When Is Hub Gene Selection Better than Standard Meta-Analysis?
Figure 2
Marginal meta-analysis tends to lead to gene lists with better validation in independent data.
The 3 barplots show validation success in our 3 applications. Each bar summarizes the gene screening success of the corresponding meta-analysis method. Specifically, we rank the genes using each meta-analysis method and retain the top 100 genes. We define gene screening success as the average correlation of these top 100 genes with the trait of interest in an independent validation data set, averaged over the validation sets in each application. Each bar represents the gene screening success; error bars give the corresponding standard deviation of the observed gene–trait correlations in the top 100 genes. This figure shows that, overall, marginal meta-analysis leads to gene lists with better validation success (i.e., higher correlation with the trait of interest in validation data). Adenocarcinoma expression data (panel A) present an exception in that meta-analysis of module membership results in gene lists with somewhat better validation.