zavolab-pyutils 0.1.1

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: Multiple normalization methods (TMM, TPM, quantile, median)
• 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 .

From conda (after bioconda release)

conda install -c bioconda zavolab_pyutils

Development installation

git clone https://github.com/zavolab/zavolab_pyutils.git
cd zavolab_pyutils
pip install -e ".[dev]"

Quick Start

Library Size Normalization

import numpy as np
from genomic_utils import normalize_by_library_size

# Sample count matrix (genes × samples)
counts = np.array([
    [100, 200, 150],
    [50, 100, 80],
    [200, 400, 300],
])

# Normalize by library size (TMM method)
normalized = normalize_by_library_size(counts, method="tmm")

Annotation Conversion

from genomic_utils import convert_gff_to_gtf

# Convert GFF3 to GTF format
convert_gff_to_gtf("input.gff3", "output.gtf")

Documentation

For detailed documentation, see the docs directory.

Testing

Run the test suite with pytest:

pytest tests/

Run with coverage:

pytest tests/ --cov=src/genomic_utils

Contributing

Contributions are welcome! Please:

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