clibas 0.4.4

Combinatorial Library Analysis Suite: analysis of NGS data from genetically encoded libraries

clibas

Welcome to clibas – a Python package for analyzing NGS data from combinatorial genetically encoded libraries, including techniques like mRNA/phage/yeast display and SELEX selections. The library provides fast and scalable tools for parsing, filtering, and analyzing .fastq files at both DNA and translated peptide levels, with a high-level API to build sophisticated analysis pipelines in just a few lines of code.

Documentation & examples

For full documentation, including a tutorial, API reference, and jupyter notebook examples, please visit our Read the Docs page. Example .ipynb notebooks are also available in this repo in docs\source\examples

Quick start

It is recommended that clibas is installed in a dedicated virtual environment to avoid potential version conflicts with existing packages. Any virtual environment (e.g., conda or pipenv) will work for this purpose.

The library can be installed from PyPI:

pip install clibas[ml]

This will also install scikit-learn, rdkit, umap-learn, hdbscan, plotly, and h5py packages. These libraries are used to run UMAP–HDBSCAN sequence embedding and clustering analyses. If these capabilities are not required, a lightweight package can be installed like this:

pip install clibas

Contact

To report bugs, seek technical assistance, and general correspondence, please contact Alex Vinogradov at [e-mail], or here on github.

Any contributions – code, feature requests, jupyter notebooks – are welcome!

Links

Project on GitHub Documentation Accompanying paper: link tbd
Vinogradov Lab at NUS

Citation

If you use clibas, please cite the accompanying publication: tbd / link tbd