Each individual GAD disease gene set (i.e. a single disease term followed by a string of genes) or mouse phenotype gene set becomes a candidate for a number of uses and applications including: a) contributing to complex (additive, multiplicative, gene-environment) statistical models for any given disease phenotype [49] [50] [51] [52] [53] ; b) use in comparative analysis of disease between disease phenotypes; c) use in interrogating other related data types, such as microarray (see below), proteomic, or SNP data [54] [55] [56] ; and d) integration into annotation engines [57] or genome browsers Table S7 [47]. [58] or other analytical software to add disease information in comparative genomic analysis. In a sense, each individual human or mouse disease/phenotype gene set becomes a unique hypothesis, testable in a variety of ways. Increasingly, combinations of genes may have important predictive value as combinatorial biomarkers in predicting disease risk as opposed to single candidate genes [59, 60] .