INteractive Codon usage Analysis (INCA) provides an array of features useful in analysis of synonymous codon usage in whole genomes. In addition to computing codon frequencies and several usage indices, such as codon bias, effective Nc and CAI, the primary strength of INCA has numerous options for the interactive graphical display of calculated values, thus allowing visual detection of various trends in codon usage. Finally, INCA includes a specific unsupervised neural network algorithm, the self-organizing map, used for gene clustering according to the preferred utilization of codons.