Multiplex de Bruijn graphs enable genome assembly from long, high-fidelity reads
Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large k -mer sizes has remained elusive. This algorithmic challenge has become particularly pressing with the emergence of long, high-fidelity (HiFi) reads that have been re...
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| Published in | Nature biotechnology Vol. 40; no. 7; pp. 1075 - 1081 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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New York
Nature Publishing Group US
01.07.2022
Nature Publishing Group |
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| Online Access | Get full text |
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| Abstract | Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large
k
-mer sizes has remained elusive. This algorithmic challenge has become particularly pressing with the emergence of long, high-fidelity (HiFi) reads that have been recently used to generate a semi-manual telomere-to-telomere assembly of the human genome. To enable automated assemblies of long, HiFi reads, we present the La Jolla Assembler (LJA), a fast algorithm using the Bloom filter, sparse de Bruijn graphs and disjointig generation. LJA reduces the error rate in HiFi reads by three orders of magnitude, constructs the de Bruijn graph for large genomes and large
k
-mer sizes and transforms it into a multiplex de Bruijn graph with varying
k
-mer sizes. Compared to state-of-the-art assemblers, our algorithm not only achieves five-fold fewer misassemblies but also generates more contiguous assemblies. We demonstrate the utility of LJA via the automated assembly of a human genome that completely assembled six chromosomes.
A multiplex de Bruijn graph algorithm allows high-accuracy genome assembly from long, high-fidelity reads. |
|---|---|
| AbstractList | Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large k-mer sizes has remained elusive. This algorithmic challenge has become particularly pressing with the emergence of long, high-fidelity (HiFi) reads that have been recently used to generate a semi-manual telomere-to-telomere assembly of the human genome. To enable automated assemblies of long, HiFi reads, we present the La Jolla Assembler (LJA), a fast algorithm using the Bloom filter, sparse de Bruijn graphs and disjointig generation. LJA reduces the error rate in HiFi reads by three orders of magnitude, constructs the de Bruijn graph for large genomes and large k-mer sizes and transforms it into a multiplex de Bruijn graph with varying k-mer sizes. Compared to state-of-the-art assemblers, our algorithm not only achieves five-fold fewer misassemblies but also generates more contiguous assemblies. We demonstrate the utility of LJA via the automated assembly of a human genome that completely assembled six chromosomes. Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large k -mer sizes has remained elusive. This algorithmic challenge has become particularly pressing with the emergence of long, high-fidelity (HiFi) reads that have been recently used to generate a semi-manual telomere-to-telomere assembly of the human genome. To enable automated assemblies of long, HiFi reads, we present the La Jolla Assembler (LJA), a fast algorithm using the Bloom filter, sparse de Bruijn graphs and disjointig generation. LJA reduces the error rate in HiFi reads by three orders of magnitude, constructs the de Bruijn graph for large genomes and large k -mer sizes and transforms it into a multiplex de Bruijn graph with varying k -mer sizes. Compared to state-of-the-art assemblers, our algorithm not only achieves five-fold fewer misassemblies but also generates more contiguous assemblies. We demonstrate the utility of LJA via the automated assembly of a human genome that completely assembled six chromosomes. A multiplex de Bruijn graph algorithm allows high-accuracy genome assembly from long, high-fidelity reads. Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large k-mer sizes has remained elusive. This algorithmic challenge has become particularly pressing with the emergence of long, high-fidelity (HiFi) reads that have been recently used to generate a semi-manual telomere-to-telomere assembly of the human genome. To enable automated assemblies of long, HiFi reads, we present the La Jolla Assembler (LJA), a fast algorithm using the Bloom filter, sparse de Bruijn graphs and disjointig generation. LJA reduces the error rate in HiFi reads by three orders of magnitude, constructs the de Bruijn graph for large genomes and large k-mer sizes and transforms it into a multiplex de Bruijn graph with varying k-mer sizes. Compared to state-of-the-art assemblers, our algorithm not only achieves five-fold fewer misassemblies but also generates more contiguous assemblies. We demonstrate the utility of LJA via the automated assembly of a human genome that completely assembled six chromosomes.Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large k-mer sizes has remained elusive. This algorithmic challenge has become particularly pressing with the emergence of long, high-fidelity (HiFi) reads that have been recently used to generate a semi-manual telomere-to-telomere assembly of the human genome. To enable automated assemblies of long, HiFi reads, we present the La Jolla Assembler (LJA), a fast algorithm using the Bloom filter, sparse de Bruijn graphs and disjointig generation. LJA reduces the error rate in HiFi reads by three orders of magnitude, constructs the de Bruijn graph for large genomes and large k-mer sizes and transforms it into a multiplex de Bruijn graph with varying k-mer sizes. Compared to state-of-the-art assemblers, our algorithm not only achieves five-fold fewer misassemblies but also generates more contiguous assemblies. We demonstrate the utility of LJA via the automated assembly of a human genome that completely assembled six chromosomes. Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large k-mer sizes has remained elusive. This algorithmic challenge has become particularly pressing with the emergence of long, high-fidelity (HiFi) reads that have been recently used to generate a semi-manual telomere-to-telomere assembly of the human genome. To enable automated assemblies of long, HiFi reads, we present the La Jolla Assembler (LJA), a fast algorithm using the Bloom filter, sparse de Bruijn graphs and disjointig generation. LJA reduces the error rate in HiFi reads by three orders of magnitude, constructs the de Bruijn graph for large genomes and large k-mer sizes and transforms it into a multiplex de Bruijn graph with varying k-mer sizes. Compared to state-of-the-art assemblers, our algorithm not only achieves five-fold fewer misassemblies but also generates more contiguous assemblies. We demonstrate the utility of LJA via the automated assembly of a human genome that completely assembled six chromosomes.A multiplex de Bruijn graph algorithm allows high-accuracy genome assembly from long, high-fidelity reads. |
| Author | Antipov, Dmitry Pevzner, Pavel A. Kolmogorov, Mikhail Bankevich, Anton Bzikadze, Andrey V. |
| Author_xml | – sequence: 1 givenname: Anton surname: Bankevich fullname: Bankevich, Anton email: abankevich@eng.ucsd.edu organization: Department of Computer Science and Engineering, University of California, San Diego – sequence: 2 givenname: Andrey V. orcidid: 0000-0002-7928-7950 surname: Bzikadze fullname: Bzikadze, Andrey V. organization: Program in Bioinformatics and Systems Biology, University of California, San Diego – sequence: 3 givenname: Mikhail orcidid: 0000-0002-5489-9045 surname: Kolmogorov fullname: Kolmogorov, Mikhail organization: Department of Biomolecular Engineering, University of California, Santa Cruz – sequence: 4 givenname: Dmitry surname: Antipov fullname: Antipov, Dmitry organization: Center for Algorithmic Biotechnology, Institute for Translational Biomedicine, Saint Petersburg State University – sequence: 5 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, San Diego |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35228706$$D View this record in MEDLINE/PubMed |
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| Copyright | The Author(s), under exclusive licence to Springer Nature America, Inc. 2022 2022. The Author(s), under exclusive licence to Springer Nature America, Inc. The Author(s), under exclusive licence to Springer Nature America, Inc. 2022. |
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k
-mer sizes has remained... Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large k-mer sizes has remained... |
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| Title | Multiplex de Bruijn graphs enable genome assembly from long, high-fidelity reads |
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