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doi:10.22028/D291-28704
Titel: | Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome |
VerfasserIn: | Wenger, Aaron M. Peluso, Paul Rowell, William J. Chang, Pi-Chuan Hall, Richard J. Concepcion, Gregory T. Ebler, Jana Fungtammasan, Arkarachai Kolesnikov, Alexey Olson, Nathan D. Töpfer, Armin Alonge, Michael Mahmoud, Medhat Qian, Yufeng Chin, Chen-Shan Phillippy, Adam M. Schatz, Michael C. Myers, Gene DePristo, Mark A. Ruan, Jue Marschall, Tobias Sedlazeck, Fritz J. Zook, Justin M. Li, Heng Koren, Sergey Carroll, Andrew Rank, David R. Hunkapiller, Michael W. |
Sprache: | Englisch |
Titel: | Nature biotechnology |
Verlag/Plattform: | Nature Publishing Group |
Erscheinungsjahr: | 2019 |
Dokumenttyp: | Journalartikel / Zeitschriftenartikel |
Abstract: | The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5 kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions <50 bp (indels) and 95.99% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the 'genome in a bottle' (GIAB) benchmark set. Nearly all (99.64%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of >15 megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads. |
DOI der Erstveröffentlichung: | 10.1038/s41587-019-0217-9 |
Link zu diesem Datensatz: | hdl:20.500.11880/27707 http://dx.doi.org/10.22028/D291-28704 |
ISSN: | 1087-0156 1546-1696 |
Datum des Eintrags: | 7-Sep-2019 |
Fakultät: | MI - Fakultät für Mathematik und Informatik |
Fachrichtung: | MI - Informatik |
Professur: | MI - Prof. Dr. Tobias Marschall |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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