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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2027
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2027
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Dataset for the manuscript "Longitudinal spatial neutrophil profiling during ACT in murine melanoma reveals distinct lymph node infiltration patterns"

Authors: van der Voort, Gemma; Effern, Maike; Yong, Michelle Chai Rong; Kiwitz, Lukas; Turiello, Roberta; Leonardelli, Sonia; Ng, Susanna; +6 Authors

Dataset for the manuscript "Longitudinal spatial neutrophil profiling during ACT in murine melanoma reveals distinct lymph node infiltration patterns"

Abstract

Dataset and code repository for the manuscript "Longitudinal spatial neutrophil profiling during ACT in murine melanoma reveals distinct lymph node infiltration patterns" Dataset and code repository for the manuscript "Longitudinal spatial neutrophil profiling during ACT in murine melanoma reveals distinct lymph node infiltration patterns" which explores neutrophil and CD8 T cell kinetics and spatial organisation in tumor-draining vs non-draining lymph nodes in murine melanoma under adoptive T cell therapy. The manuscript is published in npj systems biology and applications. An earlier version is available as a preprint on Bioarxiv. The code is also shared on github at github.com/ICB-DCM/ACT_melanoma_neutrophil/ Data repository act_neutrophil_data_repository├── figures│ ├── codex│ │ ├── manuscipt_plots│ │ ├── overview_intensity_images│ │ ├── patch_visualisations│ │ ├── phenotyping│ │ ├── spatial_analysis│ │ └── whole_LN_visualisations│ ├── flow_codex_comparison│ ├── flow_cytometry│ │ ├── lymph_node_sizes_all_conditions│ │ ├── main_conditions│ │ ├── no_cpg_conditions│ │ └── preprocessing│ ├── hematology│ └── tumor_growth_curves│ ├── merged│ ├── per_condition│ └── revision├── overview_of_experiments├── processed│ ├── codex│ │ ├── overview_intensity_images│ │ ├── revision│ │ └── statistics│ ├── flow_cytometry│ │ └── statistics│ ├── hematology│ │ └── statistics│ └── tumor_growth│ ├── metadata│ ├── per_experiment│ └── per_treatment└── raw ├── codex │ ├── data.... (folder per image) ├── flow_cytometry │ ├── cd8_panel │ ├── cd8_panel_prism_export │ ├── early_gates │ ├── pan_immune │ └── pmels_in_blood ├── hematology │ └── per_experiment └── tumor_growth└── Readme.md ACT_melanoma_neutrophil code repository General structure Scripts are sorted by data modality Per modality, scripts are numbered by the order they should be executed in: raw --> processed (script 0) processed data files can be found in the data repository under 'processed' processed --> postprocessing/analysis (script 1..n) postprocessed/analysed files ready for the visualisation scripts can be found in the data repository under 'processed' postprocessing/analysis --> visualisation for manuscript figures (script n+1). figures as .pdf files can be found in the data repository under 'figures' If two scripts/folders have the same number with a different letter (e.g. 2a, 2b), they can be executed in any order. If none of the scripts in a folder have a number, they can be executed in any order. Where applicable, the (sub)figure number in the manuscript has been appended to the file name. Running the code Use either uv sync (preferred) or pip install -r requirements.txt In `helper_files/paths_parameters`, update `data_repo_path` to the saved location of the data repository Then you can start rerunning from anywhere, the data repository has all intermediate files saved. Per analysis, we recommend running it in the numbered order from preprocessing --> analysis --> visualisation. The codex folder additionally contains a zip of a development version of the SPARQ-MI pipeline. This code was used for codex data preprocessing and a draft version of the phenotyping, thereafter manually fine-tuned. A preprint of the pipeline is available at biorxiv. This development version is provided for reproducibility purposes, we recommend users to look at the published version.

Related Organizations
Keywords

central memory CD8+ T cells, Melanoma/immunology, Neutrophils, effector CD8+ T cells, Flow Cytometry/statistics & numerical data, adoptive T cell therapy, Lymph Nodes/immunology, Flow Cytometry/statistics & numerical data, multiplex immunofluorescence imaging

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average