Prokaryotic genomic sequence data provides a rich resource for bioinformatic analytic algorithms. Information can be extracted in many ways from the sequence data. One often overlooked process involves investigating an organism’s codon usage. Degeneracy in the genetic code leads to multiple codons coding for the same amino acids. Organism’s often preferentially utilize specific codons when coding for an amino acid. This biased codon usage can be a useful trait when predicting a gene’s expressivity or whether the gene originated from horizontal transfer. There can be multiple biases at play in a genome causing errors in the predictive process. For this reason it is important to understand the interplay of multiple biases in an organism’s genome. We present here new techniques in the measurement and analysis of multiple biases in prokaryotic genomic data. Included is a visualization technique aimed at demonstrating genomic adherence to a set of discrete biases.