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

BMC Bioinformatics

Table 3 Codon usage bias across all possible quantitative relationships among positional GC contents

GC content			Purine content = 0.3			Purine content = 0.5			Purine content = 0.7
1st	2nd	3rd	CDC	Scaled N _c	Scaled N_c'	CDC	Scaled N _c	Scaled N_c'	CDC	Scaled N _c	Scaled N_c'
0.3	0.5	0.7	0.00153	0.34160	0.23472	0.00586	0.24586	0.23332	0.00481	0.39716	0.21314
0.3	0.7	0.5	0.00147	0.15648	0.05716	0.00551	0.04827	0.06330	0.00498	0.24616	0.05866
0.5	0.3	0.7	0.00146	0.36662	0.19363	0.00470	0.20034	0.17544	0.00441	0.34555	0.17306
0.5	0.7	0.3	0.00143	0.35276	0.21224	0.00519	0.19619	0.21974	0.00417	0.34831	0.21815
0.7	0.3	0.5	0.00069	0.21330	0.01419	0.00236	0.02999	0.02692	0.00233	0.16172	0.03574
0.7	0.5	0.3	0.00066	0.38224	0.22121	0.00257	0.22392	0.23947	0.00236	0.33561	0.24588

Sequences with 100000 codons were simulated. The compositions in the Med-1 set (0.3, 0.5 and 0.7) were used. GC content was considered non-uniform at three codon positions, whereas purine content was set uniform at three codon positions. The expected value of codon usage bias is zero so that these estimated values are also the deviations from the expected.

ISSN: 1471-2105