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. 2021 Nov 5;33(1):66–80. doi: 10.1007/s00335-021-09932-x

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© The Author(s) 2021

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 8 — Using functional analysis tools from the RGD toolkit to interrogate the thrombosis gene list: Within the Cardiovascular Disease Portal, with the specific disease selection for thrombosis, one finds 139 genes annotated in rat, as detailed in Fig. 5 and Online Resource 1. a Selecting “mouse” and choosing “MP: Phenotype Ontology” enrichment launches an analysis that utilizes MOET; b selecting “rat” and “CHEBI: Chemical/Drug Enrichment” alters the results accordingly; c downloading the gene list into Excel and entering it into the Gene Annotator (GA) Tool will return all annotations in any ontology selected and provide a feature of the GA tool that can generate a comparative heatmap of the genes in the intersections between and within ontologies. Here, we show the resultant heatmap of genes for the intersection of disease ontology child terms for thrombosis and Coronavirus infectious disease. For more detailed steps, see Online Resource 3