Methods of genotype imputation for genome-wide association studies

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dc.contributor.advisorDaniels, Michael Joseph
dc.contributor.committeeMemberLin, Lizhen
dc.creatorQiu, Lin, M.S. in Statistiscs
dc.date.accessioned2016-10-24T19:26:44Z
dc.date.accessioned2018-01-22T22:30:52Z
dc.date.available2016-10-24T19:26:44Z
dc.date.available2018-01-22T22:30:52Z
dc.date.issued2016-08
dc.date.submittedAugust 2016
dc.date.updated2016-10-24T19:26:44Z
dc.description.abstractIn genetic epidemiological studies, missing data problems arise when genotypes of particular markers are unavailable for reasons of data quality, cost efficiency or technical design. Genotype imputation is a well-established statistical technique for estimating unobserved genotypes in association studies. Imputation methods are implemented by copying haplotype segments from a densely genotyped reference panel into individuals typed at a subset of the reference variants. By this way, genotypes can be estimated and tested for association at variants that were not assayed in a study. This report first summarizes the missing data mechanisms. Then an overview of the different methods that have been proposed for genotype imputation is provided and some thoughts for future directions are given.
dc.format.mimetypeapplication/pdf
dc.identifierdoi:10.15781/T2RJ48W78
dc.identifier.urihttp://hdl.handle.net/2152/41868
dc.language.isoen
dc.subjectMissing Data
dc.subjectGenotype
dc.subjectIMPUTE
dc.subjectFastPHASE
dc.subjectMaCH
dc.subjectBEAGLE
dc.titleMethods of genotype imputation for genome-wide association studies
dc.typeThesis
dc.type.materialtext

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