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Genome Biol. 2019 Nov 20;20(1):246. doi: 10.1186/s13059-019-1828-7.

Structural variant calling: the long and the short of it.

Author information

1
Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.
2
Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
3
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
4
Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
5
University Center for Primary Care and Public Health, Lausanne, Switzerland.
6
Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland. Christophe.Dessimoz@unil.ch.
7
Swiss Institute of Bioinformatics, Lausanne, Switzerland. Christophe.Dessimoz@unil.ch.
8
Department of Computational Biology, University of Lausanne, Lausanne, Switzerland. Christophe.Dessimoz@unil.ch.
9
Centre for Life's Origins and Evolution, Department of Genetics, Evolution & Environment, University College London, London, UK. Christophe.Dessimoz@unil.ch.
10
Department of Computer Science, University College London, London, UK. Christophe.Dessimoz@unil.ch.
11
Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA. fritz.sedlazeck@bcm.edu.

Abstract

Recent research into structural variants (SVs) has established their importance to medicine and molecular biology, elucidating their role in various diseases, regulation of gene expression, ethnic diversity, and large-scale chromosome evolution-giving rise to the differences within populations and among species. Nevertheless, characterizing SVs and determining the optimal approach for a given experimental design remains a computational and scientific challenge. Multiple approaches have emerged to target various SV classes, zygosities, and size ranges. Here, we review these approaches with respect to their ability to infer SVs across the full spectrum of large, complex variations and present computational methods for each approach.

KEYWORDS:

De novo assembly; Gene fusion; Hybrid; Long-read; Mapping; RNA-Seq; Short-read; Structural variant (SV) detection

PMID:
31747936
DOI:
10.1186/s13059-019-1828-7
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