Schematic flowchart illustrating the network-oriented comparisons using transcriptome data in a variety of developmental contexts. Gene set enrichment analysis (GSEA) takes the hORGNet (and its two modules, hStemModule and hDiffModule) as a gene set and determines the degree to which genes in the gene set are overrepresented at the top or bottom of a ranked gene list. The ranked gene lists are predefined by a LIMMA supervised analysis of three representative context-specific transcriptome datasets, including human embryos, stem cell matrix, and EB models. The right panel illustrates the hypothetical results of GSEA analysis. Genes in a gene set tend to be at the top ("Significant positive"), at the bottom ("Significant negative") or randomly distributed ("Null") over a predefined ranked gene list. The normalized enrichment score (NES) reflects the degree to which genes in a gene set are overrepresented at the top or bottom of the ranked gene list. A positive NES (e.g., 2.00) indicates overrepresentation at the top of the ranked gene list, whereas a negative NES (e.g., -2.00) indicates overrepresentation at the bottom. The significance of the overrepresentation corresponding to each NES can be assessed by false discovery rate (FDR).