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cubar

Overview

cubar is a package for codon usage bias analysis in R. Main features are as follows:

• Codon level analyses
  • Calculate tRNA weights;
  • Calculate relative synonymous codon usage (RSCU);
  • Machine learning-based inference of optimal codons;
  • Visualization codon-anticodon pairing relationships;
• Gene level analyses
  • Tabulate codon frequency of each coding sequence;
  • Measure codon usage similarity to highly expressed genes with Codon Adaptation Index (CAI);
  • Quantify the influnce of codon usage on mRNA stability with Mean Codon Stabilization Coefficients (CSCg);
  • Measure codon usage bias with the nonparametric index Effective number of codons (ENC);
  • Measure the fraction of pre-determined optimal codons (Fop) in each sequence;
  • Overall GC content (GC) or that of 3rd synonymous positions (GC3s) or 4-fold degenerate sites (GC4d);
  • Quantify whether codon usage matches tRNA availability using tRNA Adaptation Index (tAI);
• Utilities
  • Sliding window analysis of codon usage within a coding sequence;
  • Optimize codon usage based on optimal codons for heterologous expression;
  • Test differential usage of codons between two sets of sequences;

Main advantages of cubar are as follows: - Process large datasets (>10,0000 sequences) efficiently using the Biostrings and data.table backends; - Support genetic codes cataloged by NCBI as well as custom ones; - Integrate with other data analysis or bioinformatic packages in the R ecosystem;

Dependencies

Depends

• R (>= 4.1.0)

Imports

• Biostrings (>= 2.60.0),
• IRanges (>= 2.34.0),
• data.table (>= 1.14.0),
• ggplot2 (>= 3.3.5),
• rlang (>= 0.4.11)

Installation

The latest release of cubar can be installed with:

install.packages("cubar")

The latest developmental version of cubar can be installed with:

devtools::install_github("mt1022/cubar", dependencies = TRUE)

Usage

Documentation can be found within R (by typing ?function_name). The following tutorials are available from our website:

• Get Started: A brief introduction demonstrating the basic usage of cubar;
• Non-standard Genetic Code: How to use cubar with non-standard genetic codes;
• Theories behind cubar: The mathematical details behind the core functions in cubar;

Getting help

Please use GitHub issues for bug reports, questions, and feature requests.

Suggests

• Biostrings for sequence input/output and manipulation;
• Peptides for peptide- or protein-related indices;

Acknowledgements

GitHub Copilot was used to suggest code snippets in the development of this package. Thanks the GitHub Education teacher program for providing free access to GitHub Copilot.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.