Immunology produces large amounts of complex and hierarchical data. The overwhelming quantities and complexity of these data present a challenge for immunologists trying to interpret results, extract useful information, and derive new knowledge. Visualization plays an increasingly important role in the process of analyzing and understanding immunological data. We employed two visualization modules - heat map and stack graph, to be embedded in MULTIPRED2, a computational system for antigenic analysis and support of large-scale vaccine studies. We have described two complementary modules that display complex information on antigenic targets from proteins. The heat map enables visualization of large number of HLA variants, their groupings within the supertypes, and identification of antigenic regions within a query protein sequence. The stack graph is an interactive tool that presents predicted immunogenicity of a query protein across multiple HLA supertypes at human population level. The stack graph enables zooming in and out facilitating visualization at desired level of detail. Both visualization tools present a large amount of information in a single graphical display. The goal of visualization tools is to help immunologists and vaccine researchers to gain rapid insight into the data using comprehensive but clear graphic representation and summarization.