Iris8090/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

📂 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.

🔧 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

💡 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.

📚 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

🙏 Acknowledgments

• —Dataset extracted and converted to .parquet by Iris Lee for use in longevity and immune aging hackathons.
• —Original research by Yang et al., published in Cell Research, provided foundational insights into immune aging.

📁 License

Please refer to the license of the original publication. This conversion is provided for non-commercial research purposes only.