A General Approach for Haplotype Phasing across the Full Spectrum of Relatedness
By Jared O’Connell, D. Gurdasani, Olivier Delaneau, N. Pirastu, Sheila Ulivi, M. Cocca, M. Traglia, Jie Huang, J. Huffman, I. Rudan and 17 more. PLoS Genetics, 2014
602 citations recorded by the source corpus.
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.
Subfields: Genetics
View Paper: https://www.semanticscholar.org/paper/bdc1bdb0a00d9c635925c3ebd7655aac096ccab3
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Citations in the corpus
- High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios (2021, positive): “We performed haplotype phasing of high quality autosomal SNVs and INDELs across the 3,202-sample 1kGP cohort using statistical phasing with pedigree-based correction, as implemented in the SHAPEIT2-duohmm software 28,29 .”
- Identification of type 2 diabetes subgroups through topological analysis of patient similarity (2015, methodology): “After quality control for call quality and population equilibrium, the genotype data were phased by ShapeIt v2 r644 (75), yielding 850,067 SNPs, and then imputed by IMPUTE2.”
- WhatsHap: Weighted Haplotype Assembly for Future-Generation Sequencing Reads (2015, background): “…between 0.1 and 0.25% of positions are affected by phasing errors), when comparing them to error rates that can be achieved by statistical phasers, which usually amount to at least 1%; see, for example, O’Connell et al. (2014) (Table 1 on ‘‘unrelated individuals’’) for evaluations of such methods.”