PT  - JOURNAL ARTICLE
AU  - Olivier Delaneau
AU  - Jean-François Zagury
AU  - Matthew Robinson
AU  - Jonathan Marchini
AU  - Emmanouil Dermitzakis
TI  - Integrative haplotype estimation with sub-linear complexity
AID  - 10.1101/493403
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 493403
4099  - http://biorxiv.org/content/early/2018/12/13/493403.short
4100  - http://biorxiv.org/content/early/2018/12/13/493403.full
AB  - 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.