🧬 Gene Expression Analysis (scRNA-seq)

This project performs a basic single-cell RNA-seq (scRNA-seq) analysis using Python and the Scanpy library. It includes steps for preprocessing, clustering, visualization, and marker gene detection.

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📁 Project Structure

gene_project/ ├── data/ # Contains the .h5 dataset (download manually) ├── results/ # Stores generated plots and outputs ├── script.py # Main analysis script ├── gene_expression_analysis.py # Alternative or extended script ├── Requirement.txt # List of Python dependencies

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📥 Dataset

Download the sample dataset from 10x Genomics:

📎 PBMC 3k filtered_feature_bc_matrix.h5 (HDF5)

Save this file into the data/ folder and rename it if needed (e.g., your_file.h5).

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▶️ How to Run

1. Install required packages:

   pip install -r Requirement.txt
   

2. Run the analysis:

   python script.py
   
   

🔬 Pipeline Steps

• Load and filter scRNA-seq data
• Normalize and transform
• PCA + UMAP for visualization
• Cluster with Leiden algorithm
• Detect marker genes

📊 Outputs

• UMAP plot of clusters
• PCA plot
• Marker gene heatmap

🧠 Extensions

• Add sample comparison (e.g. healthy vs diseased)
• Train ML model for cell type classification

👨‍💻 Author

Gaurav More