SouradiptoC / CodonU

A python project for analysis of codon usage for gene or genome analysis

Introduction

Welcome to CodonU!

This is an integrated package for codon usage analysis. To know more about motivation and workflow, please read the Thesis or the Paper. The documentation is available here.

What's New (As of September 23rd, 2023)

Now you can analyze tRNA adaptation index

Functionalities

Various functionalities can be found below. For gene/genome analysis, this package can:

• For Nucleotide sequences
  • Calculate RSCU
  • Calculate CAI
  • Calculate CBI
  • Calculate ENc
  • Calculate tAI
• For Protein sequences
  • Calculate Aromaticity
  • Calculate gravy

One can also calculate the multivariate analysis, popularly known as correspondence analysis (COA) for the codons easily. Supported calculations are:

• For Nucleotide sequences
  • COA using codon frequency for codons and genes
  • COA using codon RSCU values for codons and genes
• For Protein sequences
  • COA using amino acid frequency with scale set to gravy score
  • COA using amino acid frequency with scale set to aromaticity score

Phylogenetic analysis and tree building now can be done.

Detailed instructions on how to use the functions can be found in the examples

Graphics!!

Also, can generate beautiful graphics for publication purposes or otherwise. Some plots are:

ENc plot for human chromosome 2

Neutrality plot for human chromosome 2

COA of Codon frequency for codons

COA of Codon frequency for genes

Comparative analysis of codon COA

COA of aa frequency for genes with scale set to GRAVY

Examples of other plots can be found in the images

Installation

pip install CodonU

Future Plans

None. If you would like to recommend one, please mail at [e-mail]

Citation

Please cite the article as

@ARTICLE{10330762,
    author={Choudhuri, Souradipto and Sau, Keya},
    journal={IEEE/ACM Transactions on Computational Biology and Bioinformatics}, 
    title={CodonU: A Python Package for Codon Usage Analysis}, 
    year={2024},
    volume={21},
    number={1},
    pages={36-44},
    keywords={Amino acids;Indexes;Bioinformatics;Software;Web servers;Proteins;Phylogeny;Codon bias;codon usage;codon usage analysis;CodonW;correspondence analysis;phylogenetic analysis;tRNA analysis},
    doi={10.1109/TCBB.2023.3335823}
}

Please cite the software as

@software{choudhuri_souradipto_2023_7868197,
    author={Choudhuri, Souradipto},
    title={CodonU},
    month=apr,
    year=2023,
    publisher={Zenodo},
    version={v1.0.4},
    doi={10.5281/zenodo.7868197},
    url={https://doi.org/10.5281/zenodo.7868197}
}

Reference

• J. L. Bennetzen and B. D. Hall, “Codon selection in yeast.,” Journal of Biological Chemistry, vol. 257, no. 6, pp. 3026–3031, Mar. 1982, doi: 10.1016/s0021-9258(19)81068-210.1016/s0021-9258(19)81068-2.
• F. Wright, “The ‘effective number of codons’ used in a gene,” Gene, vol. 87, no. 1, pp. 23–29, Mar. 1990, doi: 10.1016/0378-1119(90)90491-9.
• A. Fuglsang, “The ‘effective number of codons’ revisited,” Biochemical and Biophysical Research Communications, vol. 317, no. 3, pp. 957–964, May 2004, doi: 10.1016/j.bbrc.2004.03.138.
• P. M. Sharp and W.-H. Li, “The codon adaptation index-a measure of directional synonymous codon usage bias, and its potential applications,” Nucleic Acids Research, vol. 15, no. 3, pp. 1281–1295, 1987, doi: 10.1093/nar/15.3.1281.
• J. Kyte and R. F. Doolittle, “A simple method for displaying the hydropathic character of a protein,” Journal of Molecular Biology, vol. 157, no. 1, pp. 105–132, May 1982, doi: 10.1016/0022-2836(82)90515-0.
• J. R. Lobry and C. Gautier, “Hydrophobicity, expressivity and aromaticity are the major trends of amino-acid usage in 999 Escherichia coli chromosome-encoded genes,” Nucleic Acids Research, vol. 22, no. 15, pp. 3174–3180, Aug. 1994, doi: 10.1093/nar/22.15.3174.
• J. R. Lobry, Multivariate Analyses of Codon Usage Biases. ISTE Press - Elsevier, 2018. doi: 10.1016/C2018-0-02165-9.
• F. Sievers and D. G. Higgins, “Clustal Omega for making accurate alignments of many protein sequences,” Protein Science, vol. 27, no. 1, pp. 135–145, Jan. 2018, doi: 10.1002/pro.3290.
• M. A. Larkin et al., “Clustal W and Clustal X version 2.0,” Bioinformatics, vol. 23, no. 21, pp. 2947–2948, Nov. 2007, doi: 10.1093/bioinformatics/btm404.
• Anwar et al., "gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm", Frontiers in Molecular Biosciences, vol. 10, Jul. 2023, doi: 10.3389/fmolb.2023.1218518