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Protocol to characterize tumor microenvironment in a diffuse midline glioma mouse model using multi-omics approach on sequential sections.

Code ↔ Paper

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Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

Python · 27 lines · 669 B · BSD-3-Clause

  1. #!/usr/bin/env python
  3. import re
  4. import requests
  5. from packaging import version
  7. def get_most_recent_version(name):
  8. request = requests.get(
  9. "https://api.anaconda.org/package/conda-forge/" + name
  10. )
  11. request.raise_for_status()
  13. pkg = max(
  14. request.json()["files"], key=lambda x: version.parse(x["version"])
  15. )
  16. return pkg["version"]
  18. mamba_version = get_most_recent_version("mamba")
  20. with open("Miniforge3/construct.yaml", "r") as f:
  21. content = f.read()
  23. # Replace mamba version
  24. content = re.sub(r"mamba [\d.]+$", f"mamba {mamba_version}", content, flags=re.M)
  26. with open("Miniforge3/construct.yaml", "w") as f:
  27. f.write(content)

update.py at commit cf46043, under BSD-3-Clause · at the source

Overview

Authors: Raphaël Collot1,2, Celina Honhoff1,2, Cristian Ruiz-Moreno1,2, Ravian L. van Ineveld1,2, Anne C. Rios1,2,3
  1. Princess Máxima Center for pediatric oncology, Utrecht, the Netherlands
  2. Oncode Institute, Utrecht, the Netherlands
  3. Department of Biology, Faculty of Science, Utrecht University, Utrecht, the Netherlands
Institutions: Oncode Institute (Netherlands); Princess Máxima Center (Netherlands); Utrecht University (Netherlands)
Journal: STAR protocols, volume 7, issue 3, article 104801
Dates: published online 24 August 2026; in print August 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1016/j.xpro.2026.104801 · PMID 42636111 · PMCID PMC13506531 · OpenAlex W7204093701
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: genetics / omics (modality), histology / microscopy (modality), mouse (organism), other condition (population)
Methods: Evoked potentials, fMRI & imaging, Statistics
Keywords: Antibody, Cancer, Microscopy, RNAseq, Single Cell
Topic: Glioma Diagnosis and Treatment (Genetics, Medicine), according to OpenAlex
Funding: Princess Máxima Animal Facility; Princess Máxima Center for Pediatric Oncology; Oncode Institute, the Netherlands; ERC (804412)
Citations: not cited yet (Europe PMC); 8 references in the paper
Research resources: DAPI (1:2000) RRID:AB_2307445, Rabbit anti-H3K27M IgG antibody (1:400) RRID:AB_2744969, Rabbit anti-VISTA IgG antibody (1:200) RRID:AB_2799474, Rat anti-CD31 IgG2a antibody (1:200) RRID:AB_396660, Goat anti-IBA1 IgG antibody (1:300) RRID:AB_521594, R version 4.0.2 RRID:SCR_001905, Python version 3.9 RRID:SCR_008394, Seurat version 4.0 RRID:SCR_016341, Scanpy version 1.9.3 RRID:SCR_018139, QuPath RRID:SCR_018257, DoubletFinder version 2.0.3 RRID:SCR_018771, Numbat version 1.2.3 RRID:SCR_019207, SCpubR version 1.1.2 RRID:SCR_021139, SeuratWrappers version 0.3.0 RRID:SCR_022555, Cell2location version 0.1.3. RRID:SCR_024859

Abstract

Diffuse midline glioma (DMG) tumors form complex tumor-immune microenvironments with marked cellular heterogeneity. Here, we present a protocol to generate orthotopic DMG tumors in immunocompetent neonatal mice and to spatially characterize the tumor ecosystem using a multi-omics workflow on sequential brain sections. We detail procedures for brain freezing, cryosectioning, single-nuclei RNA sequencing, and Visium spatial transcriptomics. We then describe steps for cyclic immunofluorescence and integrative computational analysis to resolve cellular states and spatial organization.

