Evidence map›Paper›PMID 40997812›Full record

ReviewCell genomics2025

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

Marisa Loach, Amirhossein Naghsh Nilchi, Diana Chiang, Morgan Howells, Florian Heyl, Helena Rasche, Julia Jakiela, Mehmet Tekman, Menna Gamal, Pablo Moreno and 6 more

Abstract readReview
In one paragraph

Review in Cell genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Marisa LoachSchool of Life, Health and Chemical Sciences, The Open University, Milton Keynes, UK.
Amirhossein Naghsh NilchiDepartment of Computer Science, University of Freiburg, Freiburg, Germany; Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Diana ChiangDepartment of Computer Science, University of Freiburg, Freiburg, Germany.
Morgan HowellsSchool of Computing and Communications, The Open University, Milton Keynes, UK.
Florian HeylGerman Human Genome-Phenome Archive (GHGA) and the Division of Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany.
Helena RascheDepartment of Clinical Bioinformatics, Erasmus Medical Center, Rotterdam, the Netherlands.
Julia JakielaSchool of Chemistry, University of Edinburgh, Edinburgh, UK.
Mehmet TekmanInstitute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Menna GamalBioinformatics Department, University of Birmingham, Birmingham, UK.
Pablo MorenoOncology Data Science & AI, Oncology R&D, AstraZeneca, Cambridge, UK.
Saskia HiltemannCentral Data Facility, University of Freiburg, Freiburg, Germany.
Timon SchlegelDepartment of Computer Science, University of Freiburg, Freiburg, Germany.
Björn GrüningDepartment of Computer Science, University of Freiburg, Freiburg, Germany.
Rolf BackofenDepartment of Computer Science, University of Freiburg, Freiburg, Germany; Signalling Research Centre CIBSS, University of Freiburg, Freiburg, Germany.
Pavankumar VidemDepartment of Computer Science, University of Freiburg, Freiburg, Germany. Electronic address: videmp@informatik.uni-freiburg.de.
Wendi BaconSchool of Life, Health and Chemical Sciences, The Open University, Milton Keynes, UK. Electronic address: wendi.bacon@hdruk.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Computational BiologyGenomicsSingle-Cell AnalysisSoftwareHumansTranscriptomedata life cycleGalaxy platformglobal collaborationmultiomicsopen-source softwareRDMreproducibilityresearch data managementsingle-cellspatialtraining resources

Identifiers

PMID40997812
PMCPMC12791000

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.