Assembly of long, error-prone reads using repeat graphs

Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here,...

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Bibliographic Details
Published in	Nature biotechnology Vol. 37; no. 5; pp. 540 - 546
Main Authors	Kolmogorov, Mikhail, Yuan, Jeffrey, Lin, Yu, Pevzner, Pavel A.
Format	Journal Article
Language	English
Published	New York Nature Publishing Group US 01.05.2019 Nature Publishing Group
Subjects	631/114 631/114/2785/2302 631/1647/794 631/208/726 Agriculture Algorithms Assemblies Assembly Benchmarking Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology DNA sequencing Gene sequencing Genetic research Genome, Bacterial - genetics Genome, Human - genetics Genomes Genomics Genomics - methods Graphic methods High-Throughput Nucleotide Sequencing Human genome Humans Life Sciences Methods Molecular Sequence Annotation Repetitive Sequences, Nucleic Acid - genetics Sequence Analysis, DNA Software
Online Access	Get full text
ISSN	1087-0156 1546-1696 1546-1696
DOI	10.1038/s41587-019-0072-8

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Abstract	Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers. Flye improves the speed and accuracy of genome assembly by using repeat graphs to resolve repeat regions.
AbstractList	Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers. Flye improves the speed and accuracy of genome assembly by using repeat graphs to resolve repeat regions. Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers. Flye improves the speed and accuracy of genome assembly by using repeat graphs to resolve repeat regions. Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers. Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers.Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers.
Audience	Academic
Author	Lin, Yu Pevzner, Pavel A. Kolmogorov, Mikhail Yuan, Jeffrey
Author_xml	– sequence: 1 givenname: Mikhail orcidid: 0000-0002-5489-9045 surname: Kolmogorov fullname: Kolmogorov, Mikhail organization: Department of Computer Science and Engineering, University of California – sequence: 2 givenname: Jeffrey orcidid: 0000-0003-3855-1994 surname: Yuan fullname: Yuan, Jeffrey organization: Graduate Program in Bioinformatics and Systems Biology, University of California – sequence: 3 givenname: Yu orcidid: 0000-0001-6339-2644 surname: Lin fullname: Lin, Yu organization: Research School of Computer Science, Australian National University – sequence: 4 givenname: Pavel A. orcidid: 0000-0002-0418-165X surname: Pevzner fullname: Pevzner, Pavel A. email: ppevzner@ucsd.edu organization: Department of Computer Science and Engineering, University of California
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/30936562$$D View this record in MEDLINE/PubMed
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Snippet	Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than...
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SubjectTerms	631/114 631/114/2785/2302 631/1647/794 631/208/726 Agriculture Algorithms Assemblies Assembly Benchmarking Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology DNA sequencing Gene sequencing Genetic research Genome, Bacterial - genetics Genome, Human - genetics Genomes Genomics Genomics - methods Graphic methods High-Throughput Nucleotide Sequencing Human genome Humans Life Sciences Methods Molecular Sequence Annotation Repetitive Sequences, Nucleic Acid - genetics Sequence Analysis, DNA Software
Title	Assembly of long, error-prone reads using repeat graphs
URI	https://link.springer.com/article/10.1038/s41587-019-0072-8 https://www.ncbi.nlm.nih.gov/pubmed/30936562 https://www.proquest.com/docview/2219592839 https://www.proquest.com/docview/2202197382
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