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dc.contributor.authorSalanti, G.en
dc.contributor.authorHiggins, J. P.en
dc.date.accessioned2015-11-24T19:04:44Z-
dc.date.available2015-11-24T19:04:44Z-
dc.identifier.issn0277-6715-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/20094-
dc.rightsDefault Licence-
dc.subjectGenetic Predisposition to Diseaseen
dc.subject*Genetic Researchen
dc.subject*Genotypeen
dc.subjectHumansen
dc.subject*Meta-Analysis as Topicen
dc.subject*Models, Statisticalen
dc.titleMeta-analysis of genetic association studies under different inheritance models using data reported as merged genotypesen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primary10.1002/sim.2919-
heal.identifier.secondaryhttp://www.ncbi.nlm.nih.gov/pubmed/17576642-
heal.identifier.secondaryhttp://onlinelibrary.wiley.com/store/10.1002/sim.2919/asset/2919_ftp.pdf?v=1&t=h0dojecl&s=3dfbab719160bec5e01b860a38d8becb9c245702-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικήςel
heal.publicationDate2008-
heal.abstractMeta-analysis of population-based genetic association studies is often challenged by obstacles associated with the underlying inheritance model. For a simple genetic variant with two alleles, a recessive, dominant or co-dominant model is typically assumed. In the absence of a strong biological rationale for a particular inheritance model, a recently suggested inheritance-model-free approach can be implemented. To enable a flexible choice among these models, summary results from each of the three genotypes are required. Incompatibility of the data across studies because of different inheritance models is a common problem. For instance, if the underlying model is dominant, studies that have assumed the recessive model and presented the results accordingly, have so far been excluded from the meta-analysis. We show how to combine data and make inferences under any inheritance model, irrespective of the models assumed within each study and the way that data are presented. Within a Bayesian framework we describe prospective models for binary and continuous outcomes, and retrospective models for binary outcomes. The methods exploit an assumption of Hardy-Weinberg equilibrium, prior information about genotype prevalence or assumption of a specific inheritance model. On application to meta-analyses of the associations between a polymorphism in the lipoprotein lipase gene and coronary heart disease or high-density lipoprotein cholesterol, we observe substantial gains in precision when there is a large proportion of studies in which different inheritance models have been assumed.en
heal.journalNameStat Meden
heal.journalTypepeer-reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΙΑΤ

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