Cytosine methylation as a reversible chromatin mark has been investigated extensively for its influence on gene silencing and the regulation of its dynamic association–disassociation at specific sites within a eukaryotic genome. With the remarkable reductions in cost and time associated with whole-genome DNA sequence analysis, coupled with the high fidelity of bisulfite-treated DNA sequencing, single nucleotide resolution of cytosine methylation repatterning within even very large genomes is increasingly achievable. What remains a challenge is the analysis of genome-wide methylome datasets and, consequently, a clear understanding of the overall influence of methylation repatterning on gene expression or vice versa. Reported data have sometimes been subject to stringent data filtering methods that can serve to skew downstream biological interpretation. These complications derive from methylome analysis procedures that vary widely in method and parameter setting. DNA methylation as a chromatin feature that influences DNA stability can be dynamic and rapidly responsive to environmental change. Consequently, methods to discriminate background “noise” of the system from biological signal in response to specific perturbation is essential in some types of experiments. We describe numerous aspects of whole-genome bisulfite sequence data that must be contemplated as well as the various steps of methylome data analysis which impact the biological interpretation of the final output.