{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:13Z","timestamp":1773705613233,"version":"3.50.1"},"reference-count":70,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2020,4,6]],"date-time":"2020-04-06T00:00:00Z","timestamp":1586131200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U54HG007963"],"award-info":[{"award-number":["U54HG007963"]}],"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":["U01TR002623"],"award-info":[{"award-number":["U01TR002623"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,1,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Precision medicine promises to revolutionize treatment, shifting therapeutic approaches from the classical one-size-fits-all to those more tailored to the patient\u2019s individual genomic profile, lifestyle and environmental exposures. Yet, to advance precision medicine\u2019s main objective\u2014ensuring the optimum diagnosis, treatment and prognosis for each individual\u2014investigators need access to large-scale clinical and genomic data repositories. Despite the vast proliferation of these datasets, locating and obtaining access to many remains a challenge. We sought to provide an overview of available patient-level datasets that contain both genotypic data, obtained by next-generation sequencing, and phenotypic data\u2014and to create a dynamic, online catalog for consultation, contribution and revision by the research community. Datasets included in this review conform to six specific inclusion parameters that are: (i) contain data from more than 500 human subjects; (ii) contain both genotypic and phenotypic data from the same subjects; (iii) include whole genome sequencing or whole exome sequencing data; (iv) include at least 100 recorded phenotypic variables per subject; (v) accessible through a website or collaboration with investigators and (vi) make access information available in English. Using these criteria, we identified 30 datasets, reviewed them and provided results in the release version of a catalog, which is publicly available through a dynamic Web application and on GitHub. Users can review as well as contribute new datasets for inclusion (Web: https:\/\/avillachlab.shinyapps.io\/genophenocatalog\/; GitHub: https:\/\/github.com\/hms-dbmi\/GenoPheno-CatalogShiny).<\/jats:p>","DOI":"10.1093\/bib\/bbaa033","type":"journal-article","created":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T12:17:16Z","timestamp":1583065036000},"page":"55-65","source":"Crossref","is-referenced-by-count":7,"title":["GenoPheno: cataloging large-scale phenotypic and next-generation sequencing data within human datasets"],"prefix":"10.1093","volume":"22","author":[{"given":"Alba","family":"Guti\u00e9rrez-Sacrist\u00e1n","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, Harvard Medical School"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlos","family":"De Niz","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Harvard Medical School"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cartik","family":"Kothari","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Harvard Medical School"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sek Won","family":"Kong","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Harvard Medical School; Computational Health Informatics Program, Boston Children's Hospital"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kenneth D","family":"Mandl","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Harvard Medical School; Computational Health Informatics Program, Boston Children's Hospital"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul","family":"Avillach","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Harvard Medical School; Computational Health Informatics Program, Boston Children's Hospital"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,4,6]]},"reference":[{"key":"2021012203204989200_ref1","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1126\/science.aab1328","article-title":"Ten things we have to do to achieve precision medicine","volume":"349","author":"Kohane","year":"2015","journal-title":"Science"},{"key":"2021012203204989200_ref2","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 Engl J Med"},{"key":"2021012203204989200_ref3","volume-title":"Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease","author":"National Research Council, Division on Earth and Life Studies, Board on Life Sciences","year":"2012"},{"key":"2021012203204989200_ref4","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1377\/hlthaff.2017.1624","article-title":"Precision medicine: from science to value","volume":"37","author":"Ginsburg","year":"2018","journal-title":"Health Aff"},{"key":"2021012203204989200_ref5","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1038\/ng1007-1181","article-title":"The