| # A Single-Cell Transcriptomic Atlas of Human Skin Aging |
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| This dataset contains structured tables extracted from the supplementary materials of the publication: |
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| > **"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) |
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| The data has been processed from the publication PDF into a `.parquet` file to facilitate downstream analysis and integration into machine learning workflows. |
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| ## 📦 Dataset Description |
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| 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. |
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| ## 🔧 Usage Instructions |
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| To load the Parquet file in Python: |
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| ```python |
| import pandas as pd |
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| df = pd.read_parquet("skin_aging_data.parquet") |
| print(df.head()) |
| ``` |
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| ## 🚀 Use Cases |
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| - 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 |
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| ## 📖 Citation |
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| If you use this dataset, please cite: |
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| **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) |
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| ## 🙏 Acknowledgments |
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| 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`) |
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| Source publication by Xie et al. (2020) — Cell Reports. |
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