Haplotype association analysis for late onset diseases using nuclear family data
dc.contributor.author | Li, Chun | en_US |
dc.contributor.author | Boehnke, Michael | en_US |
dc.date.accessioned | 2007-05-02T14:16:50Z | |
dc.date.available | 2007-05-02T14:16:50Z | |
dc.date.issued | 2006-04 | en_US |
dc.identifier.citation | Li, Chun; Boehnke, Michael (2006). "Haplotype association analysis for late onset diseases using nuclear family data." Genetic Epidemiology 30(3): 220-230. <http://hdl.handle.net/2027.42/50656> | en_US |
dc.identifier.issn | 0741-0395 | en_US |
dc.identifier.issn | 1098-2272 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/50656 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=16470533&dopt=citation | en_US |
dc.description.abstract | In haplotype-based association studies for late onset diseases, one attractive design is to use available unaffected spouses as controls (Valle et al. [1998] Diab. Care 21:949–958). Given cases and spouses only, the standard expectation-maximization (EM) algorithm (Dempster et al. [1977] J. R. Stat. Soc. B 39:1–38) for case-control data can be used to estimate haplotype frequencies. But often we will have offspring for at least some of the spouse pairs, and offspring genotypes provide additional information about the haplotypes of the parents. Existing methods may either ignore the offspring information, or reconstruct haplotypes for the subjects using offspring information and discard data from those whose haplotypes cannot be reconstructed with high confidence. Neither of these approaches is efficient, and the latter approach may also be biased. For case-control data with some subjects forming spouse pairs and offspring genotypes available for some spouse pairs or individuals, we propose a unified, likelihood-based method of haplotype inference. The method makes use of available offspring genotype information to apportion ambiguous haplotypes for the subjects. For subjects without offspring genotype information, haplotypes are apportioned as in the standard EM algorithm for case-control data. Our method enables efficient haplotype frequency estimation using an EM algorithm and supports probabilistic haplotype reconstruction with the probability calculated based on the whole sample. We describe likelihood ratio and permutation tests to test for disease-haplotype association, and describe three test statistics that are potentially useful for detecting such an association. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. | en_US |
dc.format.extent | 215077 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.publisher | Wiley Subscription Services, Inc., A Wiley Company | en_US |
dc.subject.other | Life and Medical Sciences | en_US |
dc.subject.other | Genetics | en_US |
dc.title | Haplotype association analysis for late onset diseases using nuclear family data | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Biological Chemistry | en_US |
dc.subject.hlbsecondlevel | Genetics | en_US |
dc.subject.hlbsecondlevel | Molecular, Cellular and Developmental Biology | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan | en_US |
dc.contributor.affiliationother | Department of Biostatistics, Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee ; Center for Human Genetics Research, Vanderbilt University Medical Center, 519 Light Hall, Nashville, TN 37232-0700 | en_US |
dc.identifier.pmid | 16470533 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/50656/1/20139_ftp.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1002/gepi.20139 | en_US |
dc.identifier.source | Genetic Epidemiology | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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