Abstract: This invention relates a series of methods for the visual representation and subsequent application of analyses on complex data sets. In particular, this invention is useful for the analysis of multiple sample sets that share common features, for which similar types of analyses are desired. Three concepts are embodied to aid in this analysis: “Functional equivalence by Algorithmic Polymorphism” (FEAP), in which an analysis algorithm is abstracted through the use of an associated name; a genealogical metaphor for the representation of successive or parallel analysis steps, in which “families” of analyses can be easily copied between different sample data sets; and batch analysis through the creation of multi-sample analysis surrogates (MSAS), which are groups of samples wherein analyses applied to an MSAS is then applied to every sample within the MSAS group.