Portal de Periódicos da CAPES

The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update

2022; Oxford University Press; Volume: 50; Issue: W1 Linguagem: Inglês

10.1093/nar/gkac247

1362-4962

Enis Afgan, Anton Nekrutenko, Björn Grüning, Daniel Blankenberg, Jeremy Goecks, Michael C. Schatz, Alexander Ostrovsky, Alexandru Mahmoud, Andrew Lonie, Anna Syme, Anne Fouilloux, Anthony Bretaudeau, Anton Nekrutenko, Anup Kumar, Arthur C. Eschenlauer, Assunta D DeSanto, Aysam Guerler, Beatriz Serrano‐Solano, Bérénice Batut, Björn Grüning, Bradley W. Langhorst, Bridget Carr, Bryan Raubenolt, Cameron Hyde, Catherine J. Bromhead, Christopher B. Barnett, Coline Royaux, Cristóbal Gallardo, Daniel Blankenberg, Daniel Fornika, Dannon Baker, Dave Bouvier, Dave Clements, David Anderson de Lima Morais, David López Tabernero, Delphine Larivière, Engy Nasr, Enis Afgan, Federico Zambelli, Florian Heyl, Fotis Psomopoulos, Frederik Coppens, Gareth Price, Gianmauro Cuccuru, Gildas Le Corguillé, Greg Von Kuster, Gulsum Gudukbay Akbulut, Helena Rasche, Hans-Rudolf Hotz, Ignacio Eguinoa, Igor V. Makunin, Isuru Ranawaka, James Taylor, Jayadev Joshi, Jennifer Hillman‐Jackson, Jeremy Goecks, John Chilton, Kaivan Kamali, Keith Suderman, Krzysztof Poterlowicz, Le Bras Yvan, Lucille Lopez‐Delisle, Luke Sargent, Madeline E. Bassetti, M. A. Tangaro, Marius van den Beek, Martin Čech, Matthias Bernt, Matthias Fahrner, Mehmet Tekman, Melanie Christine Föll, Michael C. Schatz, Michael R. Crusoe, Miguel Roncoroni, Natalie Kucher, Nate Coraor, Nicholas Stoler, Nick Rhodes, Nicola Soranzo, Niko Pinter, Nuwan Goonasekera, Pablo Moreno, Pavankumar Videm, Mélanie Pétéra, Pietro Mandreoli, Pratik Jagtap, Qiang Gu, Ralf J. M. Weber, Ross Lazarus, Ruben H.P. Vorderman, Saskia Hiltemann, Sergey Golitsynskiy, Shilpa Garg, Simon Bray, Simon Gladman, Simone Leo, Subina Mehta, Timothy J. Griffin, Vahid Jalili, Yves Vandenbrouck, Victor Wen, VIJAY NAGAMPALLI, Wendi Bacon, Willem de Koning, Wolfgang Maier, Peter J. Briggs,

Research Data Management Practices

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.