{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T13:14:49Z","timestamp":1771074889663,"version":"3.50.1"},"reference-count":6,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2022,4,29]],"date-time":"2022-04-29T00:00:00Z","timestamp":1651190400000},"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\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["CA241699"],"award-info":[{"award-number":["CA241699"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["CA196530"],"award-info":[{"award-number":["CA196530"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["CA204120"],"award-info":[{"award-number":["CA204120"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Changsha City","award":["kq2202180"],"award-info":[{"award-number":["kq2202180"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,26]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Summary<\/jats:title><jats:p>Gene\u2013environment (G\u2013E) interactions have important implications for many complex diseases. With higher dimensionality and weaker signals, G\u2013E interaction analysis is more challenged than the analysis of main G (and E) effects. The accumulation of published literature makes it possible to borrow strength from prior information and improve analysis. In a recent study, a \u2018quasi-likelihood + penalization\u2019 approach was developed to effectively incorporate prior information. Here, we first extend it to linear, logistic and Poisson regressions. Such models are much more popular in practice. More importantly, we develop the R package GEInfo, which realizes this approach in a user-friendly manner. To facilitate direct comparison and routine data analysis, the package also includes functions for alternative methods and visualization.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The package is available at https:\/\/CRAN.R-project.org\/package=GEInfo.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary materials are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac301","type":"journal-article","created":{"date-parts":[[2022,4,25]],"date-time":"2022-04-25T19:11:59Z","timestamp":1650913919000},"page":"3139-3140","source":"Crossref","is-referenced-by-count":1,"title":["GEInfo: an R package for gene\u2013environment interaction analysis incorporating prior information"],"prefix":"10.1093","volume":"38","author":[{"given":"Xiaoyan","family":"Wang","sequence":"first","affiliation":[{"name":"College of Finance and Statistics, Hunan University , Changsha 410079, Hunan, China"}]},{"given":"Hongduo","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Finance and Statistics, Hunan University , Changsha 410079, Hunan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9001-4999","authenticated-orcid":false,"given":"Shuangge","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Yale University , New Haven, CT 06520, USA"}]}],"member":"286","published-online":{"date-parts":[[2022,4,29]]},"reference":[{"key":"2023041403080944800_","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1214\/13-AOS1096","article-title":"A lasso for hierarchical interactions","volume":"41","author":"Bien","year":"2013","journal-title":"Ann. Stat"},{"key":"2023041403080944800_","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1080\/01621459.2015.1008363","article-title":"Variable selection with prior information for generalized linear models via the prior lasso method","volume":"111","author":"Jiang","year":"2016","journal-title":"J. Am. Stat. Assoc"},{"key":"2023041403080944800_","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.ygeno.2013.08.006","article-title":"Identification of gene-environment interactions in cancer studies using penalization","volume":"102","author":"Liu","year":"2013","journal-title":"Genomics"},{"key":"2023041403080944800_","doi-asserted-by":"crossref","first-page":"753","DOI":"10.1093\/aje\/kwx227","article-title":"Current challenges and new opportunities for gene-environment interaction studies of complex diseases","volume":"186","author":"McAllister","year":"2017","journal-title":"Am. J. Epidemiol"},{"key":"2023041403080944800_","doi-asserted-by":"crossref","first-page":"1620","DOI":"10.1002\/sim.8064","article-title":"Identifying gene-environment interactions incorporating prior information","volume":"38","author":"Wang","year":"2019","journal-title":"Stat. Med"},{"key":"2023041403080944800_","doi-asserted-by":"crossref","first-page":"624","DOI":"10.1093\/bib\/bby033","article-title":"Robust genetic interaction analysis","volume":"20","author":"Wu","year":"2019","journal-title":"Brief. Bioinformatics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btac301\/43615714\/btac301.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/11\/3139\/49878622\/btac301.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/11\/3139\/49878622\/btac301.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T15:37:30Z","timestamp":1700494650000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/38\/11\/3139\/6575887"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Wren","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2022,4,29]]},"references-count":6,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2022,5,26]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btac301","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,6,1]]},"published":{"date-parts":[[2022,4,29]]}}}