| # A Single-Cell Transcriptomic Atlas of Human Skin Aging | |
| This dataset contains structured tables extracted from the supplementary materials of the publication: | |
| > **"A single-cell transcriptomic atlas of human skin aging"** | |
| > *Cell Reports, 2020* | |
| > DOI: [10.1016/j.celrep.2020.108132](https://doi.org/10.1016/j.celrep.2020.108132) | |
| The data has been processed from the publication PDF into a `.parquet` file to facilitate downstream analysis and integration into machine learning workflows. | |
| --- | |
| ## 📦 Dataset Description | |
| The dataset includes multiple tables capturing aging-related transcriptomic changes in human skin tissue at the single-cell level. Tables were extracted using PDF parsing tools and contain gene expression summaries and annotations useful for skin biology and aging research. | |
| --- | |
| ## 🔧 Usage Instructions | |
| To load the Parquet file in Python: | |
| ```python | |
| import pandas as pd | |
| df = pd.read_parquet("skin_aging_data.parquet") | |
| print(df.head()) | |
| ``` | |
| --- | |
| ## 🚀 Use Cases | |
| - Aging biomarker discovery in dermal and epidermal compartments | |
| - Training skin-specific biological age predictors | |
| - Integrating skin aging profiles with other tissue atlases | |
| - Cross-species comparison of skin aging signatures | |
| - Evaluation of anti-aging interventions at single-cell resolution | |
| --- | |
| ## 📖 Citation | |
| If you use this dataset, please cite: | |
| **Xie, W., et al.** *A single-cell transcriptomic atlas of human skin aging*. Cell Reports, 2020. | |
| DOI: [10.1016/j.celrep.2020.108132](https://doi.org/10.1016/j.celrep.2020.108132) | |
| --- | |
| ## 🙏 Acknowledgments | |
| This dataset was curated and converted by **Iris Lee** for open access machine learning research in aging biology and skin regeneration. ### 🧑💻 Team: MultiModalMillenials. Iris Lee (`@iris8090`) | |
| Source publication by Xie et al. (2020) — Cell Reports. | |