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Accurate, scalable and integrative haplotype estimation

Open access
Delaneau, Olivier, Zagury, Jean-François, Robinson, Matthew R., Marchini, Jonathan L., Dermitzakis, Emmanouil T.·2019·Nature Communications

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.

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Metadata

Authors
Delaneau, O., Zagury, J.-F., Robinson, M. R., Marchini, J. L., & Dermitzakis, E. T.
Venue
Nature Communications
Published
2019-11-28
Volume
10
Issue
1
Pages
5436-5436
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2990059271
Cited by
622
References
31
FWCI
24.11
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Accurate, scalable and integrative haplotype estimation. https://app.cochat.ai/papers/10.1038/s41467-019-13225-y
The paper
Delaneau, O., Zagury, J.-F., Robinson, M. R., Marchini, J. L., & Dermitzakis, E. T. (2019). Accurate, scalable and integrative haplotype estimation. Nature Communications. https://doi.org/10.1038/s41467-019-13225-y

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.