Evidence map›Paper›PMID 39775842›Full record

ArticleGigaScience2025

Galaxy as a gateway to bioinformatics: Multi-Interface Galaxy Hands-on Training Suite (MIGHTS) for scRNA-seq.

Camila L Goclowski, Julia Jakiela, Tyler Collins, Saskia Hiltemann, Morgan Howells, Marisa Loach, Jonathan Manning, Pablo Moreno, Alex Ostrovsky, Helena Rasche and 4 more

Abstract read
In one paragraph

Article in GigaScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

14 authors.

Camila L GoclowskiEccles Institute of Human Genetics, University of Utah, Salt Lake City, UT, 84112, USA.ORCID 0009-0002-1327-0424
Julia JakielaSchool of Chemistry, University of Edinburgh, Edinburgh, EH9 3FJ, UK.ORCID 0009-0001-2017-8805
Tyler CollinsDepartment of Computer Science, John Hopkins Medical Institution, Baltimore, MD, 21224, USA.ORCID 0000-0002-3026-9049
Saskia HiltemannErasmus Medical Center, Rotterdam, Zuid-Holland, 3015 GD, Netherlands.ORCID 0000-0003-3803-468X
Morgan HowellsSchool of Computing & Communications, The Open University, Milton Keynes, Buckinghamshire, MK7 6AA, UK.ORCID 0009-0008-9422-6380
Marisa LoachSchool of Life, Health & Chemical Sciences, The Open University, Milton Keynes, Buckinghamshire, MK7 6AA, UK.ORCID 0000-0001-6979-6930
Jonathan ManningEuropean Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, CB10 1SD, UK.ORCID 0000-0002-3483-8456
Pablo MorenoEarly Computational Oncology, AstraZeneca, Cambridge, CB2 0AA, UK.ORCID 0000-0002-9856-1679
Alex OstrovskyDepartment of Computer Science, John Hopkins Medical Institution, Baltimore, MD, 21224, USA.ORCID 0000-0002-7901-7109
Helena RascheErasmus Medical Center, Rotterdam, Zuid-Holland, 3015 GD, Netherlands.ORCID 0000-0001-9760-8992
Mehmet TekmanDivision of Pharmacology and Toxicology, University of Freiburg, Freiburg im Breisgau, Baden-Württemberg, 79098, Germany.ORCID 0000-0002-4181-2676
Graeme TysonSchool of Life, Health & Chemical Sciences, The Open University, Milton Keynes, Buckinghamshire, MK7 6AA, UK.ORCID 0000-0002-1748-2806
Pavankumar VidemDepartment of Computer Science, University of Freiburg, Freiburg im Breisgau,Baden-Württemberg, 79098, Germany.ORCID 0000-0002-5192-126X
Wendi BaconSchool of Life, Health & Chemical Sciences, The Open University, Milton Keynes, Buckinghamshire, MK7 6AA, UK.ORCID 0000-0002-8170-8806

Funding

Engineering and Physical Sciences Research Council
6 · The paper itself

Abstract

backgroundBioinformatics is fundamental to biomedical sciences, but its mastery presents a steep learning curve for bench biologists and clinicians. Learning to code while analyzing data is difficult. The curve may be flattened by separating these two aspects and providing intermediate steps for budding bioinformaticians. Single-cell analysis is in great demand from biologists and biomedical scientists, as evidenced by the proliferation of training events, materials, and collaborative global efforts like the Human Cell Atlas. However, iterative analyses lacking reinstantiation, coupled with unstandardized pipelines, have made effective single-cell training a moving target.

findingsTo address these challenges, we present a Multi-Interface Galaxy Hands-on Training Suite (MIGHTS) for single-cell RNA sequencing (scRNA-seq) analysis, which offers parallel analytical methods using a graphical interface (buttons) or code. With clear, interoperable materials, MIGHTS facilitates smooth transitions between environments. Bridging the biologist-programmer gap, MIGHTS emphasizes interdisciplinary communication for effective learning at all levels. Real-world data analysis in MIGHTS promotes critical thinking and best practices, while FAIR data principles ensure validation of results. MIGHTS is freely available, hosted on the Galaxy Training Network, and leverages Galaxy interfaces for analyses in both settings. Given the ongoing popularity of Python-based (Scanpy) and R-based (Seurat & Monocle) scRNA-seq analyses, MIGHTS enables analyses using both.

conclusionsMIGHTS consists of 11 tutorials, including recordings, slide decks, and interactive visualizations, and a demonstrated track record of sustainability via regular updates and community collaborations. Parallel pathways in MIGHTS enable concurrent training of scientists at any programming level, addressing the heterogeneous needs of novice bioinformaticians.

Indexed as

Computational BiologySingle-Cell AnalysisSoftwareHumansRNA-SeqSequence Analysis, RNASingle-Cell Gene Expression AnalysisUser-Computer InterfacebioinformaticsGalaxy projectreproducibilityscRNA-seqsingle-cell RNA-seq analysisSTEM educationsustainabilitytraining

Identifiers

PMID39775842
PMCPMC11707610

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.