Published October 20, 2022
| Version 2022.10.20
Journal article
Open
High-resolution single-cell atlas reveals diversity and plasticity of tumor-associated neutrophils in non-small cell lung cancer
Creators
- Stefan Salcher1
-
Gregor Sturm2
- Lena Horvath1
- Gerold Untergasser1
- Christiane Kuempers3
- Georgios Fotakis2
- Elisa Panizzolo2
- Agnieszka Martowicz1
- Manuel Trebo1
- Georg Pall1
- Gabriele Gamerith1
- Martina Sykora1
- Florian Augustin4
- Katja Schmitz5
- Francesca Finotello6
- Dietmar Rieder2
- Sven Perner3
- Sieghart Sopper1
- Dominik Wolf1
- Andreas Pircher1
- Zlatko Trajanoski2
- 1. Department of Internal Medicine V (Haematology & Oncology), Comprehensive Cancer Center Innsbruck (CCCI) and Tyrolean Cancer Research Institute (TKFI), Medical University of Innsbruck (MUI), Innsbruck, Austria
- 2. Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innrain 80, 6020 Innsbruck, Austria
- 3. Institute of Pathology, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany
- 4. Tyrolpath Obrist Brunhuber GmbH, Zams, Austria
- 5. Department of Visceral, Transplant and Thoracic Surgery, Medical University Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria
- 6. Institute of Molecular Biology, Technikerstrasse 25, University of Innsbruck, Austria
Description
This archive contains all data required to reproduce the single-cell data integration and analysis for the paper
High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer
(https://doi.org/10.1101/2022.05.09.491204 )
In particular, it contains the following files:
- build_atlas_results.tar.xz contains all intermediate result of the first part of the workflow (data integration and annotation). It is also required to run the second part of the workflow without re-running the data integration steps.
- containers.tar.xz contains singularity containers that package all software dependencies required to reproduce the analyses
- core_atlas_scanvi_model.tar.gz contains a scArches model and the corresponding h5ad file (with only highly variable genes). You can use this to project your own data onto the atlas with scArches
- downstream_anslysis_results.tar.xz contains the results from the second part of the workflow, including an executed HTML version of all jupyter and rmarkdown notebooks that were used to derive the figures from the paper
- input_data.tar.xz contains the preprocessed input data (e.g. h5ad files for each individual dataset). It is required to run the first part of the analysis workflow.
If you want to download the atlas to perform you own analyses, please refer to the CZI Cell-x-gene portal. From there, you can download h5ad (scverse) and rds (Seurat) files with standardized metadata.
Files
Files
(159.9 GB)
Additional details
Related works
- Is published in
- Preprint: 10.1101/2022.05.09.491204 (DOI)