Reproducible biomedical benchmarking in the cloud

• Verfasst von: Ellrott, Kyle [VerfasserIn]
• Verfasst von: Sáez Rodríguez, Julio [VerfasserIn]
• Titel: Reproducible biomedical benchmarking in the cloud
• Titelzusatz: lessons from crowd-sourced data challenges
• Verf.angabe: Kyle Ellrott, Alex Buchanan, Allison Creason, Michael Mason, Thomas Schaffter, Bruce Hoff, James Eddy, John M. Chilton, Thomas Yu, Joshua M. Stuart, Julio Saez-Rodriguez, Gustavo Stolovitzky, Paul C. Boutros and Justin Guinney
• E-Jahr: 2019
• Jahr: 10 September 2019
• Umfang: 9 S.
• Fussnoten: Gesehen am 07.10.2019
• Titel Quelle: Enthalten in: Genome biology
• Ort Quelle: London : BioMed Central, 2000
• Jahr Quelle: 2019
• Band/Heft Quelle: 20(2019) Artikel-Nummer 195, 9 Seiten
• ISSN Quelle: 1474-760X
• DOI: doi:10.1186/s13059-019-1794-0
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1678193003

Abstract

Challenges are achieving broad acceptance for addressing many biomedical questions and enabling tool assessment. But ensuring that the methods evaluated are reproducible and reusable is complicated by the diversity of software architectures, input and output file formats, and computing environments. To mitigate these problems, some challenges have leveraged new virtualization and compute methods, requiring participants to submit cloud-ready software packages. We review recent data challenges with innovative approaches to model reproducibility and data sharing, and outline key lessons for improving quantitative biomedical data analysis through crowd-sourced benchmarking challenges.