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Optimal designs for two-stage genome-wide association studies

dc.contributor.authorSkol, Andrew D.en_US
dc.contributor.authorScott, Laura J.en_US
dc.contributor.authorAbecasis, Gonçalo R.en_US
dc.contributor.authorBoehnke, Michaelen_US
dc.date.accessioned2007-12-04T18:31:35Z
dc.date.available2008-11-05T15:05:43Zen_US
dc.date.issued2007-11en_US
dc.identifier.citationSkol, Andrew D.; Scott, Laura J.; Abecasis, GonÇalo R.; Boehnke, Michael (2007). "Optimal designs for two-stage genome-wide association studies." Genetic Epidemiology 31(7): 776-788. <http://hdl.handle.net/2027.42/57367>en_US
dc.identifier.issn0741-0395en_US
dc.identifier.issn1098-2272en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/57367
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=17549752&dopt=citation
dc.description.abstractGenome-wide association (GWA) studies require genotyping hundreds of thousands of markers on thousands of subjects, and are expensive at current genotyping costs. To conserve resources, many GWA studies are adopting a staged design in which a proportion of the available samples are genotyped on all markers in stage 1, and a proportion of these markers are genotyped on the remaining samples in stage 2. We describe a strategy for designing cost-effective two-stage GWA studies. Our strategy preserves much of the power of the corresponding one-stage design and minimizes the genotyping cost of the study while allowing for differences in per genotyping cost between stages 1 and 2. We show that the ratio of stage 2 to stage 1 per genotype cost can strongly influence both the optimal design and the genotyping cost of the study. Increasing the stage 2 per genotype cost shifts more of the genotyping and study cost to stage 1, and increases the cost of the study. This higher cost can be partially mitigated by adopting a design with reduced power while preserving the false positive rate or by increasing the false positive rate while preserving power. For example, reducing the power preserved in the two-stage design from 99 to 95% that of the one-stage design decreases the two-stage study cost by ∼15%. Alternatively, the same cost savings can be had by relaxing the false positive rate by 2.5-fold, for example from 1/300,000 to 2.5/300,000, while retaining the same power. Genet. Epidemiol . 2007. © 2007 Wiley-Liss, Inc.en_US
dc.format.extent326246 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.subject.otherLife and Medical Sciencesen_US
dc.subject.otherGeneticsen_US
dc.titleOptimal designs for two-stage genome-wide association studiesen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelBiological Chemistryen_US
dc.subject.hlbsecondlevelGeneticsen_US
dc.subject.hlbsecondlevelMolecular, Cellular and Developmental Biologyen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan ; Department of Medicine, Section of Genetic Medicine, University of Chicago, Chicago, Illinois ; Department of Medicine, Section of Genetic Medicine, University of Chicago, 5841 South Maryland Avenue, W611A – MC6091, Chicago, Illinois 60637en_US
dc.contributor.affiliationumDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michiganen_US
dc.contributor.affiliationumDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michiganen_US
dc.contributor.affiliationumDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michiganen_US
dc.identifier.pmid17549752
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/57367/1/20240_ftp.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1002/gepi.20240en_US
dc.identifier.sourceGenetic Epidemiologyen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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