NCBI dbGaP database of genotypes and phenotypes","volume":"39","author":"Mailman","year":"2007","journal-title":"Nat Genet"},{"key":"2021012203204989200_ref6","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1056\/NEJMsr1809937","article-title":"The \u2018all of us\u2019 research program","volume":"381","author":"All of Us Research Program Investigators","year":"2019","journal-title":"N Engl J Med"},{"key":"2021012203204989200_ref7","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41586-018-0579-z","article-title":"The UK biobank resource with deep phenotyping and genomic data","volume":"562","author":"Bycroft","year":"2018","journal-title":"Nature"},{"key":"2021012203204989200_ref8","doi-asserted-by":"crossref","DOI":"10.1007\/s10654-020-00606-7","article-title":"Contributions of the UK biobank high impact papers in the era of precision medicine","author":"Glynn","year":"2020","journal-title":"Eur J Epidemiol"},{"key":"2021012203204989200_ref9","article-title":"Sequencing of 53,831 diverse genomes from the NHLBI TOPMed program","author":"Taliun","year":"2019","journal-title":"bioRxiv"},{"key":"2021012203204989200_ref10","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1101\/gr.157826.113","article-title":"Hypothesis-generating research and predictive medicine","volume":"23","author":"Biesecker","year":"2013","journal-title":"Genome Res"},{"key":"2021012203204989200_ref11","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1287\/isre.5.4.446","article-title":"Research report-hypothesis testing and hypothesis generating research: an example from the user participation literature","volume":"5","author":"Hartwick","year":"1994","journal-title":"Info Sys Research"},{"key":"2021012203204989200_ref12","doi-asserted-by":"crossref","first-page":"D975","DOI":"10.1093\/nar\/gkt1211","article-title":"NCBI\u2019s database of genotypes and phenotypes: dbGaP","volume":"42","author":"Tryka","year":"2014","journal-title":"Nucleic Acids Res"},{"key":"2021012203204989200_ref13","doi-asserted-by":"crossref","first-page":"1205","DOI":"10.1093\/bioinformatics\/btq126","article-title":"PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations","volume":"26","author":"Denny","year":"2010","journal-title":"Bioinformatics"},{"key":"2021012203204989200_ref14","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1038\/nrg3461","article-title":"Pleiotropy in complex traits: challenges and strategies","volume":"14","author":"Solovieff","year":"2013","journal-title":"Nat Rev Genet"},{"key":"2021012203204989200_ref15","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1038\/nbt1486","article-title":"Next-generation DNA sequencing","volume":"26","author":"Shendure","year":"2008","journal-title":"Nat Biotechnol"},{"key":"2021012203204989200_ref16","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1038\/nrneurol.2013.278","article-title":"Disentangling the heterogeneity of autism spectrum disorder through genetic findings","volume":"10","author":"Jeste","year":"2014","journal-title":"Nat Rev Neurol"},{"key":"2021012203204989200_ref17","first-page":"A68","article-title":"The cancer genome atlas (TCGA): an immeasurable source of knowledge","volume":"19","author":"Tomczak","year":"2015","journal-title":"Contemp Oncol"},{"key":"2021012203204989200_ref18","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1038\/nrg3555","article-title":"Rare-disease genetics in the era of next-generation sequencing: discovery to translation","volume":"14","author":"Boycott","year":"2013","journal-title":"Nat Rev Genet"},{"key":"2021012203204989200_ref19","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.ajhg.2018.11.014","article-title":"Integrating genomics into healthcare: a global responsibility","volume":"104","author":"Stark","year":"2019","journal-title":"Am J Hum Genet"},{"key":"2021012203204989200_ref20","doi-asserted-by":"crossref","first-page":"648","DOI":"10.1126\/science.1262110","article-title":"The genotype-tissue expression (GTEx) pilot analysis: multitissue gene regulation in humans","volume":"348","author":"GTEx Consortium. Human genomics","year":"2015","journal-title":"Science"},{"key":"2021012203204989200_ref21","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1002\/aur.1322","article-title":"Parental broader autism subphenotypes in ASD affected families: relationship to gender, child\u2019s symptoms, SSRI treatment, and platelet serotonin","volume":"6","author":"Levin-Decanini","year":"2013","journal-title":"Autism Res"},{"key":"2021012203204989200_ref22","doi-asserted-by":"crossref","first-page":"1223","DOI":"10.1080\/14622200802163266","article-title":"Race differences in nicotine dependence in the collaborative genetic study of nicotine dependence (COGEND)","volume":"10","author":"Luo","year":"2008","journal-title":"Nicotine