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README.md

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+# GSE167186 – Single-Nucleus RNA-Seq of Aged Human Skeletal Muscle
+
+**Organism**: *Homo sapiens*  
+**Tissue**: Human skeletal muscle  
+**Samples**: 23 individuals (young and aged)  
+**Technique**: 10x Genomics single-nucleus RNA-seq  
+**Data Type**: Processed sparse expression matrix and cell metadata  
+
+---
+
+## 🧭 Description
+
+This dataset contains single-nucleus transcriptomes from human skeletal muscle samples spanning young and aged adult individuals. The goal was to understand the molecular changes in muscle cells associated with aging.
+
+Each sample is represented by a `.h5` file in the original dataset, which we have converted into a unified sparse expression matrix and metadata file for easy access and analysis.
+
+---
+
+## 📂 Files Included
+
+- `GSE167186_expression_sparse.parquet`  
+   → Gene expression matrix (sparse, cells × genes), saved using `scipy.sparse.save_npz`
+
+- `GSE167186_metadata.parquet`  
+   → Cell-level metadata, including sample ID and batch assignment
+
+---
+
+## 📥 How to Use
+
+```python
+import pandas as pd
+from scipy import sparse
+
+# Load expression matrix
+X = sparse.load_npz("GSE167186_expression_sparse.parquet")
+
+# Load metadata
+meta = pd.read_parquet("GSE167186_metadata.parquet")
+```
+
+---
+
+## 💡 Use Cases
+
+- Investigating age-related changes in skeletal muscle at single-cell resolution
+- Benchmarking trajectory inference or cell clustering tools
+- Identifying differentially expressed genes between young and aged muscle
+- Studying cell-type-specific transcriptional signatures of human aging
+
+---
+
+## 🔗 Citation
+
+If you use this dataset, please cite:
+
+> Rubenstein et al. (2022). "Single-nucleus transcriptomics of human skeletal muscle reveals molecular signatures of aging." *Nature Aging*. DOI: [10.1038/s43587-022-00221-1](https://doi.org/10.1038/s43587-022-00221-1)
+
+---
+
+## 🙏 Acknowledgments
+
+Original dataset from GEO Accession [GSE167186](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167186).  
+Data curated and converted by Iris Lee as part of the 2025 Longevity x AI Hackathon. ### 🧑‍💻 Team: MultiModalMillenials. Iris Lee (`@iris8090`)