For complete details on the use and execution of this protocol, please refer to Collot et al.1

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above.

conda-forge/miniforge

License: BSD-3-Clause
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: cf4604327d8c6f43b66f4a126bee12a2faa3db1d, 19 September 2026
Languages: Shell (8), Python (3), JavaScript (1)
Size: 32 files, 12 scripts
Software Heritage: archived
Found in: the text, “Image co-registration”
Holds: README, license file, environment (docs/requirements.txt, .github/workflows/conda_release.yml, .github/actions/autoupdate/environment.yml), continuous integration, documentation
Not found: CITATION.cff, tests
Tools: NumPy (1 file), Pillow (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
14 files
At the source: github.com/conda-forge/miniforge/releases

Zenodo 21513336

License: MIT
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Data and code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
At the source: doi.org/10.5281/zenodo.21513336

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 12 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data and code availability

• Sequencing datasets generated as part of the original study1 are available on Zenodo: https://doi.org/10.5281/zenodo.21513336. • Code for the image co-registration (CycFluoCoreg-STAR) can be found on GitHub (https://github.com/Dream3DLab/CycFluoCoreg-STAR), along with a tutorial dataset (https://github.com/Dream3DLab/CycFluoCoreg-STAR).

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 5 keywords, 4 funders, 8 references, 15 RRIDs.

Cite

This paper

Collot, R., Honhoff, C., Ruiz-Moreno, C., van Ineveld, R. L., & Rios, A. C. (2026). Protocol to characterize tumor microenvironment in a diffuse midline glioma mouse model using multi-omics approach on sequential sections. STAR protocols, 7(3), 104801. https://doi.org/10.1016/j.xpro.2026.104801

BibTeX

@article{collot2026protocol,
author = {Collot, Raphaël and Honhoff, Celina and Ruiz-Moreno, Cristian and van Ineveld, Ravian L. and Rios, Anne C.},
title = {{Protocol to characterize tumor microenvironment in a diffuse midline glioma mouse model using multi-omics approach on sequential sections}},
journal = {STAR protocols},
year = {2026},
month = aug,
volume = {7},
number = {3},
pages = {104801},
publisher = {Elsevier},
issn = {2666-1667},
doi = {10.1016/j.xpro.2026.104801},
url = {https://doi.org/10.1016/j.xpro.2026.104801},
pmid = {42636111},
pmcid = {PMC13506531}
}

RIS

TY - JOUR
AU - Collot, Raphaël
AU - Honhoff, Celina
AU - Ruiz-Moreno, Cristian
AU - van Ineveld, Ravian L.
AU - Rios, Anne C.
TI - Protocol to characterize tumor microenvironment in a diffuse midline glioma mouse model using multi-omics approach on sequential sections
T2 - STAR protocols
J2 - STAR Protoc
PY - 2026
DA - 2026/08/24
VL - 7
IS - 3
SP - 104801
SN - 2666-1667
PB - Elsevier
DO - 10.1016/j.xpro.2026.104801
UR - https://doi.org/10.1016/j.xpro.2026.104801
LA - en
ER -

CSL-JSON

{
"id": "10.1016/j.xpro.2026.104801",
"type": "article-journal",
"title": "Protocol to characterize tumor microenvironment in a diffuse midline glioma mouse model using multi-omics approach on sequential sections",
"container-title": "STAR protocols",
"author": [
{
"family": "Collot",
"given": "Raphaël"
},
{
"family": "Honhoff",
"given": "Celina"
},
{
"family": "Ruiz-Moreno",
"given": "Cristian"
},
{
"family": "van Ineveld",
"given": "Ravian L."
},
{
"family": "Rios",
"given": "Anne C."
}
],
"container-title-short": "STAR Protoc",
"volume": "7",
"issue": "3",
"page": "104801",
"DOI": "10.1016/j.xpro.2026.104801",
"PMID": "42636111",
"PMCID": "PMC13506531",
"ISSN": "2666-1667",
"publisher": "Elsevier",
"URL": "https://doi.org/10.1016/j.xpro.2026.104801",
"language": "en",
"issued": {
"date-parts": [
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8,
24
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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