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cubar  

Codon Usage Bias Analysis
View on CRAN: Click here


Download and install cubar package within the R console
Install from CRAN:
install.packages("cubar")

Install from Github:
library("remotes")
install_github("cran/cubar")

Install by package version:
library("remotes")
install_version("cubar", "1.1.0")



Attach the package and use:
library("cubar")
Maintained by
Hong Zhang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-07-17
Latest Update: 2024-01-09
Description:
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.
How to cite:
Hong Zhang (2023). cubar: Codon Usage Bias Analysis. R package version 1.1.0, https://cran.r-project.org/web/packages/cubar. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.4.0 (2023-07-17 20:00), 0.4.2 (2023-11-18 16:30), 0.5.0 (2024-01-09 05:00), 0.6.0 (2024-07-04 14:50), 1.0.0 (2024-08-01 06:20)
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Maintainer: Qi Qin (view profile)

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