longevity-db/Immune-Aging-transcriptomic

🧬 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

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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)

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

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💡 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

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🙏 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.