(Figure 2C) with the most popular genes: EGR1, FOS, TXNIP, DDIT4 and SGK1. EGR1 and FOS are well-known immediate early genes (IEG), and their high presence likely confirms that these genes are most commonly found as differentially expressed. The appearance of TXNIP, DDIT4 and SGK1 as common genes is interesting since these genes have a lesser-known role to be most responsive. The identification of the common occurrence of genes in submitted lists and annotated gene sets can potentially be applied to correct for biases, and as a result improve knowledge extraction. More extensive analysis of gene occurrence and co-occurrence in submitted lists demonstrates that such collective knowledge can be used to discover gene functions and predict protein interactions (37). Finally, we plot the distribution of the lengths of the 180 184 annotated gene sets provided for search by Enrichr (Figure 2D). Overall, this distribution also fits a power law with few inflections that likely represent specific libraries with hard cut-offs for gene sets. It is still an open question what are the recommendations for optimal enrichment analysis when it comes to setting thresholds for gene set lengths. This is likely because the answer is context dependent, but more investigation can