Tob Res"},{"key":"2021012203204989200_ref23","doi-asserted-by":"crossref","first-page":"1420","DOI":"10.1001\/jama.295.12.1420","article-title":"Sex differences in platelet reactivity and response to low-dose aspirin therapy","volume":"295","author":"Becker","year":"2006","journal-title":"JAMA"},{"key":"2021012203204989200_ref24","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1086\/316927","article-title":"A genome scan for renal function among hypertensives: the HyperGEN study","volume":"68","author":"DeWan","year":"2001","journal-title":"Am J Hum Genet"},{"key":"2021012203204989200_ref25","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s00787-014-0543-x","article-title":"The Tourette international collaborative genetics (TIC genetics) study, finding the genes causing Tourette syndrome: objectives and methods","volume":"24","author":"Dietrich","year":"2015","journal-title":"Eur Child Adolesc Psychiatry"},{"key":"2021012203204989200_ref26","doi-asserted-by":"crossref","first-page":"32","DOI":"10.3109\/15412550903499522","article-title":"Genetic epidemiology of COPD (COPDGene) study design","volume":"7","author":"Regan","year":"2010","journal-title":"COPD"},{"key":"2021012203204989200_ref27","doi-asserted-by":"crossref","first-page":"999","DOI":"10.1016\/S0140-6736(13)61752-3","article-title":"The Framingham heart study and the epidemiology of cardiovascular disease: a historical perspective","volume":"383","author":"Mahmood","year":"2014","journal-title":"Lancet"},{"key":"2021012203204989200_ref28","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1089\/jwh.1995.4.519","article-title":"Informed consent in the Women\u2019s health initiative clinical trial and observational study","volume":"4","author":"McTIERNAN","year":"1995","journal-title":"J Womens Health"},{"key":"2021012203204989200_ref29","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1093\/oxfordjournals.aje.a115184","article-title":"The atherosclerosis risk in communities (ARIC) study: design and objectives. The ARIC investigators","volume":"129","author":"Szklo","year":"1989","journal-title":"Am J Epidemiol"},{"key":"2021012203204989200_ref30","article-title":"Study design for genetic analysis in the Jackson heart study","volume":"15","author":"Wilson","year":"2005","journal-title":"Ethn Dis"},{"key":"2021012203204989200_ref31","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/1047-2797(91)90005-W","article-title":"The cardiovascular health study: design and rationale","volume":"1","author":"Fried","year":"1991","journal-title":"Ann Epidemiol"},{"key":"2021012203204989200_ref32","doi-asserted-by":"crossref","first-page":"T20","DOI":"10.1016\/j.jpain.2013.07.014","article-title":"Signs and symptoms of first-onset TMD and sociodemographic predictors of its development: the OPPERA prospective cohort study","volume":"14","author":"Slade","year":"2013","journal-title":"J Pain"},{"key":"2021012203204989200_ref33","doi-asserted-by":"crossref","first-page":"1513","DOI":"10.1002\/mds.25175","article-title":"NINDS NET-PD investigators. Design innovations and baseline findings in a long-term Parkinson\u2019s trial: the National Institute of Neurological Disorders and Stroke exploratory trials in Parkinson's disease long-term Study-1","volume":"27","author":"Elm","year":"2012","journal-title":"Mov Disord"},{"key":"2021012203204989200_ref34","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1002\/mds.26438","article-title":"The NINDS Parkinson\u2019s disease biomarkers program","volume":"31","author":"Rosenthal","year":"2016","journal-title":"Mov Disord"},{"key":"2021012203204989200_ref35","doi-asserted-by":"crossref","first-page":"e0191319","DOI":"10.1371\/journal.pone.0191319","article-title":"The congenital heart disease genetic network study: cohort description","volume":"13","author":"Hoang","year":"2018","journal-title":"PLoS One"},{"key":"2021012203204989200_ref36","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1093\/aje\/kwf113","article-title":"Multi-ethnic study of atherosclerosis: objectives and design","volume":"156","author":"Bild","year":"2002","journal-title":"Am J Epidemiol"},{"key":"2021012203204989200_ref37","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1038\/ng.806","article-title":"A framework for variation discovery and genotyping using next-generation DNA sequencing data","volume":"43","author":"DePristo","year":"2011","journal-title":"Nat Genet"},{"key":"2021012203204989200_ref38","first-page":"201178","article-title":"Scaling accurate genetic variant discovery to tens of thousands of samples","author":"Poplin","year":"2018","journal-title":"bioRxiv"},{"key":"2021012203204989200_ref39","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1097\/FPC.0b013e32834fdd41","article-title":"A genome-wide association study of inflammatory