cubar: Codon Usage Bias Analysis

A suite of functions for rapid and flexible analysis of codon usage bias. It provides in-depth analysis at the codon level, including relative synonymous codon usage (RSCU), tRNA weight calculations, machine learning predictions for optimal or preferred codons, and visualization of codon-anticodon pairing. Additionally, it can calculate various gene- specific codon indices such as codon adaptation index (CAI), effective number of codons (ENC), fraction of optimal codons (Fop), tRNA adaptation index (tAI), mean codon stabilization coefficients (CSCg), and GC contents (GC/GC3s/GC4d). It also supports both standard and non-standard genetic code tables found in NCBI, as well as custom genetic code tables.

Version: 0.5.0
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)
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-01-09
Author: Hong Zhang ORCID iD [aut, cre, cph]
Maintainer: Hong Zhang < at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: cubar results


Reference manual: cubar.pdf
Vignettes: Introduction


Package source: cubar_0.5.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): cubar_0.5.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): cubar_0.5.0.tgz, r-oldrel (x86_64): not available
Old sources: cubar archive


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