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