@article{7710, abstract = {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.}, author = {Delaneau, Olivier and Zagury, Jean-François and Robinson, Matthew Richard and Marchini, Jonathan L. and Dermitzakis, Emmanouil T.}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Accurate, scalable and integrative haplotype estimation}}, doi = {10.1038/s41467-019-13225-y}, volume = {10}, year = {2019}, }