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Haplotype threading: accurate polyploid phasing from long reads

Authors
  • Schrinner, Sven D.1
  • Mari, Rebecca Serra2, 3, 4
  • Ebler, Jana2
  • Rautiainen, Mikko5, 3, 4
  • Seillier, Lancelot6
  • Reimer, Julia J.6
  • Usadel, Björn7, 6, 8
  • Marschall, Tobias2
  • Klau, Gunnar W.1, 8
  • 1 Algorithmic Bioinformatics, Heinrich Heine University Düsseldorf, Universitätsstr. 1, Düsseldorf, 40225, Germany , Düsseldorf (Germany)
  • 2 Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraße 5, Düsseldorf, 40225, Germany , Düsseldorf (Germany)
  • 3 Center for Bioinformatics, Saarland University, Saarland Informatics Campus E2.1, Saarbrücken, 66123, Germany , Saarbrücken (Germany)
  • 4 Graduate School of Computer Science, Saarland Informatics Campus E1.3, Saarbrücken, 66123, Germany , Saarbrücken (Germany)
  • 5 Max Planck Institute for Informatics, Saarbrücken, 66123, Germany , Saarbrücken (Germany)
  • 6 Institute for Biology I, RWTH Aachen, Worringer Weg 3, Aachen, 52074, Germany , Aachen (Germany)
  • 7 Forschungszentrum Jülich IBG-4, Wilhelm-Johnen-Str., Jülich, 52428, Germany , Jülich (Germany)
  • 8 Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich Heine University Düsseldorf, Universitätsstr. 1, Düsseldorf, 40225, Germany , Düsseldorf (Germany)
Type
Published Article
Publication Date
Sep 21, 2020
Volume
21
Issue
1
Identifiers
DOI: 10.1186/s13059-020-02158-1
Source
Springer Nature
Keywords
License
Green

Abstract

Resolving genomes at haplotype level is crucial for understanding the evolutionary history of polyploid species and for designing advanced breeding strategies. Polyploid phasing still presents considerable challenges, especially in regions of collapsing haplotypes.We present WhatsHap polyphase, a novel two-stage approach that addresses these challenges by (i) clustering reads and (ii) threading the haplotypes through the clusters. Our method outperforms the state-of-the-art in terms of phasing quality. Using a real tetraploid potato dataset, we demonstrate how to assemble local genomic regions of interest at the haplotype level. Our algorithm is implemented as part of the widely used open source tool WhatsHap.

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