{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T10:19:44Z","timestamp":1770286784657,"version":"3.49.0"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"15","license":[{"start":{"date-parts":[[2020,5,29]],"date-time":"2020-05-29T00:00:00Z","timestamp":1590710400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001711","name":"Swiss National Science Foundation","doi-asserted-by":"publisher","award":["31003A-143914"],"award-info":[{"award-number":["31003A-143914"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001711","name":"Swiss National Science Foundation","doi-asserted-by":"publisher","award":["310030-189147"],"award-info":[{"award-number":["310030-189147"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>Increasing sample size is not the only strategy to improve discovery in Genome Wide Association Studies (GWASs) and we propose here an approach that leverages published studies of related traits to improve inference. Our Bayesian GWAS method derives informative prior effects by leveraging GWASs of related risk factors and their causal effect estimates on the focal trait using multivariable Mendelian randomization. These prior effects are combined with the observed effects to yield Bayes Factors, posterior and direct effects. The approach not only increases power, but also has the potential to dissect direct and indirect biological mechanisms.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>bGWAS package is freely available under a GPL-2 License, and can be accessed, alongside with user guides and tutorials, from https:\/\/github.com\/n-mounier\/bGWAS.<\/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\/btaa549","type":"journal-article","created":{"date-parts":[[2020,5,25]],"date-time":"2020-05-25T11:08:09Z","timestamp":1590404889000},"page":"4374-4376","source":"Crossref","is-referenced-by-count":13,"title":["bGWAS: an R package to perform Bayesian genome wide association studies"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6663-5402","authenticated-orcid":false,"given":"Ninon","family":"Mounier","sequence":"first","affiliation":[{"name":"Department of Training, Research and Innovation, University Center for Primary Care and Public Health , Lausanne 1010, Switzerland"},{"name":"Swiss Institute of Bioinformatics , Lausanne 1015, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8285-7523","authenticated-orcid":false,"given":"Zolt\u00e1n","family":"Kutalik","sequence":"additional","affiliation":[{"name":"Department of Training, Research and Innovation, University Center for Primary Care and Public Health , Lausanne 1010, Switzerland"},{"name":"Swiss Institute of Bioinformatics , Lausanne 1015, Switzerland"}]}],"member":"286","published-online":{"date-parts":[[2020,5,29]]},"reference":[{"key":"2023062312042375000_btaa549-B1","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1016\/j.neuron.2019.01.056","article-title":"A quarter century of APOE and Alzheimer\u2019s disease: progress to date and the path forward","volume":"101","author":"Belloy","year":"2019","journal-title":"Neuron"},{"key":"2023062312042375000_btaa549-B2","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1038\/s41562-019-0566-x","article-title":"Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits","volume":"3","author":"Grotzinger","year":"2019","journal-title":"Nat. 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