{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T07:29:17Z","timestamp":1774423757700,"version":"3.50.1"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T00:00:00Z","timestamp":1652659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010626","name":"Ryukoku University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010626","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,6,13]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Summary<\/jats:title><jats:p>An R package that can implement multiple linear learners, including penalized regression and regression with spike and slab priors, in a single model has been developed. Solutions are obtained with fast minorize-maximization algorithms in the framework of variational Bayesian inference. This package helps to incorporate multimodal and high-dimensional explanatory variables in a single regression model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The R package VIGoR (Variational Bayesian Inference for Genome-wide Regression) is available at the Comprehensive R Archive Network (CRAN) (https:\/\/cran.r-project.org\/) and at GitHub (https:\/\/github.com\/Onogi\/VIGoR).<\/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\/btac328","type":"journal-article","created":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T11:48:06Z","timestamp":1652701686000},"page":"3306-3309","source":"Crossref","is-referenced-by-count":4,"title":["An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1707-9539","authenticated-orcid":false,"given":"Akio","family":"Onogi","sequence":"first","affiliation":[{"name":"Department of Plant Life Science, Faculty of Agriculture, Ryukoku University , Otsu, Shiga 520-2194, Japan"}]},{"given":"Aisaku","family":"Arakawa","sequence":"additional","affiliation":[{"name":"Division of Animal Breeding and Reproduction Research, Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization , Tsukuba, Ibaraki 305-0901, Japan"}]}],"member":"286","published-online":{"date-parts":[[2022,5,16]]},"reference":[{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v033.i01","article-title":"Regularization paths for generalized linear models via coordinate descent","volume":"33","author":"Friedman","year":"2010","journal-title":"J. Stat. Softw"},{"key":"2023041408203579900_","first-page":"1","article-title":"Multi-sensor integrated system for wireless monitoring of greenhouse environment","author":"Gupta","year":"2018","journal-title":"2018 IEEE Sensors Applications Symposium (SAS), Seoul"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1186\/1471-2105-12-186","article-title":"Extension of the Bayesian alphabet for genomic selection","volume":"12","author":"Habier","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1186\/s13059-017-1215-1","article-title":"Multi-omics approaches to disease","volume":"18","author":"Hasin","year":"2017","journal-title":"Genome Biol"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1039\/C7MO00051K","article-title":"Data integration and predictive modeling methods for multi-omics datasets","volume":"14","author":"Kim","year":"2018","journal-title":"Mol. Omics"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1297-9686-45-24","article-title":"Impact of prior specifications in a shrinkage-inducing Bayesian model for quantitative trait mapping and genomic prediction","volume":"45","author":"Kn\u00fcrr","year":"2013","journal-title":"Genet. Sel. Evol"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"1819","DOI":"10.1093\/genetics\/157.4.1819","article-title":"Prediction of total genetic value using genome-wide dense marker maps","volume":"157","author":"Meuwissen","year":"2001","journal-title":"Genetics"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1109\/ICACOMIT.2017.8253384","article-title":"Design of real-time weather monitoring system based on mobile application using automatic weather station","author":"Munandar","year":"2017","journal-title":"2017 2nd International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology (ICACOMIT), Jakarta"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1534\/genetics.110.119586","article-title":"Extended Bayesian LASSO for multiple quantitative trait loci mapping and unobserved phenotype prediction","volume":"186","author":"Mutshinda","year":"2010","journal-title":"Genetics"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"e11","DOI":"10.5334\/jors.80","article-title":"VIGoR: variational Bayesian inference for genome-wide regression","volume":"4","author":"Onogi","year":"2016","journal-title":"J. Open Res. Softw"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1007\/s00122-014-2411-y","article-title":"Exploring the areas of applicability of whole-genome prediction methods for Asian rice (Oryza sativa L.)","volume":"128","author":"Onogi","year":"2015","journal-title":"Theor. Appl. Genet"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"803636","DOI":"10.3389\/fgene.2021.803636","article-title":"A method for identifying environmental stimuli and genes responsible for genotype-by-environment interactions from a large-scale multi-environment data set","volume":"12","author":"Onogi","year":"2021","journal-title":"Front. Genet"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1198\/016214508000000337","article-title":"The Bayesian lasso","volume":"103","author":"Park","year":"2008","journal-title":"J. Am. Stat. Assoc"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1534\/genetics.114.164442","article-title":"Genome-wide regression and prediction with the BGLR Statistical package","volume":"198","author":"P\u00e9rez","year":"2014","journal-title":"Genetics"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1038\/ng.1033","article-title":"Genomic and metabolic prediction of complex heterotic traits in hybrid maize","volume":"44","author":"Riedelsheimer","year":"2012","journal-title":"Nat. Genet"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"3940","DOI":"10.1093\/bioinformatics\/bti623","article-title":"ROCR: visualizing classifier performance in R","volume":"21","author":"Sing","year":"2005","journal-title":"Bioinformatics"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"J. R. Stat. Soc. B"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1093\/carcin\/bgx084","article-title":"Metabolome-wide association study identified the association between a circulating polyunsaturated fatty acid variant rs174548 and lung cancer","volume":"38","author":"Wang","year":"2017","journal-title":"Carcinogenesis"},{"key":"2023041408203579900_","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","article-title":"Regularization and variable selection via the elastic net","volume":"67","author":"Zou","year":"2005","journal-title":"J. R. Stat. Soc. B"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btac328\/43796810\/btac328.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/12\/3306\/49885440\/btac328.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/12\/3306\/49885440\/btac328.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T01:40:11Z","timestamp":1727228411000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/38\/12\/3306\/6586288"}},"subtitle":[],"editor":[{"given":"Russell","family":"Schwartz","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2022,5,16]]},"references-count":19,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2022,6,13]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btac328","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,6,15]]},"published":{"date-parts":[[2022,5,16]]}}}