Spatial-Immune Multi-omics Refines Prognostication in Early-Stage Estrogen Receptor-Positive Breast Cancer
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| Formato: | Recurso digital |
| Lenguaje: | inglés |
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Zenodo
2025
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| _version_ | 1866902048732086272 |
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| author | Kinsella, Zak |
| author_facet | Kinsella, Zak |
| contents | <p>Raw CSV files containing source data for the modalities used in the corresponding study. A brief description of each CSV file:<br>(1) 'TAILORx_Patient_TIL' contains percentages ('_per_pos') and densities for subject-level queries.<br>(2) 'TAILORx_Patient_TIL_SingleCell' contains information on Euclidean pairwise distances of each detected phenotype, and distances of each phenotype from an epithelial boundary (i.e. tumour mask). </p> <p>(3) 'TAILORx_Patient_TIL_Omics' contains information on ROI-level immune counts and z-score normalised genes for stroma (TME) and epithelia (tumour) for each available patient. As one TMA core was used per patient for this analysis, proteomics immune phenotype percentages and densities for that core are attached. </p> <p>(4) 'TAILORx_Patient_CD8_IHC' contains information on CD8 IHC data for whole-slide images. </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17288210 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Spatial-Immune Multi-omics Refines Prognostication in Early-Stage Estrogen Receptor-Positive Breast Cancer Kinsella, Zak <p>Raw CSV files containing source data for the modalities used in the corresponding study. A brief description of each CSV file:<br>(1) 'TAILORx_Patient_TIL' contains percentages ('_per_pos') and densities for subject-level queries.<br>(2) 'TAILORx_Patient_TIL_SingleCell' contains information on Euclidean pairwise distances of each detected phenotype, and distances of each phenotype from an epithelial boundary (i.e. tumour mask). </p> <p>(3) 'TAILORx_Patient_TIL_Omics' contains information on ROI-level immune counts and z-score normalised genes for stroma (TME) and epithelia (tumour) for each available patient. As one TMA core was used per patient for this analysis, proteomics immune phenotype percentages and densities for that core are attached. </p> <p>(4) 'TAILORx_Patient_CD8_IHC' contains information on CD8 IHC data for whole-slide images. </p> |
| title | Spatial-Immune Multi-omics Refines Prognostication in Early-Stage Estrogen Receptor-Positive Breast Cancer |
| url | https://doi.org/10.5281/zenodo.17288210 |