CodonU: A Python Package for Codon Usage Analysis

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Codon Usage Analysis (CUA) currently relies on diverse, fragmented tools.
• A need exists for a unified, reusable software solution for CUA data handling and analysis pipelines.

Purpose of the Study:

• To develop CodonU, a comprehensive Python package for integrating various aspects of codon usage analysis.
• To provide a compatible and versatile tool for researchers working with CUA data.

Main Methods:

• Developed CodonU as a Python package.
• Integrated statistical measures for nucleotide and protein sequences (e.g., codon adaptation index (CAI), codon bias index (CBI), tRNA adaptation index (tAI), Gravy score).
• Included functionalities for correspondence analysis (COA), graphics generation, and phylogenetic tree development.

Main Results:

• CodonU successfully integrates diverse CUA tools and statistical measures.
• The package is compatible with existing file formats and can be used independently or with other packages.
• Demonstrated capabilities on the Staphylococcus aureus genome.

Conclusions:

• CodonU offers a unified and efficient platform for codon usage analysis.
• The package enhances usability and accessibility for researchers in bioinformatics and genomics.
• CodonU supports multifaceted CUA, from basic statistics to advanced analyses like phylogenetic tree construction.