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Haplotype variation and genotype imputation in African populations

dc.contributor.authorHuang, Lucyen_US
dc.contributor.authorJakobsson, Mattiasen_US
dc.contributor.authorPemberton, Trevor J.en_US
dc.contributor.authorIbrahim, Muntaseren_US
dc.contributor.authorNyambo, Thomasen_US
dc.contributor.authorOmar, Sabahen_US
dc.contributor.authorPritchard, Jonathan K.en_US
dc.contributor.authorTishkoff, Sarah A.en_US
dc.contributor.authorRosenberg, Noah A.en_US
dc.date.accessioned2011-12-05T18:34:51Z
dc.date.available2013-02-01T20:26:19Zen_US
dc.date.issued2011-12en_US
dc.identifier.citationHuang, Lucy; Jakobsson, Mattias; Pemberton, Trevor J.; Ibrahim, Muntaser; Nyambo, Thomas; Omar, Sabah; Pritchard, Jonathan K.; Tishkoff, Sarah A.; Rosenberg, Noah A. (2011). "Haplotype variation and genotype imputation in African populations." Genetic Epidemiology 35(8): 766-780. <http://hdl.handle.net/2027.42/88099>en_US
dc.identifier.issn0741-0395en_US
dc.identifier.issn1098-2272en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/88099
dc.description.abstractSub‐Saharan Africa has been identified as the part of the world with the greatest human genetic diversity. This high level of diversity causes difficulties for genome‐wide association (GWA) studies in African populations—for example, by reducing the accuracy of genotype imputation in African populations compared to non‐African populations. Here, we investigate haplotype variation and imputation in Africa, using 253 unrelated individuals from 15 Sub‐Saharan African populations. We identify the populations that provide the greatest potential for serving as reference panels for imputing genotypes in the remaining groups. Considering reference panels comprising samples of recent African descent in Phase 3 of the HapMap Project, we identify mixtures of reference groups that produce the maximal imputation accuracy in each of the sampled populations. We find that optimal HapMap mixtures and maximal imputation accuracies identified in detailed tests of imputation procedures can instead be predicted by using simple summary statistics that measure relationships between the pattern of genetic variation in a target population and the patterns in potential reference panels. Our results provide an empirical basis for facilitating the selection of reference panels in GWA studies of diverse human populations, especially those of African ancestry. Genet. Epidemiol . 35:766–780, 2011. © 2011 Wiley Periodicals, Inc.en_US
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.subject.otherHaplotype Variationen_US
dc.subject.otherImputationen_US
dc.subject.otherLinkage Disequilibriumen_US
dc.titleHaplotype variation and genotype imputation in African populationsen_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.affiliationumCenter for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michiganen_US
dc.contributor.affiliationotherDepartment of Evolutionary Biology, Uppsala University, Uppsala, Swedenen_US
dc.contributor.affiliationotherDepartment of Biology, Stanford University, Stanford, Californiaen_US
dc.contributor.affiliationotherDepartment of Molecular Biology, Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudanen_US
dc.contributor.affiliationotherDepartment of Biochemistry, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzaniaen_US
dc.contributor.affiliationotherKenya Medical Research Institute, Center for Biotechnology Research and Development, Nairobi, Kenyaen_US
dc.contributor.affiliationotherDepartment of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, Illinoisen_US
dc.contributor.affiliationotherDepartment of Biology and Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvaniaen_US
dc.contributor.affiliationotherDepartment of Biology, Stanford University, Stanford, Californiaen_US
dc.identifier.pmid22125220en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/88099/1/20626_ftp.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/88099/2/gepi_20626_sm_SuppInfo.pdf
dc.identifier.doi10.1002/gepi.20626en_US
dc.identifier.sourceGenetic Epidemiologyen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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