Summary
===========
The redundancy in the genetic code means that apart from methionine and tryptophan, an
amino acid is encoded by at least two codons. Different codons for the same amino acid are
termed synonymous codons. Synonymous codon usage is strongly influenced by evolutionary
forces namely, selection and mutation and may vary strongly within or among organisms The
preference of specific codons over others contributes to this variation and this phenomenon is
called codon usage bias (CUB).
Many measurements have been developed to analyze and study CUB; effective number of
codons ( ENc ) (Wright, 1990), codon adaptation index ( CAI ), relative synonymous codon
usage ( RSCU ) (Sharp & Li, 1987) and, translational selection index ( P2-index ) (Liyuan
Wang & Sun, 2018). Also, statistical analysis has been used to investigate the effect of differ-
ent factors as selection and mutation on shaping CUB such as; Correspondence analysis, Parity
Rule 2-plot Analysis and, Neutrality Plot (Hui Song & Nan, 2017).
BCAW tool was developed to analyze such phenomena ( Codon Usage Bias ) by the aforementioned measurements. Various tools are available to analyze and measure CUB, but they lack some important measurements and plots for CUB analysis. What BCAW tool does is an automated workflow to
study the CUB of an organism’s genes by all the measurements and plots mentioned above.
Further, using the correlation method to determine the optimal codons described by (Hersh-
berg & Petrov, 2009) is implemented for the first time in the BCAW tool. The tool also includes
statistical analysis such as correspondence analysis, correlation analysis, and t-test.