# Liver Annotation
Liver Annotation is a Python package designed to annotate clusters in single-cell RNA sequencing (scRNA-seq) data from liver samples. This package provides a machine learning model that is specifically trained on liver cells, enabling out-of-the-box functionality without the need for pre-existing expert-annotated data.
## Features
- Machine learning model trained specifically on liver cells.
- Supports both neural network and random forest classifier models.
- Annotates clusters using either the most common annotation or probability-based methods.
## Installation
To install the package, use pip:
```bash
pip install liver_annotation
```
## Usage
### Classification of Cells
You can classify cells by cell type using the classify_cells function. The function requires an input in_data which is a standard scanpy/anndata object with gene expression data.
```python
from liver_annotation import classify_cells
# Example usage
classify_cells(ann_data_obj, species="human", model_type="nn")
```
- `species`: Choose between `"human"` or `"mouse"`.
- `model_type`: Choose between `"rfc"` (random forest classifier) or `"nn"` (neural network).
### Cluster Annotation
Annotate clusters using the cluster_annotations function. This function requires an input in_data and allows you to specify the clustering algorithm and model type.
```python
from liver_annotation import cluster_annotations
# Example usage
cluster_annotations(in_data, species="human", clusters="louvain", algorithm="mode", model_type="nn")
```
- `clusters`: The column in `in_data.obs` to use for cluster data.
- `algorithm`: Choose between `"mode"` or `"prob"` for cluster annotation.
- `model_type`: Choose between `"rfc"` or `"nn"`.
## Dependencies
- `torch`
- `joblib`
- `scipy`
- `numpy`
- `scanpy`
## License
This project is licensed under the MIT License - see the LICENSE file for details.
## Contributing
Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.
## Contact
For any questions or issues, please contact Madhavendra Thakur at madhavendra.thakur@gmail.com.
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"description": "# Liver Annotation\r\n\r\nLiver Annotation is a Python package designed to annotate clusters in single-cell RNA sequencing (scRNA-seq) data from liver samples. This package provides a machine learning model that is specifically trained on liver cells, enabling out-of-the-box functionality without the need for pre-existing expert-annotated data.\r\n\r\n## Features\r\n\r\n- Machine learning model trained specifically on liver cells.\r\n- Supports both neural network and random forest classifier models.\r\n- Annotates clusters using either the most common annotation or probability-based methods.\r\n\r\n## Installation\r\n\r\nTo install the package, use pip:\r\n\r\n```bash\r\npip install liver_annotation\r\n```\r\n\r\n## Usage\r\n\r\n### Classification of Cells\r\n\r\nYou can classify cells by cell type using the classify_cells function. The function requires an input in_data which is a standard scanpy/anndata object with gene expression data.\r\n\r\n```python\r\nfrom liver_annotation import classify_cells\r\n\r\n# Example usage\r\nclassify_cells(ann_data_obj, species=\"human\", model_type=\"nn\")\r\n```\r\n\r\n- `species`: Choose between `\"human\"` or `\"mouse\"`.\r\n- `model_type`: Choose between `\"rfc\"` (random forest classifier) or `\"nn\"` (neural network).\r\n\r\n### Cluster Annotation\r\n\r\nAnnotate clusters using the cluster_annotations function. This function requires an input in_data and allows you to specify the clustering algorithm and model type.\r\n\r\n```python\r\nfrom liver_annotation import cluster_annotations\r\n\r\n# Example usage\r\ncluster_annotations(in_data, species=\"human\", clusters=\"louvain\", algorithm=\"mode\", model_type=\"nn\")\r\n```\r\n\r\n- `clusters`: The column in `in_data.obs` to use for cluster data.\r\n- `algorithm`: Choose between `\"mode\"` or `\"prob\"` for cluster annotation.\r\n- `model_type`: Choose between `\"rfc\"` or `\"nn\"`.\r\n\r\n## Dependencies\r\n\r\n- `torch`\r\n- `joblib`\r\n- `scipy`\r\n- `numpy`\r\n- `scanpy`\r\n\r\n## License\r\n\r\nThis project is licensed under the MIT License - see the LICENSE file for details.\r\n\r\n## Contributing\r\n\r\nContributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.\r\n\r\n## Contact\r\n\r\nFor any questions or issues, please contact Madhavendra Thakur at madhavendra.thakur@gmail.com.\r\n\r\n",
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