Galaxy (https://galaxyproject.org) is deployed globally, predominantly through free-to-use services, supporting user-driven research that broadens in scope each year. Users are attracted to public Galaxy services by platform stability, tool and reference dataset diversity, training, support and integration, which enables complex, reproducible, shareable data analysis. Applying the principles of user experience design (UXD), has driven improvements in accessibility, tool discoverability through Galaxy Labs/subdomains, and a redesigned Galaxy ToolShed. Galaxy tool capabilities are progressing in two strategic directions: integrating general purpose graphical processing units (GPGPU) access for cutting-edge methods, and licensed tool support. Engagement with global research consortia is being increased by developing more workflows in Galaxy and by resourcing the public Galaxy services to run them. The Galaxy Training Network (GTN) portfolio has grown in both size, and accessibility, through learning paths and direct integration with Galaxy tools that feature in training courses. Code development continues in line with the Galaxy Project roadmap, with improvements to job scheduling and the user interface. Environmental impact assessment is also helping engage users and developers, reminding them of their role in sustainability, by displaying estimated CO2 emissions generated by each Galaxy job.
The Galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update / L.A.L. Abueg, E. Afgan, O. Allart, A.H. Awan, W.A. Bacon, D. Baker, M. Bassetti, B. Batut, M. Bernt, D. Blankenberg, A. Bombarely, A. Bretaudeau, C.J. Bromhead, M.L. Burke, P.K. Capon, M. Čech, M. Chavero-Díez, J.M. Chilton, T.J. Collins, F. Coppens, N. Coraor, G. Cuccuru, F. Cumbo, J. Davis, P.F. De Geest, W. de Koning, M. Demko, A. Desanto, J.M.D. Begines, M.A. Doyle, B. Droesbeke, A. Erxleben-Eggenhofer, M.C. Föll, G. Formenti, A. Fouilloux, R. Gangazhe, T. Genthon, J. Goecks, A.N.G. Beltran, N.A. Goonasekera, N. Goué, T.J. Griffin, B.A. Grüning, A. Guerler, S. Gundersen, O.J.R. Gustafsson, C. Hall, T.W. Harrop, H. Hecht, A. Heidari, T. Heisner, F. Heyl, S. Hiltemann, H. Hotz, C.J. Hyde, P.D. Jagtap, J. Jakiela, J.E. Johnson, J. Joshi, M. Jossé, K. Jum'Ah, M. Kalaš, K. Kamieniecka, T. Kayikcioglu, M. Konkol, L. Kostrykin, N. Kucher, A. Kumar, M. Kuntz, D. Lariviere, R. Lazarus, Y.L. Bras, G.L. Corguillé, J. Lee, S. Leo, L. Liborio, R. Libouban, D.L. Tabernero, L. Lopez-Delisle, L.S. Los, A. Mahmoud, I. Makunin, P. Marin, S. Mehta, W. Mok, P.A. Moreno, F. Morier-Genoud, S. Mosher, T. Müller, E. Nasr, A. Nekrutenko, T.M. Nelson, A.J. Oba, A. Ostrovsky, P.V. Polunina, K. Poterlowicz, E.J. Price, G.R. Price, H. Rasche, B. Raubenolt, C. Royaux, L. Sargent, M.T. Savage, V. Savchenko, D. Savchenko, M.C. Schatz, P. Seguineau, B. Serrano-Solano, N. Soranzo, S.K. Srikakulam, K. Suderman, A.E. Syme, M.A. Tangaro, J.A. Tedds, M. Tekman, W. Cheng (Mike) Thang, A.S. Thanki, M. Uhl, M. van den Beek, D. Varshney, J. Vessio, P. Videm, G. Von Kuster, G.R. Watson, N. Whitaker-Allen, U. Winter, M. Wolstencroft, F. Zambelli, P. Zierep, R. Zoabi. - In: NUCLEIC ACIDS RESEARCH. - ISSN 0305-1048. - (2024), pp. gkae410.1-gkae410.12. [Epub ahead of print] [10.1093/nar/gkae410]
The Galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update
F. Zambelli;
2024
Abstract
Galaxy (https://galaxyproject.org) is deployed globally, predominantly through free-to-use services, supporting user-driven research that broadens in scope each year. Users are attracted to public Galaxy services by platform stability, tool and reference dataset diversity, training, support and integration, which enables complex, reproducible, shareable data analysis. Applying the principles of user experience design (UXD), has driven improvements in accessibility, tool discoverability through Galaxy Labs/subdomains, and a redesigned Galaxy ToolShed. Galaxy tool capabilities are progressing in two strategic directions: integrating general purpose graphical processing units (GPGPU) access for cutting-edge methods, and licensed tool support. Engagement with global research consortia is being increased by developing more workflows in Galaxy and by resourcing the public Galaxy services to run them. The Galaxy Training Network (GTN) portfolio has grown in both size, and accessibility, through learning paths and direct integration with Galaxy tools that feature in training courses. Code development continues in line with the Galaxy Project roadmap, with improvements to job scheduling and the user interface. Environmental impact assessment is also helping engage users and developers, reminding them of their role in sustainability, by displaying estimated CO2 emissions generated by each Galaxy job.
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