Accurate detection of complex structural variations using single-molecule sequencing

Accurate detection of complex structural variations using single-molecule sequencing

Abstract

Structural variations are the greatest source of genetic variation, but they remain poorly understood because of technological limitations. Single-molecule long-read sequencing has the potential to dramatically advance the field, although high error rates are a challenge with existing methods. Addressing this need, we introduce open-source methods for long-read alignment (NGMLR; https://github.com/philres/ngmlr) and structural variant identification (Sniffles; https://github.com/fritzsedlazeck/Sniffles) that provide unprecedented sensitivity and precision for variant detection, even in repeat-rich regions and for complex nested events that can have substantial effects on human health. In several long-read datasets, including healthy and cancerous human genomes, we discovered thousands of novel variants and categorized systematic errors in short-read approaches. NGMLR and Sniffles can automatically filter false events and operate on low-coverage data, thereby reducing the high costs that have hindered the application of long reads in clinical and research settings.

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Authors
  • Sedlazeck, Fritz J.
  • Rescheneder, Philipp
  • Smolka, Moritz
  • Fang, Han
  • Nattestad, Maria
  • von Haeseler, Arndt
  • Schatz, Michael C.
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Shortfacts
Category
Journal Paper
Divisions
Bioinformatics and Computational Biology
Journal or Publication Title
Nature Methods
ISSN
1548-7091
Publisher
Nature Publishing Group
Place of Publication
United Kingdom
Page Range
pp. 461-468
Number
6
Volume
15
Date
30 April 2018
Official URL
http://dx.doi.org/10.1038/s41592-018-0001-7
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