Cancer is caused by alterations to DNA that ultimately are translated into altered proteins with unique amino acid sequences when compared with their counterparts in normal cells. By inference, these altered proteins have the potential to elicit immune responses such as T-cell recognition, if properly presented by the immune system following protein degradation and major histocompatibility complex binding. Historically, identifying tumor-specific mutant antigens was painstaking work that involved molecular cloning and immune screening. This scenario has changed dramatically in the last few years as new sequencing technology combined with computational data analysis can identify the unique tumor peptide sequences, and algorithmic evaluation of these novel peptides can estimate their binding affinity to the major histocompatibility complex haplotypes encoded by each genome. This process can identify unique neoantigens in each cancer, either as a means of characterizing the overall neoantigen load or as a precursor to designing a personalized cancer vaccine. An overview of the data and analysis methods used to identify cancer neoantigens will be presented along with an in-depth consideration of the nuances of each step.