title: A comparison of phasing algorithms for trios and unrelated individuals.
abstract: Knowledge of haplotype phase is valuable for many analysis methods in the study of disease, population, and evolutionary genetics. Considerable research effort has been devoted to the development of statistical and computational methods that infer haplotype phase from genotype data. Although a substantial number of such methods have been developed, they have focused principally on inference from unrelated individuals, and comparisons between methods have been rather limited. Here, we describe the extension of five leading algorithms for phase inference for handling father-mother-child trios. We performed a comprehensive assessment of the methods applied to both trios and to unrelated individuals, with a focus on genomic-scale problems, using both simulated data and data from the HapMap project. The most accurate algorithm was PHASE (v2.1). For this method, the percentages of genotypes whose phase was incorrectly inferred were 0.12%, 0.05%, and 0.16% for trios from simulated data, HapMap Centre d'Etude du Polymorphisme Humain (CEPH) trios, and HapMap Yoruban trios, respectively, and 5.2% and 5.9% for unrelated individuals in simulated data and the HapMap CEPH data, respectively. The other methods considered in this work had comparable but slightly worse error rates. The error rates for trios are similar to the levels of genotyping error and missing data expected. We thus conclude that all the methods considered will provide highly accurate estimates of haplotypes when applied to trio data sets. Running times differ substantially between methods. Although it is one of the slowest methods, PHASE (v2.1) was used to infer haplotypes for the 1 million-SNP HapMap data set. Finally, we evaluated methods of estimating the value of r(2) between a pair of SNPs and concluded that all methods estimated r(2) well when the estimated value was >or=0.8.
authors.affiliation: Department of Statistics, University of Oxford, Oxford OX1 3TG, United Kingdom. marchini@stats.ox.ac.uk
authors.forename: Jonathan
authors.initials: J
authors.lastname: Marchini
authors.forename: David
authors.initials: D
authors.lastname: Cutler
authors.forename: Nick
authors.initials: N
authors.lastname: Patterson
authors.forename: Matthew
authors.initials: M
authors.lastname: Stephens
authors.forename: Eleazar
authors.initials: E
authors.lastname: Eskin
authors.forename: Eran
authors.initials: E
authors.lastname: Halperin
authors.forename: Shin
authors.initials: S
authors.lastname: Lin
authors.forename: Zhaohui S
authors.initials: ZS
authors.lastname: Qin
authors.forename: Heather M
authors.initials: HM
authors.lastname: Munro
authors.forename: Goncalo R
authors.initials: GR
authors.lastname: Abecasis
authors.forename: Peter
authors.initials: P
authors.lastname: Donnelly
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005824:Genetics, Behavioral / Q000379:methods*; D006239:Haplotypes / Q000235:genetics*; D006801:Humans; D010287:Parent-Child Relations; D020641:Polymorphism, Single Nucleotide