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README.md

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+# 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.