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. 2022 Apr 4;220(4):iyac005.
doi: 10.1093/genetics/iyac005.

MOET: a web-based gene set enrichment tool at the Rat Genome Database for multiontology and multispecies analyses

Mahima Vedi  1 , Harika S Nalabolu  1 , Chien-Wei Lin  2 , Matthew J Hoffman  3 , Jennifer R Smith  1 , Kent Brodie  4 , Jeffrey L De Pons  1 , Wendy M Demos  1 , Adam C Gibson  1 , G Thomas Hayman  1 , Morgan L Hill  1 , Mary L Kaldunski  1 , Logan Lamers  1 , Stanley J F Laulederkind  1 , Ketaki Thorat  1 , Jyothi Thota  1 , Monika Tutaj  1 , Marek A Tutaj  1 , Shur-Jen Wang  1 , Stacy Zacher  5 , Melinda R Dwinell  3 , Anne E Kwitek  1   3
Affiliations

MOET: a web-based gene set enrichment tool at the Rat Genome Database for multiontology and multispecies analyses

Mahima Vedi et al. Genetics. .

Abstract

Biological interpretation of a large amount of gene or protein data is complex. Ontology analysis tools are imperative in finding functional similarities through overrepresentation or enrichment of terms associated with the input gene or protein lists. However, most tools are limited by their ability to do ontology-specific and species-limited analyses. Furthermore, some enrichment tools are not updated frequently with recent information from databases, thus giving users inaccurate, outdated or uninformative data. Here, we present MOET or the Multi-Ontology Enrichment Tool (v.1 released in April 2019 and v.2 released in May 2021), an ontology analysis tool leveraging data that the Rat Genome Database (RGD) integrated from in-house expert curation and external databases including the National Center for Biotechnology Information (NCBI), Mouse Genome Informatics (MGI), The Kyoto Encyclopedia of Genes and Genomes (KEGG), The Gene Ontology Resource, UniProt-GOA, and others. Given a gene or protein list, MOET analysis identifies significantly overrepresented ontology terms using a hypergeometric test and provides nominal and Bonferroni corrected P-values and odds ratios for the overrepresented terms. The results are shown as a downloadable list of terms with and without Bonferroni correction, and a graph of the P-values and number of annotated genes for each term in the list. MOET can be accessed freely from https://rgd.mcw.edu/rgdweb/enrichment/start.html.

Keywords: gene set enrichment; model organism database; multiple ontology; multiple species analysis; ontology; rat; web tool.

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Figures

Fig. 1.
Fig. 1.
Schematic overview of MOET functionality. The user provides input using the options shown, MOET uses data integrated at RGD from all the sources, performs enrichment and statistical analysis, and provides downloadable results.
Fig. 2.
Fig. 2.
Access to MOET from A) and B) “Analysis & Visualization” and individual disease pages from “Diseases” and “Disease Portals”; C) You can enter your gene or protein list in the MOET interface as one of the acceptable RGD identifier types and then click on continue to view the results.
Fig. 3.
Fig. 3.
MOET results page with downloadable list and graph; A) A list of over-represented terms with the uncorrected and Bonferroni-corrected P-values and odds ratio for each term; B) The species or ontology used for the analysis can be changed with the click of a single button. Current display is for rat and disease as indicated by the green tabs. Click Human and Pathway Ontology to obtain over-represented pathway terms for the list of human orthologs of the original input list of rat genes (refer to Supplementary Fig. S1); C) The result list can be downloaded. The resulting file contains the list of terms with the counts of genes annotated to each term in the input set and the reference set, the P-value, Bonferroni correction and odds ratio. D) The results shown in the graph of the number of annotated genes and P-value for each term in the result set can be made more or less stringent by changing the P-value limit using the drop-down list of options.
Fig. 4.
Fig. 4.
MOET is accessible from individual Disease Portal pages. Here “Obesity/Metabolic Syndrome Portal” is shown; A) Rat as species and Disease as Ontology Category are selected as default; B) Number of genes associated with the selected species and disease category annotated to the term “familial hyperlipidemia” are shown; C) You can interchangeably select a different ontology for MOET analysis from the buttons below “Gene Set Enrichment.” Here, ontology analysis results for Rat in Chemicals and Drugs or ChEBI ontology are shown with “unsaturated fatty acid” as the top term.
Fig. 5.
Fig. 5.
Intersecting curated canonical pathways and ontologies used in software comparison. This Venn diagram depicts common and unique resources used by MOET, PANTHER, GSEA, and DAVID for integration into their respective ontology and pathway analyses. Several resources including KEGG and UniProt are included in the development of MOET ontologies, but results to their specific terms are not provided from the analysis.
Fig. 6.
Fig. 6.
Representation of top 100 GO term overlap among compared enrichment tools. Gene Ontology analysis was performed using an experimentally derived DEG set. Genes were loaded into each software (MOET, PANTHER, GSEA, and DAVID). The top 100 terms ranked on P-value were assessed and overlaps are depicted in the Venn diagram. MOET has 63 terms in common with PANTHER, 27 terms with GSEA, and 6 terms with DAVID.
Fig. 7.
Fig. 7.
MOET top 20 GO biological process term overlap with compared enrichment tools. MOET contained 6 additional terms from the top 20 that were found in the top 100 terms from results in comparison software.
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