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Integrative haplotype estimation with sub-linear complexity

By Olivier Delaneau, Jean-Fran├žois Zagury, Matthew Robinson, Jonathan Marchini, Emmanouil Dermitzakis

Posted 13 Dec 2018
bioRxiv DOI: 10.1101/493403

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 new method, SHAPEIT4, which substantially improves upon other methods to process large genotype and high coverage sequencing datasets. It notably exhibits sub-linear scaling 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 SHAPET4 in an open source format on https://odelaneau.github.io/shapeit4/ 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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