# BioBatchNet
## Installation
### Clone the Repository
Clone the repository to your local machine:
```bash
git clone https://github.com/Manchester-HealthAI/BioBatchNet](https://github.com/Manchester-HealthAI/BioBatchNet
```
### Set Up the Environment
Create a virtual environment and install dependencies using `environment.yml`:
#### Using Conda:
```bash
conda env create -f environment.yml
conda activate bbn
```
## BioBatchNet Usage
### Enter BioBatchNet
```bash
cd BioBatchNet
```
### Construct dataset
For the IMC dataset, place the dataset inside:
```bash
mv <your-imc-dataset> Data/IMC/
```
For scRNA-seq data, create a folder named `gene_data` inside the `Data` directory and place the dataset inside:
```bash
mkdir -p Data/gene_data/
mv <your-scrna-dataset> Data/scRNA-seq/
```
### Batch effect correction
**For IMC Data**
To process **IMC** data, run the following command to train BioBatchNet:
```bash
python imc.py -c config/IMC/IMMUcan.yaml
```
**For scRNA-seq Data**
To process **scRNA-seq** data, modify the dataset, run the following command to train BioBatchNet:
```bash
python scrna.py -c config/IMC/macaque.yaml
```
## CPC Usage
CPC utilizes the **embedding output from BioBatchNet** as input. The provided sample data consists of the **batch effect corrected embedding of IMMUcan IMC data**.
To use CPC, ensure you are running in the **same environment** as BioBatchNet.
All experiment results can be found in the following directory:
```bash
cd CPC/IMC_experiment
```
✅ **Key Notes**:
- CPC requires embeddings from BioBatchNet as input.
- Sample data includes batch-corrected IMMUcan IMC embeddings.
- Ensure the **same computational environment** as BioBatchNet before running CPC.
## 📂 Data Download Link
To use BioBatchNet for **batch effect correction**, you need to download the corresponding dataset and place it in the appropriate directory.
### **🔹 Download scRNA-seq Data**
The **scRNA-seq dataset** is available on OneDrive. Click the link below to download:
🔗 [Download scRNA-seq Data](https://drive.google.com/drive/folders/1m4AkNc_KMadp7J_lL4jOQj9DdyKutEZ5?usp=sharing)
### **🔹 Download IMC Data**
The **IMC dataset** can be accessed from the **Bodenmiller Group IMC datasets repository**. Visit the link below to explore and download the datasets:
🔗 [IMC Datasets - Bodenmiller Group](https://github.com/BodenmillerGroup/imcdatasets)
## To Do List
- [x] Data download link
- [ ] Checkpoint
- [ ] Benchmark method results
## License
This project is licensed under the MIT License. See the LICENSE file for details.
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"description": "# BioBatchNet\n\n## Installation\n### Clone the Repository\n\nClone the repository to your local machine:\n\n```bash\ngit clone https://github.com/Manchester-HealthAI/BioBatchNet](https://github.com/Manchester-HealthAI/BioBatchNet\n```\n\n### Set Up the Environment\n\nCreate a virtual environment and install dependencies using `environment.yml`:\n\n#### Using Conda:\n\n```bash\nconda env create -f environment.yml\nconda activate bbn\n```\n\n## BioBatchNet Usage\n\n### Enter BioBatchNet\n```bash\ncd BioBatchNet\n```\n\n### Construct dataset\nFor the IMC dataset, place the dataset inside:\n\n```bash\nmv <your-imc-dataset> Data/IMC/\n```\n\nFor scRNA-seq data, create a folder named `gene_data` inside the `Data` directory and place the dataset inside:\n\n```bash\nmkdir -p Data/gene_data/\nmv <your-scrna-dataset> Data/scRNA-seq/\n```\n\n### Batch effect correction\n\n**For IMC Data**\nTo process **IMC** data, run the following command to train BioBatchNet:\n```bash\npython imc.py -c config/IMC/IMMUcan.yaml\n```\n\n**For scRNA-seq Data**\nTo process **scRNA-seq** data, modify the dataset, run the following command to train BioBatchNet:\n```bash\npython scrna.py -c config/IMC/macaque.yaml\n```\n\n## CPC Usage\n\nCPC utilizes the **embedding output from BioBatchNet** as input. The provided sample data consists of the **batch effect corrected embedding of IMMUcan IMC data**.\n\nTo use CPC, ensure you are running in the **same environment** as BioBatchNet. \nAll experiment results can be found in the following directory:\n\n```bash\ncd CPC/IMC_experiment\n```\n\n\u2705 **Key Notes**: \n- CPC requires embeddings from BioBatchNet as input. \n- Sample data includes batch-corrected IMMUcan IMC embeddings. \n- Ensure the **same computational environment** as BioBatchNet before running CPC. \n\n## \ud83d\udcc2 Data Download Link\n\nTo use BioBatchNet for **batch effect correction**, you need to download the corresponding dataset and place it in the appropriate directory.\n\n### **\ud83d\udd39 Download scRNA-seq Data**\nThe **scRNA-seq dataset** is available on OneDrive. Click the link below to download:\n\n\ud83d\udd17 [Download scRNA-seq Data](https://drive.google.com/drive/folders/1m4AkNc_KMadp7J_lL4jOQj9DdyKutEZ5?usp=sharing)\n\n### **\ud83d\udd39 Download IMC Data**\nThe **IMC dataset** can be accessed from the **Bodenmiller Group IMC datasets repository**. Visit the link below to explore and download the datasets:\n\n\ud83d\udd17 [IMC Datasets - Bodenmiller Group](https://github.com/BodenmillerGroup/imcdatasets)\n\n\n## To Do List\n\n- [x] Data download link\n- [ ] Checkpoint\n- [ ] Benchmark method results\n\n## License\n\nThis project is licensed under the MIT License. See the LICENSE file for details.\n\n",
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