{"month":"11","intvolume":" 10","publisher":"Springer Nature","author":[{"first_name":"Olivier","full_name":"Delaneau, Olivier","last_name":"Delaneau"},{"last_name":"Zagury","full_name":"Zagury, Jean-François","first_name":"Jean-François"},{"full_name":"Robinson, Matthew Richard","first_name":"Matthew Richard","id":"E5D42276-F5DA-11E9-8E24-6303E6697425","last_name":"Robinson","orcid":"0000-0001-8982-8813"},{"full_name":"Marchini, Jonathan L.","first_name":"Jonathan L.","last_name":"Marchini"},{"full_name":"Dermitzakis, Emmanouil T.","first_name":"Emmanouil T.","last_name":"Dermitzakis"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"7710","doi":"10.1038/s41467-019-13225-y","title":"Accurate, scalable and integrative haplotype estimation","publication_identifier":{"issn":["2041-1723"]},"abstract":[{"text":"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.","lang":"eng"}],"article_number":"5436","article_processing_charge":"No","language":[{"iso":"eng"}],"oa_version":"Published Version","date_updated":"2021-01-12T08:15:01Z","volume":10,"day":"28","main_file_link":[{"url":"https://doi.org/10.1038/s41467-019-13225-y","open_access":"1"}],"date_published":"2019-11-28T00:00:00Z","oa":1,"quality_controlled":"1","article_type":"original","publication_status":"published","year":"2019","date_created":"2020-04-30T10:40:32Z","publication":"Nature Communications","extern":"1","type":"journal_article","citation":{"apa":"Delaneau, O., Zagury, J.-F., Robinson, M. R., Marchini, J. L., & Dermitzakis, E. T. (2019). Accurate, scalable and integrative haplotype estimation. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-019-13225-y","chicago":"Delaneau, Olivier, Jean-François Zagury, Matthew Richard Robinson, Jonathan L. Marchini, and Emmanouil T. Dermitzakis. “Accurate, Scalable and Integrative Haplotype Estimation.” Nature Communications. Springer Nature, 2019. https://doi.org/10.1038/s41467-019-13225-y.","short":"O. Delaneau, J.-F. Zagury, M.R. Robinson, J.L. Marchini, E.T. Dermitzakis, Nature Communications 10 (2019).","ama":"Delaneau O, Zagury J-F, Robinson MR, Marchini JL, Dermitzakis ET. Accurate, scalable and integrative haplotype estimation. Nature Communications. 2019;10. doi:10.1038/s41467-019-13225-y","mla":"Delaneau, Olivier, et al. “Accurate, Scalable and Integrative Haplotype Estimation.” Nature Communications, vol. 10, 5436, Springer Nature, 2019, doi:10.1038/s41467-019-13225-y.","ieee":"O. Delaneau, J.-F. Zagury, M. R. Robinson, J. L. Marchini, and E. T. Dermitzakis, “Accurate, scalable and integrative haplotype estimation,” Nature Communications, vol. 10. Springer Nature, 2019.","ista":"Delaneau O, Zagury J-F, Robinson MR, Marchini JL, Dermitzakis ET. 2019. Accurate, scalable and integrative haplotype estimation. Nature Communications. 10, 5436."},"status":"public"}