de Jong S et al. BMC Genomics 2010, 11:20 http://www.biomedcentral.com/1471-2164/11/20 Zhang and Horvath to choose the power (beta = 8) [29]. One advantage of soft thresholding is that it leads to net- works that are highly robust with respect to different soft- thresholds (beta). In particular, our findings remained vir- tually unchanged for different choices of beta. Soft thresh- olding resulted in a 5,000 × 5,000 dimensional weighted adjacency matrix containing pairwise connection strengths. Next, a connectivity measure (k) per probe was calculated by summing the connection strengths with other network genes. Since module genes tend to be highly connected, we restricted the module detection ana- lysis to genes that had relatively high connectivity. We chose a connectivity threshold of 0.1, which resulted in 2,795 probes for the module detection analyses. Module detection We define co-expression modules as branches of a hier- archical clustering tree. Specifically, we used average link- age hierarchical clustering with the topological overlap similarity measure to define a cluster tree. The topologi- cal overlap is a robust measure of interconnectedness, which keeps track of shared patterns of connection strengths [29,31-33]. For branch cutting (module detection) we used the dynamic branch-cutting algorithm implemented in the dynamicTreeCut and WGCNA (weighted gene co- expression network analysis) R library [26,34]. Each module (or branch) is assigned a unique color label which is visualized in the color band underneath the cluster tree (see Figure 1). We found 10 modules, each of which contained at least 50 probes. Our module detection method followed the standard WGCNA approach that has been successfully used in multiple applications [8,25,26,29,35]. Since our modules are large and distinct, we expect them to be found by many alter- native detection methods. Average gene expression levels of all modules range from 8.52 to 9.51. Page 3 of 14 Modules related to strain and brain region To identify modules that are related to the sample traits of interest - here mouse strain status (A/J versus C57BL/6J) and brain region (amygdala versus hippocam- pus) - we correlated the sample traits with a representa- tive measure of each module. To define a representative module expression profile (referred to as the module eigengene), we summarized the (standardized) gene expression profiles of the module by their first principal component. The module eigengene can be considered a weighted average of the module gene expression profiles. The correlation between the eigengene module and the sample trait of interest (e.g. brain region status) is referred to as eigengene significance. A standard correla- tion test can be used to assess the statistical significance (p-value) of the eigengene significance. Our module- based analysis has a major advantage over a standard differential gene expression analysis: since it only relates a handful of modules to the sample trait, the module- based analysis circumvents the multiple comparison problem that plagues standard gene-based analyses (that relate thousands of probes to the sample trait). We found a highly significant correlation between the Magenta module eigengene (based on 76 probes) and strain status (r = 0.99, p < 1.0e-29). This shows that the Magenta module is comprised of genes that are highly differentially expressed between the two strains. Strik- ingly, we found that brain region status (amygdala ver- sus hippocampus) was highly correlated with both the Red module (r = -0.99, p = 1.8e-29, 198 probes,) and the Pink module (r = -0.81, p = 4.4e-09, 84 probes) eigengenes. All of these p-values remain highly signifi- cant even after carrying out the most stringent multiple comparison adjustment (Bonferroni correction) for the number of modules. Figure 1 Network construction identifies distinct modules of co-expressed genes using hippocampus and amygdala samples of A/J and C57BL/6J mice (n = 35). The dendrogram was produced by average linkage hierarchical clustering of genes using topological overlap. Modules of co-expressed genes were assigned colors corresponding to the branches indicated by the horizontal bar beneath the dendrogram.