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Scientific Article
unige:144668 
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Accurate, scalable and integrative haplotype estimation |
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| Authors | ||
| Published in | Nature communications. 2019, vol. 10, no. 1, 5436 | |
| 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. | |
| Keywords | Biological Specimen Banks — Data Interpretation — Statistical — Datasets as Topic — Genotype — Haplotypes — High-Throughput Nucleotide Sequencing — Humans — Polymorphism — Single Nucleotide — Sample Size — Sequence Analysis — DNA — Software | |
| Identifiers | PMID: 31780650 | |
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| Research group | Population Genomics and Genetics of Complex Traits (892) | |
| Citation (ISO format) | DELANEAU, Olivier et al. Accurate, scalable and integrative haplotype estimation. In: Nature Communications, 2019, vol. 10, n° 1, p. 5436. doi: 10.1038/s41467-019-13225-y https://archive-ouverte.unige.ch/unige:144668 |
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