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

被引:5
|
作者
Bryce-Smith, Sam [1 ]
Burri, Dominik [2 ,3 ]
Gazzara, Matthew R. [4 ]
Herrmann, Christina J. [2 ,3 ]
Danecka, Weronika [5 ]
Fitzsimmons, Christina M. [6 ]
Wan, Yuk Kei [7 ,8 ]
Zhuang, Farica [9 ]
Fansler, Mervin M. [10 ,11 ]
Fernandez, Jose M. [12 ,13 ]
Ferret, Meritxell [12 ,13 ]
Gonzalez-Uriarte, Asier [12 ,13 ]
Haynes, Samuel [5 ]
Herdman, Chelsea [14 ]
Kanitz, Alexander [2 ,3 ]
Katsantoni, Maria [2 ,3 ]
Marini, Federico [15 ]
McDonnel, Euan [16 ]
Nicolet, Ben [17 ,18 ]
Poon, Chi-Lam [19 ]
Rot, Gregor [3 ,20 ]
Scharfen, Leonard [21 ]
Wu, Pin-Jou [22 ]
Yoon, Yoseop [23 ]
Barash, Yoseph [4 ,9 ]
Zavolan, Mihaela [2 ,3 ]
机构
[1] UCL, UCL Queen Sq Inst Neurol, Dept Neuromuscular Dis, UCL Queen Sq Motor Neuron Dis Ctr, London, England
[2] Univ Basel, Biozentrum, Basel, Switzerland
[3] Swiss Inst Bioinformat, Lausanne, Switzerland
[4] Univ Penn, Perelman Sch Med, Dept Genet, Philadelphia, PA 19104 USA
[5] Univ Edinburgh, Inst Cell Biol, Sch Biol Sci, Edinburgh EH9 3FF, Midlothian, Scotland
[6] NCI, Lab Cell Biol, Ctr Canc Res, NIH, Bethesda, MD 20892 USA
[7] Genome Inst Singapore, Buona Vista 138672, Singapore
[8] Natl Univ Singapore, Yong Loo Lin Sch Med, Kent Ridge 119228, Singapore
[9] Univ Penn, Sch Engn, Dept Comp & Informat Sci, Philadelphia, PA 19104 USA
[10] Weill Cornell Grad Studies, Triinst Program Computat Biol & Med, New York, NY 10065 USA
[11] MSKCC, Sloan Kettering Inst, Canc Biol & Genet, New York, NY 10065 USA
[12] Barcelona Supercomp Ctr, Barcelona, Spain
[13] Spanish Natl Bioinformat Inst INB, ELIXIR ES, Madrid, Spain
[14] Univ Utah, Dept Neurobiol, Salt Lake City, UT 84132 USA
[15] Johannes Gutenberg Univ Mainz, Univ Med Ctr, Inst Med Biostat Epidemiol & Informat IMBEI, Mainz, Germany
[16] Univ Leeds, Leeds Inst Data Analyt, Sch Mol & Cellular Biol, Leeds LS2 9NL, England
[17] Univ Amsterdam, Dept Hematopoiesis, Landsteiner Lab, Sanquin Res,Amsterdam UMC, Amsterdam, Netherlands
[18] Oncode Inst, Utrecht, Netherlands
[19] Weill Cornell Med, Grad Sch Med Sci, New York, NY 10065 USA
[20] Univ Zurich, Inst Mol Life Sci, Zurich, Switzerland
[21] Yale Univ, Dept Mol Biophys & Biochem, New Haven, CT 06520 USA
[22] Univ Tubingen, Ctr Plant Mol Biol ZMBP, Tubingen, Germany
[23] Univ Calif Irvine, Sch Med, Dept Microbiol & Mol Genet, Irvine, CA 92617 USA
基金
瑞士国家科学基金会; 美国国家卫生研究院; 欧盟地平线“2020”;
关键词
benchmarking; (alternative) polyadenylation; bioinformatics; RNA-seq; community initiative; GENOME-WIDE ANALYSIS; ALTERNATIVE POLYADENYLATION; CLEAVAGE; EXPRESSION; REVEALS; GENES; ENDS;
D O I
10.1261/rna.079849.123
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:1839 / 1855
页数:17
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