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Genotype phasing in pedigrees using whole-genome sequence data


Blackburn, AN and Blondell, L and Kos, MZ and Blackburn, NB and Peralta, JM and Stevens, PT and Lehman, DM and Blangero, J and Goring, HHH, Genotype phasing in pedigrees using whole-genome sequence data, European Journal of Human Genetics, 28, (6) pp. 790-803. ISSN 1018-4813 (2020) [Refereed Article]

Copyright Statement

The Author(s), under exclusive licence to European Society of Human Genetics 2020

DOI: doi:10.1038/s41431-020-0574-3


Phasing is the process of inferring haplotypes from genotype data. Efficient algorithms and associated software for accurate phasing in pedigrees are needed, especially for populations lacking reference panels of sequenced individuals. We present a novel method for phasing genotypes from whole-genome sequence data in pedigrees, called PULSAR (Phasing Using Lineage Specific Alleles/Rare variants). The method is based on the property that alleles specific to a single founding chromosome within a pedigree are highly informative for identifying haplotypes that are shared identical by descent. Simulation studies are used to assess the performance of PULSAR with various pedigree sizes and structures, and the effect of genotyping errors and the presence of nonsequenced individuals is investigated. In pedigrees with complete sequencing and realistic genotyping error rates, PULSAR correctly phases >99.9% of heterozygous genotypes, excluding sites at which all individuals are heterozygous, and does so with a switch error rate frequently below 10-4. PULSAR is highly accurate, capable of genotype error correction and imputation, and computationally competitive with alternative phasing software applicable to pedigrees. Our method has the significant advantage of not requiring reference panels that are essential for other population-based phasing algorithms. A software implementation of PULSAR is freely available.

Item Details

Item Type:Refereed Article
Keywords:genetics, genomics, pedigree
Research Division:Biological Sciences
Research Group:Bioinformatics and computational biology
Research Field:Statistical and quantitative genetics
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the biological sciences
UTAS Author:Blackburn, NB (Dr Nicholas Blackburn)
ID Code:144986
Year Published:2020
Web of Science® Times Cited:2
Deposited By:Menzies Institute for Medical Research
Deposited On:2021-06-23
Last Modified:2021-10-01

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