{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T11:33:11Z","timestamp":1783855991326,"version":"3.55.0"},"reference-count":17,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2020,2,6]],"date-time":"2020-02-06T00:00:00Z","timestamp":1580947200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100001321","name":"National Research Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007431","name":"NRF","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007431","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Genomics Program","award":["2016M3C9A3945893"],"award-info":[{"award-number":["2016M3C9A3945893"]}]},{"name":"Basic Science Research Program","award":["2017R1E1A1A03070107"],"award-info":[{"award-number":["2017R1E1A1A03070107"]}]},{"DOI":"10.13039\/501100010446","name":"Institute for Basic Science","doi-asserted-by":"publisher","award":["IBS-R022-D1"],"award-info":[{"award-number":["IBS-R022-D1"]}],"id":[{"id":"10.13039\/501100010446","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Summary<\/jats:title><jats:p>We present an R-Shiny package, netGO, for novel network-integrated pathway enrichment analysis. The conventional Fisher\u2019s exact test (FET) considers the extent of overlap between target genes and pathway gene-sets, while recent network-based analysis tools consider only network interactions between the two. netGO implements an intuitive framework to integrate both the overlap and networks into a single score, and adaptively resamples genes based on network degrees to assess the pathway enrichment. In benchmark tests for gene expression and genome-wide association study (GWAS) data, netGO captured the relevant gene-sets better than existing tools, especially when analyzing a small number of genes. Specifically, netGO provides user-interactive visualization of the target genes, enriched gene-set and their network interactions for both netGO and FET results for further analysis. For this visualization, we also developed a standalone R-Shiny package shinyCyJS to connect R-shiny and the JavaScript version of cytoscape.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>netGO R-Shiny package is freely available from github, https:\/\/github.com\/unistbig\/netGO.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa077","type":"journal-article","created":{"date-parts":[[2020,1,29]],"date-time":"2020-01-29T12:15:54Z","timestamp":1580300154000},"page":"3283-3285","source":"Crossref","is-referenced-by-count":13,"title":["netGO: R-Shiny package for network-integrated pathway enrichment analysis"],"prefix":"10.1093","volume":"36","author":[{"given":"Jinhwan","family":"Kim","sequence":"first","affiliation":[{"name":"School of Life Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sora","family":"Yoon","sequence":"additional","affiliation":[{"name":"School of Life Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dougu","family":"Nam","sequence":"additional","affiliation":[{"name":"School of Life Sciences"},{"name":"Department of Mathematical Sciences , Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,2,6]]},"reference":[{"key":"2023013112025316100_btaa077-B1","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1186\/1471-2105-13-226","article-title":"Network enrichment analysis: extension of gene-set enrichment analysis to gene networks","volume":"13","author":"Alexeyenko","year":"2012","journal-title":"BMC Bioinformatics"},{"key":"2023013112025316100_btaa077-B2","first-page":"e20","article-title":"Using predictive specificity to determine when gene set analysis is biologically meaningful","volume":"45","author":"Ballouz","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B3","doi-asserted-by":"crossref","first-page":"2366","DOI":"10.1038\/nprot.2007.324","article-title":"Integration of biological networks and gene expression data using Cytoscape","volume":"2","author":"Cline","year":"2007","journal-title":"Nat. Protoc"},{"key":"2023013112025316100_btaa077-B4","doi-asserted-by":"crossref","first-page":"1216","DOI":"10.1093\/bioinformatics\/btw821","article-title":"Biomartr: genomic data retrieval with R","volume":"33","author":"Drost","year":"2017","journal-title":"Bioinformatics"},{"key":"2023013112025316100_btaa077-B5","doi-asserted-by":"crossref","first-page":"i451","DOI":"10.1093\/bioinformatics\/bts389","article-title":"EnrichNet: network-based gene set enrichment analysis","volume":"28","author":"Glaab","year":"2012","journal-title":"Bioinformatics"},{"key":"2023013112025316100_btaa077-B6","doi-asserted-by":"crossref","first-page":"4191","DOI":"10.1038\/srep04191","article-title":"Annotation enrichment analysis: an alternative method for evaluating the functional properties of gene sets","volume":"4","author":"Glass","year":"2014","journal-title":"Sci. Rep"},{"key":"2023013112025316100_btaa077-B7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/nar\/gkn923","article-title":"Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists","volume":"37","author":"Huang da","year":"2009","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B8","doi-asserted-by":"crossref","first-page":"D573","DOI":"10.1093\/nar\/gky1126","article-title":"HumanNet v2: human gene networks for disease research","volume":"47","author":"Hwang","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B9","doi-asserted-by":"crossref","first-page":"D457","DOI":"10.1093\/nar\/gkv1070","article-title":"KEGG as a reference resource for gene and protein annotation","volume":"44","author":"Kanehisa","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B10","doi-asserted-by":"crossref","first-page":"D731","DOI":"10.1093\/nar\/gkt981","article-title":"YeastNet v3: a public database of data-specific and integrated functional gene networks for Saccharomyces cerevisiae","volume":"42","author":"Kim","year":"2014","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B11","doi-asserted-by":"crossref","first-page":"D848","DOI":"10.1093\/nar\/gkv1155","article-title":"MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates","volume":"44","author":"Kim","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B12","doi-asserted-by":"crossref","first-page":"D996","DOI":"10.1093\/nar\/gku1053","article-title":"AraNet v2: an improved database of co-functional gene networks for the study of Arabidopsis thaliana and 27 other nonmodel plant species","volume":"43","author":"Lee","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B13","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":"2023013112025316100_btaa077-B14","doi-asserted-by":"crossref","first-page":"e8","DOI":"10.1093\/nar\/gkw849","article-title":"A novel method for crosstalk analysis of biological networks: improving accuracy of pathway annotation","volume":"45","author":"Ogris","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B15","doi-asserted-by":"crossref","first-page":"D362","DOI":"10.1093\/nar\/gkw937","article-title":"The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible","volume":"45","author":"Szklarczyk","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B16","doi-asserted-by":"crossref","first-page":"e60","DOI":"10.1093\/nar\/gky175","article-title":"Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2","volume":"46","author":"Yoon","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"2023013112025316100_btaa077-B17","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1186\/s12864-019-5738-6","article-title":"GScluster: network-weighted gene-set clustering analysis","volume":"20","author":"Yoon","year":"2019","journal-title":"BMC Genomics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaa077\/32540328\/btaa077.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/10\/3283\/48991103\/bioinformatics_36_10_3283.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/10\/3283\/48991103\/bioinformatics_36_10_3283.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T21:32:25Z","timestamp":1695677545000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/36\/10\/3283\/5728635"}},"subtitle":[],"editor":[{"given":"Bonnie","family":"Berger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2020,2,6]]},"references-count":17,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2020,5,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaa077","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,5,15]]},"published":{"date-parts":[[2020,2,6]]}}}