Scientific article
OA Policy
English

Accurate, scalable and integrative haplotype estimation

Published inNature Communications, vol. 10, no. 1, 5436
Publication date2019
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
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
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Identifiers
Journal ISSN2041-1723
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