Editing Codon usage bias (section)

== Methods of analysis ==

In the field of [[bioinformatics]] and [[computational biology]], many statistical methods have been proposed and used to analyze codon usage bias.<ref name="pmid9732453">{{cite journal |vauthors=Comeron JM, Aguadé M | title = An evaluation of measures of synonymous codon usage bias | journal = J. Mol. Evol. | volume = 47 | issue = 3 | pages = 268–74 |date=September 1998 | pmid = 9732453 | doi = 10.1007/PL00006384 | bibcode = 1998JMolE..47..268C | s2cid = 21862217 }}</ref> Methods such as the 'frequency of optimal codons' (Fop),<ref name="pmid6175758">{{cite journal | author = Ikemura T | title = Correlation between the abundance of Escherichia coli transfer RNAs and the occurrence of the respective codons in its protein genes: a proposal for a synonymous codon choice that is optimal for the E. coli translational system. | journal = J. Mol. Biol. | volume = 151 | issue = 3 | pages = 389–409 |date=September 1981 | pmid = 6175758 | doi = 10.1016/0022-2836(81)90003-6}}</ref> the relative codon adaptation (RCA)<ref name="pmid20453079">{{cite journal |vauthors=Fox JM, Erill I | title = Relative codon adaptation: a generic codon bias index for prediction of gene expression | journal = DNA Res. | volume = 17 | issue = 3 | pages = 185–96 |date=June 2010 | pmid = 20453079 | doi = 10.1093/dnares/dsq012 | url= | pmc=2885275}}</ref> or the [[Codon Adaptation Index|codon adaptation index]] (CAI)<ref name=SharpLi1987>{{cite journal|last1=Sharp|first1=Paul M.|author-link1=Paul M. Sharp|last2=Li|first2=Wen-Hsiung|title=The codon adaptation index-a measure of directional synonymous codon usage bias, and its potential applications|journal=[[Nucleic Acids Research]]|volume=15|issue=3|year=1987|pages=1281–1295|pmid=3547335|pmc=340524|doi=10.1093/nar/15.3.1281}}</ref> are used to predict gene expression levels, while methods such as the '[[effective number of codons]]' (Nc) and [[Shannon entropy]] from [[information theory]] are used to measure codon usage evenness.<ref name="urlCodon usage indices">{{cite web | url = http://codonw.sourceforge.net/Indices.html | title = Codon usage indices | author = Peden J | date = 2005-04-15 | work = Correspondence Analysis of Codon Usage | publisher = SourceForge  | access-date = 2010-10-20 }}</ref> Multivariate statistical methods, such as [[correspondence analysis]] and [[principal component analysis]], are widely used to analyze variations in codon usage among genes.<ref name="pmid18940873">{{cite journal |vauthors=Suzuki H, Brown CJ, Forney LJ, Top EM | title = Comparison of correspondence analysis methods for synonymous codon usage in bacteria | journal = DNA Res. | volume = 15 | issue = 6 | pages = 357–65 |date=December 2008 | pmid = 18940873 | pmc = 2608848 | doi = 10.1093/dnares/dsn028 }}</ref> There are many computer programs to implement the statistical analyses enumerated above, including CodonW, GCUA, INCA, etc. Codon optimization has applications in designing synthetic genes and [[Dna vaccines|DNA vaccines]]. Several software packages are available online for this purpose (refer to external links).{{cn|date=November 2023}}