Sohns, Melanie

[["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Genetic Epidemiology"],["dc.bibliographiccitation.volume","36"],["dc.contributor.author","Sohns, Melanie"],["dc.contributor.author","Viktorova, Elena"],["dc.contributor.author","Fehringer, Gord"],["dc.contributor.author","Gaborieau, Valerie"],["dc.contributor.author","Han, Younghun"],["dc.contributor.author","Chang-Claude, Jenny"],["dc.contributor.author","Heinrich, Joachim"],["dc.contributor.author","Risch, Angela"],["dc.contributor.author","Amos, Christopher I."],["dc.contributor.author","Brennan, P. C."],["dc.contributor.author","Hung, Rayjean J."],["dc.contributor.author","Bickeboeller, Heike"],["dc.date.accessioned","2018-11-07T09:04:08Z"],["dc.date.available","2018-11-07T09:04:08Z"],["dc.date.issued","2012"],["dc.format.extent","756"],["dc.identifier.isi","000309913200133"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/25044"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.publisher.place","Hoboken"],["dc.relation.conference","Annual Meeting of the International-Genetic-Epidemiology-Society (IGES)"],["dc.relation.eventlocation","Stevenson, WA"],["dc.relation.issn","0741-0395"],["dc.title","Application of the Empirical Hierarchical Bayes Approach for Gene-Environment Interaction to TRICL Lung Cancer GWAS"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","551"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Genetic Epidemiology"],["dc.bibliographiccitation.lastpage","559"],["dc.bibliographiccitation.volume","37"],["dc.contributor.author","Sohns, Melanie"],["dc.contributor.author","Viktorova, Elena"],["dc.contributor.author","Amos, Christopher I."],["dc.contributor.author","Brennan, P. C."],["dc.contributor.author","Fehringer, Gord"],["dc.contributor.author","Gaborieau, Valerie"],["dc.contributor.author","Han, Younghun"],["dc.contributor.author","Heinrich, Joachim"],["dc.contributor.author","Chang-Claude, Jenny"],["dc.contributor.author","Hung, Rayjean J."],["dc.contributor.author","Müller-Nurasyid, Martina"],["dc.contributor.author","Risch, Angela"],["dc.contributor.author","Lewinger, Juan Pablo"],["dc.contributor.author","Thomas, Duncan C."],["dc.contributor.author","Bickeböller, Heike"],["dc.date.accessioned","2018-11-07T09:20:57Z"],["dc.date.available","2018-11-07T09:20:57Z"],["dc.date.issued","2013"],["dc.description.abstract","The analysis of gene-environment (G x E) interactions remains one of the greatest challenges in the postgenome-wide association studies (GWASs) era. Recent methods constitute a compromise between the robust but underpowered case-control and powerful case-only methods. Inferences of the latter are biased when the assumption of gene-environment (G-E) independence in controls fails. We propose a novel empirical hierarchical Bayes approach to G x E interaction (EHB-GE), which benefits from greater rank power while accounting for population-based G-E correlation. Building on Lewinger et al.'s ([2007] Genet Epidemiol 31:871-882) hierarchical Bayes prioritization approach, the method first obtains posterior G-E correlation estimates in controls for each marker, borrowing strength from G-E information across the genome. These posterior estimates are then subtracted from the corresponding case-only G x E estimates. We compared EHB-GE with rival methods using simulation. EHB-GE has similar or greater rank power to detect G x E interactions in the presence of large numbers of G-E correlations with weak to strong effects or only a low number of such correlations with large effect. When there are no or only a few weak G-E correlations, Murcray et al.'s method ([2009] Am J Epidemiol 169:219-226) identifies markers with low G x E interaction effects better. We applied EHB-GE and competing methods to four lung cancer case-control GWAS from the Interdisciplinary Research in Cancer of the Lung/International Lung Cancer Consortium with smoking as environmental factor. A number of genes worth investigating were identified by the EHB-GE approach."],["dc.description.sponsorship","NIH [TRICL 5U19CA148127-03]; DFG GRK [1034]"],["dc.identifier.doi","10.1002/gepi.21741"],["dc.identifier.isi","000322911100003"],["dc.identifier.pmid","23893921"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/28998"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","0741-0395"],["dc.title","Empirical Hierarchical Bayes Approach to Gene-Environment Interactions: Development and Application to Genome-Wide Association Studies of Lung Cancer in TRICL"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]