Premium
Identity‐by‐descent‐based phasing and imputation in founder populations using graphical models
Author(s) -
Palin Kimmo,
Campbell Harry,
Wright Alan F.,
Wilson James F.,
Durbin Richard
Publication year - 2011
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.20635
Subject(s) - identity by descent , phaser , imputation (statistics) , haplotype , pedigree chart , pairwise comparison , biology , genetics , genome , ploidy , haplotype estimation , computational biology , genotype , computer science , artificial intelligence , missing data , gene , machine learning , physics , optics
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