Abstract
The UK Biobank (UKB) has recently released genotypes on 152,328 individuals together with extensive phenotypic and lifestyle information. We present a new phasing method SHAPEIT3 that can handle such biobank scale datasets and results in switch error rates as low as ~0.3%. The method exhibits O(NlogN) scaling in sample size (N), enabling fast and accurate phasing of even larger cohorts.
Highlights
Estimation of haplotypes from genotypes, known as phasing, is a central part of the pipeline of many modern genetic analyses
Estimated haplotypes are important for many population genetics analyses[1,2], and form a central part of imputation algorithms that are routinely used in genome-wide association studies (GWAS) 3,4
We have demonstrated that SHAPEIT3 provides a highly accurate and scalable solution to phasing biobank scale datasets
Summary
Estimation of haplotypes from genotypes, known as phasing, is a central part of the pipeline of many modern genetic analyses. Estimated haplotypes are important for many population genetics analyses[1,2], and form a central part of imputation algorithms that are routinely used in genome-wide association studies (GWAS) 3,4. The ability to phase large data sets is especially important in the context of biobanks that comprise hundreds of thousands of genotyped samples. In May 2015 the UK Biobank (UKB) released genotypes from ~152,000 samples, and this will rise to ~500,000 in 2016. Other Biobanks have already collected large scale genetic datasets[5] or are in the process of doing so[6]. The unprecedented scale of these datasets, and the depth of phenotype information, allows researchers studying
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