Abstract
Nanopore sequencing has been widely used for the reconstruction of microbial genomes. Owing to higher error rates, errors on the genome are corrected via neural networks trained by Nanopore reads. However, the systematic errors usually remain uncorrected. This paper designs a model that is trained by homologous sequences for the correction of Nanopore systematic errors. The developed program, Homopolish, outperforms Medaka and HELEN in bacteria, viruses, fungi, and metagenomic datasets. When combined with Medaka/HELEN, the genome quality can exceed Q50 on R9.4 flow cells. We show that Nanopore-only sequencing can produce high-quality microbial genomes sufficient for downstream analysis.
Highlights
Third-generation long-read sequencing is an essential technology for the reconstruction of complete genomes in many species within the biosphere
This paper develops a novel polishing tool, which is based upon a support vector machine (SVM) trained for distinguishing between sequencing errors and strain variations using homologous sequences
Homopolish is based on an SVM trained for distinguishing Nanopore systematic errors from interstrain variations according to the degree of conservation among homologs
Summary
Third-generation long-read sequencing is an essential technology for the reconstruction of complete genomes in many species within the biosphere. Oxford Nanopore Technology (ONT) is one of the major providers in third-generation sequencing, which is being used for the telomere-to-telomere reconstruction of the human genome [1, 2]. The ultra-long reads of ONT have demonstrated their power in assembly contiguity through large and complex repeat regions, their assembly accuracy (∼ 85–92%) has been criticized when compared with Illumina or PacBio High-Fidelity (HiFi) sequencing (∼ 99%), owing to the omission of important protein-coding genes [3]. Hybrid Illumina/Nanopore sequencing and assembly are required for producing a high-quality genome which possesses both satisfactory contiguity and accuracy [4].
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