NHLBI of the National Institutes of Health (NIH) under award number F31 HL162546. A.G.-U. was supported by the The Emerging Human Brain Cluster (Clúster Emergent del Cervell Humà – CECH) project, number 001-P-001682, 50% cofunded by the European Regional Development Fund of the European Union (Programa Operatiu FEDER Catalunya 2014–2020), with the support of the Catalan Government. Y.K.W. was supported by the Singapore International Graduate Award. OpenEBench is partly funded by the Horizon 2020 ELIXIR-CONVERGE programme, grant agreement number 871075. The work of Y.B. was supported by R01 GM128096, R01 GM147739, and R01 LM013437. D.B. and C.J.H. were partially supported by the Swiss National Science Foundation grant number 310030_189063 to M.Z. Publisher Copyright: © 2023 Bryce-Smith et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

PY - 2023/12

Y1 - 2023/12

N2 - 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.

AB - 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.

KW - Benchmarking

KW - Polyadenylation

KW - RNA-Seq

KW - RNA/genetics

KW - Sequence Analysis, RNA/methods

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U2 - https://doi.org/10.1261/rna.079849.123

DO - https://doi.org/10.1261/rna.079849.123

M3 - Article

C2 - 37816550

SN - 1355-8382

VL - 29

SP - 1839

EP - 1855

JO - RNA (New York, N.Y.)

JF - RNA (New York, N.Y.)

IS - 12

ER -

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

Abstract

Keywords

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