دورية أكاديمية
Spatial subsetting enables integrative modeling of oral squamous cell carcinoma multiplex imaging data
| العنوان: | Spatial subsetting enables integrative modeling of oral squamous cell carcinoma multiplex imaging data |
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| المؤلفون: | Einhaus, Jakob, Gaudilliere, Dyani, Hedou, Julien, Feyaerts, Dorien, Ozawa, Michael G., Sato, Masaki, Ganio, Edward A., Tsai, Amy S., Stelzer, Ina A., Bruckman, Karl C., Amar, Jonas N., Sabayev, Maximilian, Bonham, Thomas A., Gillard, Joshua, Diop, Maïgane, Cambriel, Amelie, Mihalic, Zala N., Valdez, Tulio, Liu, Stanley Y., Feirrera, Leticia, Lam, David K., Sunwoo, John B., Schürch, Christian M., Gaudilliere, Brice, Xiaoyuan, Han |
| سنة النشر: | 2023 |
| المجموعة: | Zenodo |
| مصطلحات موضوعية: | Imaging mass cytometry, Integrative modeling, Machine learning, Oral squamous cell carcinoma, Tumor microenvironment, Tumor immunity |
| الوصف: | The following folders/files are part of this repository: Zip-Archive "OSCC-IMC-Einhaus2023" contains all the data and code necessary reproduce all analysis steps: Folder "UOPCohort": Contains all data and code regarding the OSCC cohort collected at UOP. Folder "Dataframes": All output dataframes produced in the script "Analysis_UOP.Rmd". Folder "Metadata": Existing clinical metadata and output files of the folder "Tumormasks". Folder "Steinbock": Raw data and single-cell segmentation output after Steinbock segmentation. Folder "Tumormasks": All scripts necessary to generate tumormasks, measure celldistances from the tumorborder, and calculate zonal areas. Output files are stored in the folder "Metadata". Script "Analysis_UOP.Rmd": Code for cell phenotyping and feature matrix generation. Folder "STACohort": Contains all data and code regarding the OSCC cohort collected at STA. Folder "Dataframes": All output dataframes produced in the script "Analysis_STA.Rmd". Folder "Metadata": Existing clinical metadata and output files of the folder "Tumormasks". Folder "Steinbock": Raw data and single-cell segmentation output after Steinbock segmentation. Folder "Tumormasks": All scripts necessary to generate tumormasks, measure celldistances from the tumorborder, and calculate zonal areas. Output files are stored in the folder "Metadata". Script "Analysis_STA.Rmd": Code for cell phenotyping and feature matrix generation. Folder "AnalysisMultivariate": Code required to reproduce the multivariate model generated. Input data is pulled from the folder "UOPCohort". Folder "Model": Output data produced by the Jupiter notebook "Model.pynb". Folder "stabl": Contains a modified Python package (STABL). Folder "AnalysisUnivariate": Code required to reproduce the univariate analysis of all features. Input files are pulled from the folders "STACohort" and "UOPCohort". Folder "Visualization": Code required to reproduce figure 1-6 and supplemental figures 1-11. Input files for visualization are pulled from the folders "STACohort" and ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| العلاقة: | https://zenodo.org/record/8169946Test; https://doi.org/10.5281/zenodo.8169946Test; oai:zenodo.org:8169946 |
| DOI: | 10.5281/zenodo.8169946 |
| الإتاحة: | https://doi.org/10.5281/zenodo.8169946Test https://doi.org/10.5281/zenodo.8169945Test https://zenodo.org/record/8169946Test |
| حقوق: | info:eu-repo/semantics/openAccess ; https://creativecommons.org/licenses/by/4.0/legalcodeTest |
| رقم الانضمام: | edsbas.F8917C43 |
| قاعدة البيانات: | BASE |
| DOI: | 10.5281/zenodo.8169946 |
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