Finding biologically or clinically significant modules and genes is a major goal of many co-expression analyses. The definition of biological or clinical significance depends on the research question under consideration. Abstractly speaking, we define a gene significance measure as a function GS that assigns a non-negative number to each gene; the higher GSi the more biologically significant is gene i. In functional enrichment analysis, a gene significance measure could indicate pathway membership. In gene knock-out experiments, gene significance could indicate knock-out essentiality. A microarray sample trait T can be used to define a trait-based gene significance measure as the absolute correlation between the trait and the expression profiles, Equation 2. A measure of module significance can be defined as average gene significance across the module genes (Figure 3A). When dealing with a sample trait T, a measure of statistical significance between the module eigengene E and the trait T can be defined, for example, using correlation (Equation 2) or a p-value (Equation 3) obtained from a univariate regression model between E and T. Modules with high trait significance may represent
