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# 🧬 Single-Cell Transcriptomic Insights into Immune Aging in Human PBMCs
This dataset was extracted from the supplementary tables of the publication:
> **Title**: Single-cell transcriptomic landscape of human immune aging
> **Journal**: Cell Research (Nature Publishing Group), 2021
> **DOI**: [10.1038/s41422-020-00412-6](https://doi.org/10.1038/s41422-020-00412-6)
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## 📂 Dataset Description
The data was extracted using OCR techniques from PDF tables and saved in `.parquet` format for easy use in data science pipelines. Each row typically represents a gene, cell type, or age group comparison across various immune cell subtypes derived from peripheral blood mononuclear cells (PBMCs).
Format:
- **File**: `Immune-Aging-transcriptomic .parquet`
- **Type**: Tabular dataset
- **Structure**: Varies per table; gene names, expression levels, p-values, fold changes, and metadata columns may be present.
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## 🔧 Usage Instructions
### Python (with pandas)
```python
import pandas as pd
df = pd.read_parquet("Immune-Aging-transcriptomic .parquet")
print(df.head())
```
### Use in ML pipelines
- Input for aging clock models
- Feature matrix construction for immune cell classification
- Differential gene expression analysis
---
## 💡 Use Cases
- **Aging Biomarker Discovery**: Identify aging-related genes in immune cells.
- **Comparative Aging Studies**: Use alongside other datasets like Tabula Muris Senis or sc-ImmuAging.
- **Model Benchmarking**: Evaluate immune aging clocks using preprocessed features.
- **Longevity Research**: Investigate immune signatures linked to lifespan and healthspan.
- **Multi-omics Integration**: Combine with telomere, methylation, or proteomic datasets.
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## 📚 Citation
If you use this dataset, please cite the original paper:
> Yang, J., Zheng, Y., Gou, X. et al. Single-cell transcriptomic landscape of human immune aging. *Cell Research* **31**, 1004–1022 (2021).
> [DOI:10.1038/s41422-020-00412-6](https://doi.org/10.1038/s41422-020-00412-6)
---
## 🙏 Acknowledgments
- Dataset extracted and converted to `.parquet` by **Iris Lee** for use in longevity and immune aging hackathons. ### 🧑💻 Team: MultiModalMillenials. Iris Lee (`@iris8090`)
- Original research by Yang et al., published in *Cell Research*, provided foundational insights into immune aging.
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## 📁 License
Please refer to the license of the original publication. This conversion is provided for **non-commercial research purposes only**.
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