Codon Deviation Coefficient: a novel measure for estimating codon usage bias and its statistical significance

BMC Bioinformatics

Table 2 Codon usage bias across a variety of positional background compositions for GC and purine contents

GC Content	Purine Content	CDC	Scaled N_c	Scaled N_c'
None	None	0.00452	0.00001	0.00186
	Low	0.00407	0.04843	0.05557
	Med-1	0.00302	0.15130	0.15968
	Med-2	0.00164	0.28613	0.29389
	High	0.00054	0.40797	0.41146
Low	None	0.00452	0.05505	0.04181
	Low	0.00411	0.09548	0.08752
	Med-1	0.00305	0.19808	0.19091
	Med-2	0.00164	0.31892	0.31461
	High	0.00060	0.44778	0.44199
Med-1	None	0.00486	0.20367	0.17790
	Low	0.00438	0.23485	0.21262
	Med-1	0.00305	0.31876	0.29478
	Med-2	0.00203	0.42851	0.40322
	High	0.00054	0.53585	0.51978
Med-2	None	0.00529	0.38525	0.36068
	Low	0.00460	0.40628	0.38358
	Med-1	0.00337	0.47542	0.43927
	Med-2	0.00182	0.56759	0.52569
	High	0.00056	0.65842	0.62645
High	None	0.00606	0.56671	0.54706
	Low	0.00520	0.59091	0.56666
	Med-1	0.00371	0.65926	0.61789
	Med-2	0.00225	0.71856	0.66928
	High	0.00065	0.77246	0.73600

Sequences with 100000 codons were simulated. The expected value of codon usage bias is zero so that these estimated values are also the deviations from the expected.

ISSN: 1471-2105