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. 2022 Jun 27;13:3695. doi: 10.1038/s41467-022-31411-3

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© The Author(s) 2022

Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — a Schematic illustration of RAVmodel construction and GenomicSuperSignature application. Building the RAVmodel (gray) was performed over several days on 24 cores with 128 Gb memory. Users can apply RAVmodel on their data (red) using the GenomicSuperSignature R/Bioconductor package (blue), which operates on a time scale of seconds for exploratory data analysis (orange) on a typical laptop computer. b Information assembled as RAVmodel, a single R object. RAVmodel connects different public databases and prior information through RAVindex (Supplementary Fig. 1b), creating the interconnected resources illustrated here. Through GenomicSuperSignature R/Bioconductor package and the accompanying RAVmodel, users can instantly access and explore the diverse public databases from multiple entry points such as gene expression profiles, publications, study metadata, keywords in MeSH terms and gene sets.