Title |
Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel
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Published in |
Nature Communications, September 2015
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DOI | 10.1038/ncomms9111 |
Pubmed ID | |
Authors |
Jie Huang, Bryan Howie, Shane McCarthy, Yasin Memari, Klaudia Walter, Josine L. Min, Petr Danecek, Giovanni Malerba, Elisabetta Trabetti, Hou-Feng Zheng, Giovanni Gambaro, J. Brent Richards, Richard Durbin, Nicholas J. Timpson, Jonathan Marchini, Nicole Soranzo |
Abstract |
Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 19% |
United Kingdom | 5 | 12% |
Denmark | 2 | 5% |
Israel | 1 | 2% |
South Africa | 1 | 2% |
Germany | 1 | 2% |
Finland | 1 | 2% |
Netherlands | 1 | 2% |
Saudi Arabia | 1 | 2% |
Other | 0 | 0% |
Unknown | 21 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 25 | 60% |
Scientists | 15 | 36% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | 1% |
Italy | 2 | <1% |
United States | 2 | <1% |
Netherlands | 1 | <1% |
Australia | 1 | <1% |
South Africa | 1 | <1% |
Finland | 1 | <1% |
France | 1 | <1% |
Canada | 1 | <1% |
Other | 3 | <1% |
Unknown | 344 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 95 | 26% |
Student > Ph. D. Student | 83 | 23% |
Student > Master | 25 | 7% |
Professor | 20 | 6% |
Other | 15 | 4% |
Other | 49 | 14% |
Unknown | 74 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 89 | 25% |
Agricultural and Biological Sciences | 79 | 22% |
Medicine and Dentistry | 52 | 14% |
Engineering | 8 | 2% |
Computer Science | 7 | 2% |
Other | 29 | 8% |
Unknown | 97 | 27% |