A General Approach for Haplotype Phasing across the Full Spectrum of Relatedness

Jared O'Connell, Deepti Gurdasani, Olivier Delaneau, Nicola Pirastu, Sheila Ulivi, Massimiliano Cocca, Michela Traglia, Jie Huang, Jennifer E Huffman, Igor Rudan, Ruth McQuillan, Ross M Fraser, Harry Campbell, Ozren Polasek, Gershim Asiki, Kenneth Ekoru, Caroline Hayward, Alan F Wright, Veronique Vitart, Pau NavarroJean-Francois Zagury, James F Wilson, Daniela Toniolo, Paolo Gasparini, Nicole Soranzo, Manjinder S Sandhu, Jonathan Marchini

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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.
Original languageEnglish
Article numbere1004234
Number of pages21
JournalPLoS Genetics
Issue number4
Publication statusPublished - 17 Apr 2014


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