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PLoS Genet. 2014 Apr 17;10(4):e1004234. doi: 10.1371/journal.pgen.1004234. eCollection 2014 Apr.

A general approach for haplotype phasing across the full spectrum of relatedness.

Author information

1
Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom; Department of Statistics, University of Oxford, Oxford, United Kingdom.
2
Wellcome Trust Sanger Institute, Hinxton, United Kingdom; Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
3
Department of Statistics, University of Oxford, Oxford, United Kingdom.
4
Institute for Maternal and Child Health - IRCCS Burlo Garofolo, University of Trieste, Trieste, Italy.
5
Institute for Maternal and Child Health - IRCCS Burlo Garofolo, Trieste, Italy.
6
Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy.
7
Wellcome Trust Sanger Institute, Hinxton, United Kingdom.
8
MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom.
9
Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom.
10
Faculty of Medicine, University of Split, Split, Croatia.
11
Medical Research Council/Uganda Virus Research Institute (MRC/UVRI), Uganda Research Unit on AIDS, Entebbe, Uganda.
12
Laboratoire Génomique, Bioinformatique, et Applications (EA4627), Conservatoire National des Arts et Métiers, Paris, France.

Abstract

Many existing cohorts contain a range of relatedness between genotyped individuals, either by design or by chance. Haplotype estimation in such cohorts is a central step in many downstream analyses. Using genotypes from six cohorts from isolated populations and two cohorts from non-isolated populations, we have investigated the performance of different phasing methods designed for nominally 'unrelated' individuals. We find that SHAPEIT2 produces much lower switch error rates in all cohorts compared to other methods, including those designed specifically for isolated populations. In particular, when large amounts of IBD sharing is present, SHAPEIT2 infers close to perfect haplotypes. Based on these results we have developed a general strategy for phasing cohorts with any level of implicit or explicit relatedness between individuals. First SHAPEIT2 is run ignoring all explicit family information. We then apply a novel HMM method (duoHMM) to combine the SHAPEIT2 haplotypes with any family information to infer the inheritance pattern of each meiosis at all sites across each chromosome. This allows the correction of switch errors, detection of recombination events and genotyping errors. We show that the method detects numbers of recombination events that align very well with expectations based on genetic maps, and that it infers far fewer spurious recombination events than Merlin. The method can also detect genotyping errors and infer recombination events in otherwise uninformative families, such as trios and duos. The detected recombination events can be used in association scans for recombination phenotypes. The method provides a simple and unified approach to haplotype estimation, that will be of interest to researchers in the fields of human, animal and plant genetics.

PMID:
24743097
PMCID:
PMC3990520
DOI:
10.1371/journal.pgen.1004234
[Indexed for MEDLINE]
Free PMC Article

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