期刊
NATURE COMMUNICATIONS
卷 6, 期 -, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/ncomms9111
关键词
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资金
- Wellcome Trust [WT091310, WT098051]
- European Commission [257082, HEALTH-F5-2011-282510]
- NIHR
- CIHR
- CQDM
- FRSQ
- Jewish General Hospital
- Canadian Institutes of Health Research
- ERC [617306]
- UK Medical Research Council (MRC) [MC_UU_12013/3]
- British Heart Foundation [RG/10/13/28570, PG/13/66/30442] Funding Source: researchfish
- Economic and Social Research Council [ES/M001660/1] Funding Source: researchfish
- Medical Research Council [MC_UU_12012/5/B, MC_PC_15018, MC_UU_12013/3, MC_UU_12013/1, MC_UU_12015/1, G0800509, MR/L010305/1] Funding Source: researchfish
- National Institute for Health Research [NF-SI-0513-10008, NF-SI-0514-10176, NF-SI-0507-10380, NF-SI-0510-10268, NF-SI-0514-10027, NF-SI-0508-10198, NF-SI-0513-10109] Funding Source: researchfish
- ESRC [ES/M001660/1] Funding Source: UKRI
- MRC [MC_UU_12015/1, MC_UU_12013/3, MC_UU_12013/1, G0800509] Funding Source: UKRI
- European Research Council (ERC) [617306] Funding Source: European Research Council (ERC)
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 7,562WGS 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.
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