Journal
NATURE COMMUNICATIONS
Volume 10, Issue -, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41467-019-13225-y
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Funding
- Swiss National Science Foundation (SNSF) [PP00P3_176977, 31003A-179380]
- University of Lausanne
- European Research Council (ERC) [617306]
- LouisJeantet Foundation
- European Research Council
- Swiss National Science Foundation
- UK Biobank project [35520]
- Swiss National Science Foundation (SNF) [31003A_179380, PP00P3_176977] Funding Source: Swiss National Science Foundation (SNF)
- MRC [MC_PC_12028] Funding Source: UKRI
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The number of human genomes being genotyped or sequenced increases exponentially and efficient haplotype estimation methods able to handle this amount of data are now required. Here we present a method, SHAPEIT4, which substantially improves upon other methods to process large genotype and high coverage sequencing datasets. It notably exhibits sub-linear running times with sample size, provides highly accurate haplotypes and allows integrating external phasing information such as large reference panels of haplotypes, collections of pre-phased variants and long sequencing reads. We provide SHAPEIT4 in an open source format and demonstrate its performance in terms of accuracy and running times on two gold standard datasets: the UK Biobank data and the Genome In A Bottle.
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