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. 2022 Jul 5;50(W1):W345-W351.
doi: 10.1093/nar/gkac247.

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

Galaxy Community
Collaborators

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

Galaxy Community. Nucleic Acids Res. .

Erratum in

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.

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Figures

Graphical Abstract
Graphical Abstract
The Galaxy Project is represented by a combination of software, managed services, application of the software for solving scientific analyses, and vibrant world-wide community. In turn, each area is characterized by new depicted capabilities.
Figure 1.
Figure 1.
Usage of the usegalaxy servers in Australia (AU), Europe Union (EU) and the United States (US). Large compute infrastructure is available to anyone, for free, without any configuration and it spans the world (more below). User acquisition, user retention, and user activity are captured. A dip in usage captured at the right hand side of some diagrams is cyclical, due to the end of the calendar year. A significant increase in the number of monthly jobs in the EU is due to the start of analyzing SARS-CoV-2 data (more below).
Figure 2.
Figure 2.
Categorization of the type of tools executed by users across the three most popular usegalaxy servers.
Figure 3.
Figure 3.
A sample workflow report, showing tSNE and UMAP plots of single cell expression data, automatically generated and formatted based on the outputs of a workflow.
Figure 4.
Figure 4.
(A) The Galaxy-ML toolkit provides all the tools necessary to define a learner, train it, evaluate it, and visualize its performance. (B) A Galaxy workflow to create a learner using a pipeline, perform hyperparameter search and visualize the results.
See this image and copyright information in PMC

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