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Genotype imputation is the term used to describe the process of predicting or imputing genotypes that are not directly assayed in a sample of individuals. Imputation methods attempt to identify sharing between the underlying haplotypes of the study individuals and the haplotypes in the reference set and use this sharing to impute the missing alleles in study individuals. There are strong connections between the models and methods used to infer haplotype phase and those used to perform genotype imputation, as well as strong connections to tagging SNP-based approaches and methods used in linkage studies. This chapter concerns the main uses of imputation, a description and comparison of the different methods that are proposed for imputation. It also discusses the factors that affect imputation performance and how imputed genotypes can be used to test for association. Imputation is used to boost power, fine-mapping, and meta-analysis. Several different methods that are proposed to carry out genotype imputation can be broadly grouped into two main classes of methods: SNP tagging-based approaches that use only a small number of tagSNPs to impute each SNP, and approaches that use more of the flanking genotype data to impute each SNP through the use of various types of hidden Markov models. © 2011 Elsevier Inc. All rights reserved.

Original publication

DOI

10.1016/B978-0-12-375142-3.10010-0

Type

Journal article

Publication Date

01/12/2011

Pages

157 - 175