biomarker changes in response to fenofibrate treatment in the genetics of lipid lowering drug and diet network","volume":"22","author":"Aslibekyan","year":"2012","journal-title":"Pharmacogenet Genomics"},{"key":"2021012203204989200_ref40","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1002\/ajhb.22553","article-title":"Prevalence of adiposity and associated cardiometabolic risk factors in the Samoan genome-wide association study","volume":"26","author":"Hawley","year":"2014","journal-title":"Am J Hum Biol"},{"key":"2021012203204989200_ref41","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1164\/ajrccm.159.5.9809079","article-title":"Risk factors for sleep-disordered breathing in children. Associations with obesity, race, and respiratory problems","volume":"159","author":"Redline","year":"1999","journal-title":"Am J Respir Crit Care Med"},{"key":"2021012203204989200_ref42","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1016\/j.amjmed.2003.12.032","article-title":"Familial aggregation of hypertension treatment and control in the genetic epidemiology network of Arteriopathy (GENOA) study","volume":"116","author":"Daniels","year":"2004","journal-title":"Am J Med"},{"key":"2021012203204989200_ref43","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1038\/nbt.1958","article-title":"Comprehensive catalog of European biobanks","volume":"29","author":"Wichmann","year":"2011","journal-title":"Nat Biotechnol"},{"key":"2021012203204989200_ref44","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1089\/bio.2016.0088","article-title":"BBMRI-ERIC directory: 515 biobanks with over 60 million biological samples","volume":"14","author":"Holub","year":"2016","journal-title":"Biopreserv Biobank"},{"key":"2021012203204989200_ref45","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.neuron.2010.10.006","article-title":"The Simons simplex collection: a resource for identification of autism genetic risk factors","volume":"68","author":"Fischbach","year":"2010","journal-title":"Neuron"},{"key":"2021012203204989200_ref46","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.ajhg.2017.01.006","article-title":"The undiagnosed diseases network: accelerating discovery about health and disease","volume":"100","author":"Ramoni","year":"2017","journal-title":"Am J Hum Genet"},{"key":"2021012203204989200_ref47","doi-asserted-by":"crossref","first-page":"21","DOI":"10.3390\/jpm7040021","article-title":"Development of the precision link biobank at Boston Children\u2019s hospital: challenges and opportunities","volume":"7","author":"Bourgeois","year":"2017","journal-title":"J Pers Med"},{"key":"2021012203204989200_ref48","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1038\/s41436-019-0646-3","article-title":"The genomics research and innovation network: creating an interoperable, federated, genomics learning system","volume":"22","author":"Mandl","year":"2019","journal-title":"Genet Med"},{"key":"2021012203204989200_ref49","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1146\/annurev-publhealth-031210-100700","article-title":"Administrative record linkage as a tool for public health research","volume":"32","author":"Jutte","year":"2011","journal-title":"Annu Rev Public Health"},{"key":"2021012203204989200_ref50","first-page":"2479","article-title":"Finding the missing link for big biomedical data","volume":"311","author":"Weber","year":"2014","journal-title":"JAMA"},{"key":"2021012203204989200_ref51","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1038\/nrg2999","article-title":"Using electronic health records to drive discovery in disease genomics","volume":"12","author":"Kohane","year":"2011","journal-title":"Nat Rev Genet"},{"key":"2021012203204989200_ref52","first-page":"1","article-title":"Using electronic health records to improve quality and efficiency: the experiences of leading hospitals","volume":"17","author":"Silow-Carroll","year":"2012","journal-title":"Issue Brief"},{"key":"2021012203204989200_ref53"},{"key":"2021012203204989200_ref54","doi-asserted-by":"crossref","first-page":"e54","DOI":"10.1542\/peds.2013-0819","article-title":"Comorbidity clusters in autism spectrum disorders: an electronic health record time-series analysis","volume":"133","author":"Doshi-Velez","year":"2014","journal-title":"Pediatrics"},{"key":"2021012203204989200_ref55","doi-asserted-by":"crossref","first-page":"h1885","DOI":"10.1136\/bmj.h1885","article-title":"Development of phenotype algorithms using electronic medical records and incorporating natural language processing","volume":"350","author":"Liao","year":"2015","journal-title":"BMJ"},{"key":"2021012203204989200_ref56","doi-asserted-by":"crossref","DOI":"10.14806\/ej.24.0.910","article-title":"Genomic big data hitting the storage bottleneck","volume":"24","author":"Papageorgiou","year":"2018","journal-title":"EMBnet