Evidence map›Paper›PMID 37425672›Full record

ArticlebioRxiv : the preprint server for biology2023

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 and 16 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors.

Sam Bryce-SmithUCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK.
Dominik BurriBiozentrum, University of Basel, Basel, Switzerland.
Matthew R GazzaraDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
Christina J HerrmannBiozentrum, University of Basel, Basel, Switzerland.
Weronika DaneckaInstitute for Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom.
Christina M FitzsimmonsLaboratory of Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Yuk Kei WanGenome Institute of Singapore, Buona Vista, Singapore.
Farica ZhuangDepartment of Computer and Information Science, School of Engineering, University of Pennsylvania, Philadelphia, USA.
Mervin M FanslerTri-Institutional Program in Computational Biology and Medicine, Weill Cornell GraduateStudies, New York, NY, USA.
José M FernándezBarcelona Supercomputing Center, Barcelona, Spain.
Meritxell FerretBarcelona Supercomputing Center, Barcelona, Spain.
Asier Gonzalez-UriarteBarcelona Supercomputing Center, Barcelona, Spain.
Samuel HaynesInstitute for Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom.
Chelsea HerdmanDepartment of Neurobiology, University of Utah, Utah, USA.
Alexander KanitzBiozentrum, University of Basel, Basel, Switzerland.
Maria KatsantoniBiozentrum, University of Basel, Basel, Switzerland.
Federico MariniInstitute of Medical Biostatistics, Epidemiology and Informatics (IMBEI) - UniversityMedical Center of the Johannes Gutenberg, University Mainz, Germany.
Euan McDonnelLeeds Institute for Data Analytics, School of Molecular and Cellular Biology, University of Leeds, United Kingdom.
Ben NicoletDepartment of Hematopoiesis, Sanquin Research, Landsteiner Laboratory, AmsterdamUMC, University of Amsterdam, and Oncode Institute, Amsterdam, The Netherlands.
Chi-Lam PoonWeill Cornell Medicine, New York, NY, USA.
Gregor RotSwiss Institute of Bioinformatics, Lausanne, Switzerland.
Leonard SchärfenDepartment of Molecular Biophysics & Biochemistry, Yale University, New Haven CT, USA.
Pin-Jou WuCenter for Plant Molecular Biology (ZMBP), University of Tübingen, Germany.
Yoseop YoonDepartment of Microbiology and Molecular Genetics, School of Medicine, University of California Irvine, Irvine, California, USA.
Yoseph BarashDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
Mihaela ZavolanBiozentrum, University of Basel, Basel, Switzerland.

Funding

Methods for RNA splicing variations detection, quantification, visualization, and association from large heterogeneous datasetsR01GM128096 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI BARASH, YOSEPH · 2018 to 2021
$1.8M
Identifying regulatory uORFs as a targetable axis for hereditary diseaseR01GM147739 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI BARASH, YOSEPH, HAND, NICHOLAS JOSEPH · 2022 to 2025
$1.7M
Methods for improving clinical diagnostic by detection, prediction, interpretation and prioritization of aberrant transcriptome variationsR01LM013437 · NLM · UNIVERSITY OF PENNSYLVANIA · PI BARASH, YOSEPH · 2020 to 2023
$1.4M
Mechanisms and consequences of 3'UTR isoform diversity in erythropoiesisF31HL162546 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI GAZZARA, MATTHEW ROBERT · 2022 to 2024
$136k
NHLBI NIH HHS F31 HL162546NIGMS NIH HHS R01 GM128096NIGMS NIH HHS R01 GM147739NLM NIH HHS R01 LM013437
6 · The paper itself

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, and 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 seamless 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. Furthermore, the containers and reproducible workflows generated in the course of this project can be seamlessly deployed and extended in the future to evaluate new methods or datasets.

Indexed as

(alternative) polyadenylationBenchmarkingbioinformaticscommunity initiativeRNA-seq

Identifiers

PMID37425672
PMCPMC10327023

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.