Genes and Genomes (KEGG) (5). Later on, other types of annotated gene sets for enrichment analysis emerged; for example, chromosome location of genes, computationally predicted targets of microRNAs and transcription factors, and gene modules identified computationally from large collections of gene expression data (6). Subsequently, improved enrichment analysis algorithms (7,8) and enrichment analysis tools (9–13) emerged. Here we present a major update to the enrichment analysis tool Enrichr, which was first published in 2013. Since its initial publication, we added many new features and data sets to Enrichr. The new gene set libraries that were added include differentially expressed genes after drug, gene, disease and pathogen perturbations extracted from the national center for biotechnology information (NCBI) gene expression omnibus (GEO) through a crowdsourcing project. Furthermore, we have implemented the ability to submit fuzzy sets, upload BED files, a calendar that shows the number of lists submitted each day, an improved application programming interface (API), an enhanced help documentation, an improved Find a Gene feature, and visualization of the results as clustergrams. In this manuscript, we also provide updated benchmarking results of the different scoring schemes implemented in Enrichr and visualize the overlap between the data sets currently within Enrichr compared
