Accurate knowledge of haplotypes, the combination of alleles co‐residing on a single copy of a chromosome, enables powerful gene mapping and sequence imputation methods. Since humans are diploid, haplotypes must be derived from genotypes by a phasing process. In this study, we present a new computational model for haplotype phasing based on pairwise sharing of haplotypes inferred to be Identical‐By‐Descent (IBD). We apply the Bayesian network based model in a new phasing algorithm, called systematic long‐range phasing (SLRP), that can capitalize on the close genetic relationships in isolated founder populations, and show with simulated and real genome‐wide genotype data that SLRP substantially reduces the rate of phasing errors compared to previous phasing algorithms. Furthermore, the method accurately identifies regions of IBD, enabling linkage‐like studies without pedigrees, and can be used to impute most genotypes with very low error rate. Genet. Epidemiol. 2011. © 2011 Wiley Periodicals, Inc.35:853‐860, 2011
Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models
Kimmo Palin,H. Campbell,A. Wright,James F. Wilson,R. Durbin
Published 2011 in Genetic Epidemiology
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- Publication year
2011
- Venue
Genetic Epidemiology
- Publication date
2011-10-17
- Fields of study
Biology, Medicine, Computer Science
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Semantic Scholar, PubMed
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