zavolab-pyutils 0.1.2

Genomic data analysis utilities from Zavolan Lab

zavolab_pyutils

Genomic data analysis utilities from the Zavolan Lab. A collection of Python utilities for common bioinformatics tasks including library size normalization, annotation conversion, and other genomic data analysis operations.

Features

• Library Size Normalization: Deseq2-like normalization
• Annotation Conversion: Convert between GTF and GFF3 formats
• Genomic Data Processing: Utilities for working with genomic annotation files

Installation

From source

git clone https://github.com/zavolab/zavolab_pyutils.git
cd zavolab_pyutils
pip install -e .

With conda environment

Create a conda environment from the provided environment.yml file:

conda env create -f environment.yml
conda activate zavolab_pyutils

The environment automatically installs the package and all dependencies including ipykernel for Jupyter notebook support.

From PyPI (TO DO)

pip install zavolab_pyutils

From bioconda (TO DO)

conda install -c bioconda zavolab_pyutils

Quick Start

Library Size Normalization

import pandas as pd
from zavolab_pyutils.read_count_data_analysis import deseq2_normalize

# Create sample count matrix (genes × samples) as a DataFrame
data = {
    "Sample_1": [100, 50, 200],
    "Sample_2": [200, 100, 400],
    "Sample_3": [150, 80, 300],
}
counts_df = pd.DataFrame(data, index=["Gene_1", "Gene_2", "Gene_3"])

# Normalize using DESeq2 method
norm_counts_df, size_factors_df = deseq2_normalize(
    counts_df, 
    sample_list=["Sample_1", "Sample_2", "Sample_3"]
)

print(norm_counts_df)
print(size_factors_df)

Documentation and examples of usage

For detailed documentation, see the docs directory. TO DO

For a working example, see test_module.ipynb which demonstrates the deseq2_normalize function with sample data.

Testing TO DO

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/new-feature)
3. Commit your changes (git commit -m 'Add new feature')
4. Push to the branch (git push origin feature/new-feature)
5. Open a Pull Request

Please ensure all tests pass and add new tests for new functionality.

Citation

If you use zavolab_pyutils in your research, please cite:

TODO: Add citation information

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For issues, questions, or suggestions, please open an issue on GitHub.

Acknowledgments

Developed by the Zavolan Lab at the University of Basel.