{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T07:54:06Z","timestamp":1772092446592,"version":"3.50.1"},"reference-count":13,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2018,9,13]],"date-time":"2018-09-13T00:00:00Z","timestamp":1536796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"National Institute of Health","award":["R01GM069430"],"award-info":[{"award-number":["R01GM069430"]}]},{"name":"National Institute of Health","award":["R01CA216108"],"award-info":[{"award-number":["R01CA216108"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81773541"],"award-info":[{"award-number":["81773541"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81573253"],"award-info":[{"award-number":["81573253"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>BhGLM is a freely available R package that implements Bayesian hierarchical modeling for high-dimensional clinical and genomic data. It consists of functions for setting up various Bayesian hierarchical models, including generalized linear models (GLMs) and Cox survival models, with four types of prior distributions for coefficients, i.e. double-exponential, Student-t, mixture double-exponential and mixture Student-t. These functions adapt fast and stable algorithms to estimate parameters. BhGLM also provides functions for summarizing results numerically and graphically and for evaluating predictive values. The package is particularly useful for analyzing large-scale molecular data, i.e. detecting disease-associated variables and predicting disease outcomes. We here describe the models, algorithms and associated features implemented in BhGLM.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The package is freely available from the public GitHub repository, https:\/\/github.com\/nyiuab\/BhGLM.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty803","type":"journal-article","created":{"date-parts":[[2018,9,12]],"date-time":"2018-09-12T19:24:16Z","timestamp":1536780256000},"page":"1419-1421","source":"Crossref","is-referenced-by-count":39,"title":["BhGLM: Bayesian hierarchical GLMs and survival models, with applications to genomics and epidemiology"],"prefix":"10.1093","volume":"35","author":[{"given":"Nengjun","family":"Yi","sequence":"first","affiliation":[{"name":"Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zaixiang","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boyi","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,9,13]]},"reference":[{"key":"2023012808250496100_bty803-B1","doi-asserted-by":"crossref","DOI":"10.1201\/b12677","volume-title":"Computational Systems Biology of Cancer","author":"Barillot","year":"2012"},{"key":"2023012808250496100_bty803-B2","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1056\/NEJMp1500523","article-title":"A new initiative on precision medicine","volume":"372","author":"Collins","year":"2015","journal-title":"N. 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