Understanding heterogeneity in adaptive immune responses is essential to dissect pathways of memory B and T cell differentiation and to define correlates of protective immunity. Traditionally, immunologists have deconvoluted this heterogeneity with flow cytometry—with combinations of markers to define signatures that represent specific lineages, differentiation states, and functions. Genome-scale technologies have become widely available and provide the ability to define expression signatures—sets of genes—that represent discrete biological properties of cell populations. Because genomic signatures can serve as surrogates of a phenotype, function, or cell state, they can integrate phenotypic information between experiments, cell types, and species. Here, we discuss how integration of well-defined expression signatures across experimental conditions together with functional analysis of their component genes could provide new opportunities to dissect the complexity of the adaptive immune response and map the immune response to vaccines and pathogens.