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Improving Estimates of Genetic Maps: A Maximum Likelihood Approach
dc.contributor.authorStewart, William C. L.en_US
dc.contributor.authorThompson, Elizabeth A.en_US
dc.date.accessioned2010-04-01T15:46:45Z
dc.date.available2010-04-01T15:46:45Z
dc.date.issued2006-09en_US
dc.identifier.citationStewart, William C. L.; Thompson, Elizabeth A. (2006). "Improving Estimates of Genetic Maps: A Maximum Likelihood Approach." Biometrics 62(3): 728-734. <http://hdl.handle.net/2027.42/66271>en_US
dc.identifier.issn0006-341Xen_US
dc.identifier.issn1541-0420en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/66271
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=16984314&dopt=citationen_US
dc.description.abstractAs a result of previous large, multipoint linkage studies there is a substantial amount of existing marker data. Due to the increased sample size, genetic maps estimated from these data could be more accurate than publicly available maps. However, current methods for map estimation are restricted to data sets containing pedigrees with a small number of individuals, or cannot make full use of marker data that are observed at several loci on members of large, extended pedigrees. In this article, a maximum likelihood (ML) method for map estimation that can make full use of the marker data in a large, multipoint linkage study is described. The method is applied to replicate sets of simulated marker data involving seven linked loci, and pedigree structures based on the real multipoint linkage study of Abkevich et al. (2003, American Journal of Human Genetics 73, 1271–1281). The variance of the ML estimate is accurately estimated, and tests of both simple and composite null hypotheses are performed. An efficient procedure for combining map estimates over data sets is also suggested.en_US
dc.format.extent279366 bytes
dc.format.extent3110 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherBlackwell Publishing Incen_US
dc.rights2006, The International Biometric Societyen_US
dc.subject.otherMap Estimationen_US
dc.subject.otherMultipoint Linkage Analysisen_US
dc.subject.otherOptimization Algorithmsen_US
dc.subject.otherStochastic Approximationen_US
dc.titleImproving Estimates of Genetic Maps: A Maximum Likelihood Approachen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumCurrent address: Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109-2029, U.S.A.en_US
dc.contributor.affiliationotherDepartment of Statistics, University of Washington, Seattle, Washington 98195, U.S.A.en_US
dc.identifier.pmid16984314en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/66271/1/j.1541-0420.2006.00532.x.pdf
dc.identifier.doi10.1111/j.1541-0420.2006.00532.xen_US
dc.identifier.sourceBiometricsen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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