A statistical approach for the analysis of synonymous codon signatures (ASCS) maps codon bias onto a functional network of gene categories. These scripts are used to identify codon-biased genes in Saccharomyces cerevisiae (S288C strain) using binomial distribution and GC3 as a covariate, and map the codon bias signatures onto the functional network of genes using canonical correlation analysis (CCA). Required data and functions are provided in the 'Data' and 'Functions' folders, respectively. Files must be run in the order specified by their numbers. For details, see our publication at ... This work was financially supported by the National Institutes of Health (ES026856, ES031529, GM070641, ES024615, ES002109), the National Research Foundation of Singapore through the Singapore-MIT Alliance for Research and Technology Antimicrobial Resistance Interdisciplinary Research Group, and the Agilent Foundation.