| --- |
| license: cc-by-nc-nd-4.0 |
| task_categories: |
| - image-segmentation |
| - object-detection |
| - zero-shot-image-classification |
| language: |
| - en |
| pretty_name: Histomorphological Cell Atlas |
| size_categories: |
| - 1M-10M |
| viewable: false |
| viewer: false |
| --- |
| |
| # Histomorphological Atlas of Single Cells across the Human Life Span |
|
|
| A billion-scale single-cell atlas of human tissue from whole-slide histopathology images across 16 organs. This dataset contains cell type densities (cells per mm²), spatial coordinates, morphological phenotypes, and tissue graphs derived from deep learning analysis of H&E-stained tissue sections from 980 donors (ages 20-70) in the GTEx cohort. |
|
|
| ## Dataset Description |
|
|
| We applied deep learning to 14,788 whole-slide H&E images from the GTEx project, detecting and classifying over 3.5 billion single cells. This dataset provides the processed outputs of that pipeline, including per-slide cell type densities, per-cell spatial coordinates, cell type identities, and slide-level tissue graphs. |
|
|
| ### Organs Covered |
|
|
| 16 organs (20 tissue subtypes): Adrenal Gland, Colon (Sigmoid, Transverse), Esophagus (Gastroesophageal Junction, Mucosa, Muscularis), Liver, Lung, Ovary, Pancreas, Prostate, Skin (Sun-Exposed, Not Sun-Exposed), Small Intestine (Terminal Ileum), Spleen, Stomach, Testis, Thyroid, Uterus, Vagina. |
|
|
| ### Contents |
|
|
| | File | Description | |
| |------|-------------| |
| | `16_tissues_cell_abundances.parquet` | Cell type densities (cells per mm²) across all 16 tissues, collapsed by cell phenotype | |
| | *(forthcoming)* Cell polygons | Per-cell spatial polygon coordinates for each slide | |
| | *(forthcoming)* Cell identities | Per-cell type classification for each slide | |
| | *(forthcoming)* Slide graphs | Tissue-level spatial graphs for each slide | |
|
|
| ### Data Format |
|
|
| **`16_tissues_cell_abundances.parquet`** |
| |
| Columns: |
| - `slide_id`: GTEx slide identifier |
| - `organ`: Organ/tissue name |
| - `mpp`: Microns per pixel (image resolution) |
| - `pixels`: Total pixel area analyzed |
| - `cells_pmm2`: Total cell density (cells per mm²) |
| - `endothelial_error_pmm2`: Endothelial segmentation error density (cells per mm²) |
| - Remaining columns: Cell phenotype densities (cells per mm²) — including Hepatocyte/Chromaffin, Connective, Immune, Cuboidal, Muscle, Glandular, Elongated, Glandular (Columnar), Epithelial, Dead, Endothelial, Squamous, Alveolar, Seminiferous, Follicular |
| |
| ### Source Data |
| |
| Whole-slide images and metadata from the GTEx project: |
| - [GTEx Histology Portal](https://gtexportal.org/home/histologyPage) |
| - [GTEx Sampling Site Page](https://gtexportal.org/home/samplingSitePage) |
| |
| GTEx whole-slide images are publicly available from the GTEx portal. Associated donor metadata and transcriptomic data are available through dbGaP under controlled access. |
| |
| ### Pipeline Summary |
| |
| Cells were segmented and classified from whole-slide H&E images using CellViT (SAM-H backbone). Cell phenotyping integrates CellViT morphological features and DINOv2 (ViT-S/14) nuclear features, with PLIP providing text-based guidance, to classify each cell into a phenotype class. |
| |
| ## Citation |
| |
| If you use this dataset, please cite: |
| |
| ``` |
| Abila, E., Zheng, Y., Bago-Horvath, Z. & Rendeiro, A.F. A single-cell view of human |
| tissue aging reveals architectural decline beyond cellular composition. (2026). |
| ``` |
| |
| ## License |
| |
| This dataset is licensed under CC-BY-NC-ND-4.0. |
| |
| ## Contact |
| |
| Andre F. Rendeiro — arendeiro@cemm.oeaw.ac.at |
| |
