Codon Deviation Coefficient: A Novel Measure for Estimating Codon Usage Bias and Its Statistical Significance
Professor ZHANG Zhang and his team at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences (CAS) has developed Codon Deviation Coefficient which is a measure for estimating codon usage bias and its statistical significance without requiring any prior knowledge.
Codon usage bias (CUB) refers to differences in the frequency of occurrence of synonymous codons in coding DNA (defined by Wikipedia). It is believed to be closely related to genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, protein function through natural selection, and etc. Therefore, it is important to accurately measure CUBs.
Codon Deviation Coefficient (CDC), a novel measure for CUB, estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. Prof. ZHANG has published the comparative results on simulated sequences and empirical data recently, where the CDC shown outperformance of the other measuresby providing informative estimates of CUB and its statistical significance.
Prof. ZHANG stated CDC as "promises a significant advance in raw analysis of codon usage, providing the means to better reveal aspects of the historical evolutionary pressures on gene function without the assumptions of underlying reference data sets."
Paper link: http://www.biomedcentral.com/1471-2105/13/43/abstract
Codon usage bias across a range of sequence lengths. Sequences were
simulated with the four non-uniform positional composition sets: Low (panel A), Med-1
(panel B), Med-2 (panel C) and High (panel D).
Contact: Prof. ZHANG Zhang Email: zhangzhang@big.ac.cn
