modEnrichr: a suite of gene set enrichment analysis tools for model organisms

Abstract

High-throughput experiments produce increasingly large datasets that are difficult to analyze and integrate. While most data integration approaches focus on aligning metadata, data integration can be achieved by abstracting experimental results into gene sets. Such gene sets can be made available for reuse through gene set enrichment analysis tools such as Enrichr. Enrichr currently only supports gene sets compiled from human and mouse, limiting accessibility for investigators that study other model organisms. modEnrichr is an expansion of Enrichr for four model organisms: fish, fly, worm and yeast. The gene set libraries within FishEnrichr, FlyEnrichr, WormEnrichr and YeastEnrichr are created from the Gene Ontology, mRNA expression profiles, GeneRIF, pathway databases, protein domain databases and other organism-specific resources. Additionally, libraries were created by predicting gene function from RNA-seq co-expression data processed uniformly from the gene expression omnibus for each organism. The modEnrichr suite of tools provides the ability to convert gene lists across species using an ortholog conversion tool that automatically detects the species. For complex analyses, modEnrichr provides API access that enables submitting batch queries. In summary, modEnrichr leverages existing model organism databases and other resources to facilitate comprehensive hypothesis generation through data integration.

Figure 1.

Screenshot of the modEnrichr's landing page. The input form on the left enables users to submit gene lists with an option to convert them to their orthologs in alternative species. The panel on the right provides names, logos, and links to the collection of modEnrichr tools with statistics about submissions, libraries, and annotated gene sets.

Figure 2.

Flow chart depicting the various options provided to modEnrichr users for submitting gene set queries.

Figure 3.

Benchmarking the ability of the gene-gene co-expression matrices to predict relevant genes for terms within libraries for (A) Caenorhabditis elegans, (B) Danio rerio, (C) Drosophila melanogaster and (D) Saccharomyces cerevisiae. To compare these results to a baseline, AUCs were calculated after randomly shuffling terms. Benchmarking was also performed after removing half of the most redundant gene sets from each library in order to demonstrate robustness of these predictions to this factor.

Figure 4.

Flow chart depicting the various routes taken to generate the gene set libraries that populate modEnrichr.