complete tables from spreadsheets with special characters, and other non-standard genes names. To accommodate these users, Enrichr needs to provide methods to convert these inputs into usable gene sets. The enrichment analysis concept can be expanded into new directions. For example, drug-set enrichment analysis (42) can be used to identify common functions for collections of drugs. In addition, enrichment analysis tools are increasingly becoming network-aware. The edge set enrichment analysis (43) method is one example of how network information can be incorporated into enrichment analysis. The collective analysis of the over one million gene sets submitted to Enrichr can be viewed as a potential resource for biological discovery. Each list can be classified into an attractor of similar lists and classified by methods of data acquisition but also biological regulatory layers, i.e. mRNA/proteins/SNPs, as well as biological roles. While we are committed to keeping user lists completely private, we also aim to explore the collective knowledge that is accumulating from all user submissions to Enrichr (37).
