Overlap graph-based generation of haplotigs for diploids and polyploids

Baaijens, Jasmijn A; Schönhuth, Alexander

Overlap graph-based generation of haplotigs for diploids and polyploids

Baaijens JA, Schönhuth A (2019)
Bioinformatics 35(21): 4281-4289.

Zeitschriftenaufsatz | Veröffentlicht | Englisch

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DOI

https://doi.org/10.1093/bioinformatics/btz255

Autor*in

Baaijens, Jasmijn A; Schönhuth, Alexander^UniBi

Einrichtung

Technische Fakultät > AG Genome Data Science

Abstract / Bemerkung

Abstract Motivation Haplotype-aware genome assembly plays an important role in genetics, medicine and various other disciplines, yet generation of haplotype-resolved de novo assemblies remains a major challenge. Beyond distinguishing between errors and true sequential variants, one needs to assign the true variants to the different genome copies. Recent work has pointed out that the enormous quantities of traditional NGS read data have been greatly underexploited in terms of haplotig computation so far, which reflects that methodology for reference independent haplotig computation has not yet reached maturity. Results We present POLYploid genome fitTEr (POLYTE) as a new approach to de novo generation of haplotigs for diploid and polyploid genomes of known ploidy. Our method follows an iterative scheme where in each iteration reads or contigs are joined, based on their interplay in terms of an underlying haplotype-aware overlap graph. Along the iterations, contigs grow while preserving their haplotype identity. Benchmarking experiments on both real and simulated data demonstrate that POLYTE establishes new standards in terms of error-free reconstruction of haplotype-specific sequence. As a consequence, POLYTE outperforms state-of-the-art approaches in various relevant aspects, where advantages become particularly distinct in polyploid settings. Availability and implementation POLYTE is freely available as part of the HaploConduct package at https://github.com/HaploConduct/HaploConduct, implemented in Python and C++. Supplementary information Supplementary data are available at Bioinformatics online.

Stichworte

Statistics and Probability; Computational Theory and Mathematics; Biochemistry; Molecular Biology; Computational Mathematics; Computer Science Applications

Erscheinungsjahr

2019

Zeitschriftentitel

Bioinformatics

Band

Ausgabe

Seite(n)

4281-4289

ISSN

1367-4803

eISSN

1460-2059

Page URI

https://pub.uni-bielefeld.de/record/2941761

Zitieren

Baaijens JA, Schönhuth A. Overlap graph-based generation of haplotigs for diploids and polyploids. Bioinformatics. 2019;35(21):4281-4289.

Baaijens, J. A., & Schönhuth, A. (2019). Overlap graph-based generation of haplotigs for diploids and polyploids. Bioinformatics, 35(21), 4281-4289. doi:10.1093/bioinformatics/btz255

Baaijens, Jasmijn A, and Schönhuth, Alexander. 2019. “Overlap graph-based generation of haplotigs for diploids and polyploids”. Bioinformatics 35 (21): 4281-4289.

Baaijens, J. A., and Schönhuth, A. (2019). Overlap graph-based generation of haplotigs for diploids and polyploids. Bioinformatics 35, 4281-4289.

Baaijens, J.A., & Schönhuth, A., 2019. Overlap graph-based generation of haplotigs for diploids and polyploids. Bioinformatics, 35(21), p 4281-4289.

J.A. Baaijens and A. Schönhuth, “Overlap graph-based generation of haplotigs for diploids and polyploids”, Bioinformatics, vol. 35, 2019, pp. 4281-4289.

Baaijens, J.A., Schönhuth, A.: Overlap graph-based generation of haplotigs for diploids and polyploids. Bioinformatics. 35, 4281-4289 (2019).

Baaijens, Jasmijn A, and Schönhuth, Alexander. “Overlap graph-based generation of haplotigs for diploids and polyploids”. Bioinformatics 35.21 (2019): 4281-4289.

Daten bereitgestellt von European Bioinformatics Institute (EBI)