Since 2005, over 1000 human GWAS (genome-wide association study) publications have described genetic associations to a wide range of diseases and traits [1]. However, extending GWAS findings to mechanistic hypotheses about development and disease has been a major ongoing challenge. In particular, the focus on single loci has been confounded by two insights: (i) most GWAS-implicated common alleles and differentially-expressed genes on expression arrays have exhibited modest effect sizes; and (ii) genes function within biological pathways and interact within biological networks [2]. As such, genome-wide data sets are increasingly viewed as foundations for discovering pathways and networks relevant to phenotypes [3]. This trend is vital, given that pathway mechanisms are natural sources for developing strategies to diagnose, treat, and prevent complex diseases. In this context, it is not surprising that pathway-based analyses have exploded in use during the last 3–5 years (Figure 1).