J"},{"key":"2021012203204989200_ref57","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1136\/amiajnl-2014-002974","article-title":"The National Institutes of Health\u2019s big data to knowledge (BD2K) initiative: capitalizing on biomedical big data","volume":"21","author":"Margolis","year":"2014","journal-title":"J Am Med Inform Assoc"},{"key":"2021012203204989200_ref58","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1007\/s00439-011-1031-8","article-title":"Children and biobanks: a review of the ethical and legal discussion","volume":"130","author":"Hens","year":"2011","journal-title":"Hum Genet"},{"key":"2021012203204989200_ref59","doi-asserted-by":"crossref","first-page":"160018","DOI":"10.1038\/sdata.2016.18","article-title":"The FAIR guiding principles for scientific data management and stewardship","volume":"3","author":"Wilkinson","year":"2016","journal-title":"Scientific Data"},{"key":"2021012203204989200_ref60","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1016\/j.drudis.2019.01.008","article-title":"Implementation and relevance of FAIR data principles in biopharmaceutical R&D","volume":"24","author":"Wise","year":"2019","journal-title":"Drug Discov Today"},{"key":"2021012203204989200_ref61","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1038\/s41431-018-0160-0","article-title":"The FAIR guiding principles for data stewardship: fair enough?","volume":"26","author":"Boeckhout","year":"2018","journal-title":"Eur J Hum Genet"},{"key":"2021012203204989200_ref62","doi-asserted-by":"crossref","first-page":"49","DOI":"10.3233\/ISU-170824","article-title":"Cloudy, increasingly FAIR; revisiting the FAIR data guiding principles for the European Open Science cloud","volume":"37","author":"Mons","year":"2017","journal-title":"ISU"},{"key":"2021012203204989200_ref63","doi-asserted-by":"crossref","first-page":"e1007309","DOI":"10.1371\/journal.pgen.1007309","article-title":"Population structure in genetic studies: confounding factors and mixed models","volume":"14","author":"Sul","year":"2018","journal-title":"PLoS Genet"},{"key":"2021012203204989200_ref64","doi-asserted-by":"crossref","first-page":"1175","DOI":"10.1038\/ejhg.2016.17","article-title":"Multi-ethnic genome-wide association study identifies novel locus for type 2 diabetes susceptibility","volume":"24","author":"Cook","year":"2016","journal-title":"Eur J Hum Genet"},{"key":"2021012203204989200_ref65","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1038\/nrg2760","article-title":"Genome-wide association studies in diverse populations","volume":"11","author":"Rosenberg","year":"2010","journal-title":"Nat Rev Genet"},{"key":"2021012203204989200_ref66","doi-asserted-by":"crossref","first-page":"878","DOI":"10.1158\/2159-8290.CD-15-0315","article-title":"A large multiethnic genome-wide association study of prostate cancer identifies novel risk variants and substantial ethnic differences","volume":"5","author":"Hoffmann","year":"2015","journal-title":"Cancer Discov"},{"key":"2021012203204989200_ref67","doi-asserted-by":"crossref","first-page":"e1003419","DOI":"10.1371\/journal.pgen.1003419","article-title":"Genome-wide testing of putative functional exonic variants in relationship with breast and prostate cancer risk in a multiethnic population","volume":"9","author":"Haiman","year":"2013","journal-title":"PLoS Genet"},{"key":"2021012203204989200_ref68","doi-asserted-by":"crossref","first-page":"692","DOI":"10.1038\/ng.3312","article-title":"The European genome-phenome archive of human data consented for biomedical research","volume":"47","author":"Lappalainen","year":"2015","journal-title":"Nat Genet"},{"key":"2021012203204989200_ref69"},{"key":"2021012203204989200_ref70","doi-asserted-by":"crossref","first-page":"T12","DOI":"10.1016\/j.jpain.2011.08.001","article-title":"Study methods, recruitment, sociodemographic findings, and demographic representativeness in the OPPERA study","volume":"12","author":"Slade","year":"2011","journal-title":"J Pain"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bib\/article-pdf\/22\/1\/55\/35934635\/bbaa033.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/bib\/article-pdf\/22\/1\/55\/35934635\/bbaa033.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,1,23]],"date-time":"2021-01-23T11:44:42Z","timestamp":1611402282000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/22\/1\/55\/5816026"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,6]]},"references-count":70,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2020,4,6]]},"published-print":{"date-parts":[[2021,1,18]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbaa033","relation":{},"ISSN":["1477-4054"],"issn-type":[{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2021,1]]},"published":{"date-parts":[[2020,4,6]]}}}