Galaxy single-cell & spatial omics community update: Navigating new frontiers in 2025

Abstract

Single-cell omics, named Method of the Year three times, have revolutionized biological research by enabling the high-resolution exploration of cellular heterogeneity and molecular processes. Initially centered on transcriptomics, this rapidly evolving field now ranges from multiomics to spatial analysis, with expanding customization options. The ubiquity of such analyses and the lack of a unified pipeline necessitate the development of scalable, flexible, and integrated tools and workflows. The Galaxy platform has responded to these technological advancements, extending its repertoire of freely accessible tools and workflows, backed by expert-reviewed and user-informed training resources to empower researchers to perform and interpret their own analyses. With more than 175 tools, 120 training resources, and 300,000 jobs running at the time of writing, this process has culminated in the development of Galaxy single-cell and spatial omics community (SPOC), designed to promote global collaboration in advancing usable, reproducible, accessible, and sustainable single-cell and spatial omics research.

Keywords: Galaxy platform; RDM; data life cycle; global collaboration; multiomics; open-source software; reproducibility; research data management; single-cell; spatial; training resources.

Graphical abstract

Figure 1

Galaxy SPO resources and community growth over time (A) SPO tools added to the Galaxy platform. Complex tool suites are often divided into multiple Galaxy tools; for instance, the Anndata Python package is split into four distinct tools, each serving a specific purpose—importing, exporting, inspecting, and manipulating Anndata objects. Since 2020, we have gathered more functionality in individual tools, rather than one function per tool, to make tool finding easier for users. (B) Number of commits in Galaxy SPO tool repositories. Four of the main tool repositories with a total of over 1,400 commits show tool sustainability. (C) The number of contributors to Galaxy SPO tool repositories steadily increased over time. (D) SPO training resources added to the GTN. Since 2020, a wide range of new tutorials (31), workflows (38), FAQs (20), recordings (18), and slide decks (7) have expanded the GTN. (E) Cumulative lines added to SPO training resources within the GTN. (F) In February 2022, the GTN added support for recording different aspects of a contributor’s contributions, which is reflected in the increase in editors and testers for single-cell materials. (G) Regional, technical, and pragmatic collaboration for SPOC. Left side: collaboration across the original “big three” servers of AU, USA, and EU, which enables shared resources for further federated servers. Right side: collaboration across technical skillsets (user, developer, and trainer) and existing community sites (Galaxy Community Hub; Subdomains/Galaxy Labs; Galaxy Training Network). (H) The allowed conversions between common SPO data types in Galaxy.

Figure 2

SPO resources usage (A) New SPO Galaxy users (who have run at least one SPO tool), (B) number of jobs, and (C) computing resources for SPO tools over the period of 7 years. (D) Cumulative number of jobs run using Scanpy and Anndata tools. Continuous updates and the incorporation of user feature requests have ensured their sustainability. (E) Pageviews and visitors for GTN single-cell pages over time. This graph focuses solely on pages under single-cell topic to ensure data are not inadvertently collected for non-single-cell page visits (e.g., event pages with general audiences). Four annotations are marked, from left to right, they are as follows: GTN Smörgåsbord 3, which was an asynchronous learning event with many topics, including the large outage that occurred when Galaxy Europe administrators could not restore metrics gathering services, OU’s bioinformatics bootcamp, which covered solely single-cell tutorials, and lastly, the recent Galaxy Training Academy (GTA) vent, which was similar in scope to GTN Smörgåsbord 3.

Figure 3

Using the Galaxy SPO resources: We can plan experiments using conceptual slide decks that address concepts of batch correction and interpretation, along with exemplar paper replications We can collect data from LIMS as well as EBI and Human Cell Atlas single-cell data repositories using retrieval tools. We can process datasets, interconverting between formats using dedicated tools and workflows, from various protocols like Drop-seq, 10× Chromium, inDrop, and Smart-Seq. We can analyze data using our plethora of training materials and workflows. This includes standard clustering and annotation methods, pseudobulk analyses, trajectory analyses, and the integration of multiomics data. We preserve data—Galaxy allows containerization of data and metadata into research object standards like Research Object Crate and BioCompute objects. These formats bundle together analyzed data, metadata, and analysis parameters, creating a comprehensive package that can be easily shared and reused. We can share data and analyses effectively using Galaxy histories and the archive-to-Zenodo feature, as well as Pan-Galactic workflow search functions. Finally, we emphasize data reuse in Galaxy, providing specific tools, workflows, and training on how to reuse old data to create new insights—most notably in our bulk RNA deconvolution materials. Image modified from original; ELIXIR (2021) research data management kit. A deliverable from the EU-funded ELIXIR-CONVERGE project (grant agreement 871075). URL: https://rdmkit.elixir-europe.org/.