{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T17:57:23Z","timestamp":1785952643804,"version":"3.56.0"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T00:00:00Z","timestamp":1668643200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Center for Tumor Diseases"},{"name":"Molecular Precision Oncology Program"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>GREAT (Genomic Regions Enrichment of Annotations Tool) is a widely used tool for functional enrichment on genomic regions. However, as an online tool, it has limitations of outdated annotation data, small numbers of supported organisms and gene set collections, and not being extensible for users. Here, we developed a new R\/Bioconductorpackage named rGREAT which implements the GREAT algorithm locally. rGREAT by default supports more than 600 organisms and a large number of gene set collections, as well as self-provided gene sets and organisms from users. Additionally, it implements a general method for dealing with background regions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The package rGREAT is freely available from the Bioconductor project: https:\/\/bioconductor.org\/packages\/rGREAT\/. The development version is available at https:\/\/github.com\/jokergoo\/rGREAT. Gene Ontology gene sets for more than 600 organisms retrieved from Ensembl BioMart are presented in an R package BioMartGOGeneSets which is available at https:\/\/github.com\/jokergoo\/BioMartGOGeneSets.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac745","type":"journal-article","created":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T07:45:27Z","timestamp":1668671127000},"source":"Crossref","is-referenced-by-count":170,"title":["<i>rGREAT<\/i>\n                    : an R\/bioconductor package for functional enrichment on genomic regions"],"prefix":"10.1093","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7395-8709","authenticated-orcid":false,"given":"Zuguang","family":"Gu","sequence":"first","affiliation":[{"name":"Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) , Heidelberg 69120, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"H\u00fcbschmann","sequence":"additional","affiliation":[{"name":"Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) , Heidelberg 69120, Germany"},{"name":"Heidelberg Institute of Stem Cell Technology and Experimental Medicine (HI-STEM) , Heidelberg 69120, Germany"},{"name":"German Cancer Consortium (DKTK) , Heidelberg 69120, Germany"},{"name":"Department of Pediatric Immunology, Hematology and Oncology, University Hospital Heidelberg , Heidelberg, 69120, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,11,17]]},"reference":[{"key":"2023010107544144700_btac745-B1","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1186\/s12859-018-2438-1","article-title":"Mind the gaps: overlooking inaccessible regions confounds statistical testing in genome analysis","volume":"19","author":"Domanska","year":"2018","journal-title":"BMC Bioinformatics"},{"key":"2023010107544144700_btac745-B2","doi-asserted-by":"crossref","first-page":"3439","DOI":"10.1093\/bioinformatics\/bti525","article-title":"BioMart and bioconductor: a powerful link between biological databases and microarray data analysis","volume":"21","author":"Durinck","year":"2005","journal-title":"Bioinformatics"},{"key":"2023010107544144700_btac745-B3","doi-asserted-by":"crossref","first-page":"D916","DOI":"10.1093\/nar\/gkaa1087","article-title":"gencode 2021","volume":"49","author":"Frankish","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2023010107544144700_btac745-B4","doi-asserted-by":"crossref","first-page":"3587","DOI":"10.1093\/bioinformatics\/bti565","article-title":"Ontological analysis of gene expression data: current tools, limitations, and open problems","volume":"21","author":"Khatri","year":"2005","journal-title":"Bioinformatics"},{"key":"2023010107544144700_btac745-B5","doi-asserted-by":"crossref","first-page":"bar030","DOI":"10.1093\/database\/bar030","article-title":"Ensembl BioMarts: a hub for data retrieval across taxonomic space","volume":"2011","author":"Kinsella","year":"2011","journal-title":"Database"},{"key":"2023010107544144700_btac745-B6","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1093\/bioinformatics\/btr260","article-title":"Molecular signatures database (MSigDB) 3.0","volume":"27","author":"Liberzon","year":"2011","journal-title":"Bioinformatics"},{"key":"2023010107544144700_btac745-B7","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1038\/nbt.1630","article-title":"GREAT improves functional interpretation of cis-regulatory regions","volume":"28","author":"McLean","year":"2010","journal-title":"Nat. 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