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A Sequence-Based Novel Approach for Quality Evaluation of Third-Generation Sequencing Reads

School of Information Science and Engineering, Central South University, Changsha 410083, China
Author to whom correspondence should be addressed.
Genes 2019, 10(1), 44;
Received: 29 November 2018 / Revised: 7 January 2019 / Accepted: 8 January 2019 / Published: 14 January 2019
PDF [1200 KB, uploaded 14 January 2019]


The advent of third-generation sequencing (TGS) technologies, such as the Pacific Biosciences (PacBio) and Oxford Nanopore machines, provides new possibilities for contig assembly, scaffolding, and high-performance computing in bioinformatics due to its long reads. However, the high error rate and poor quality of TGS reads provide new challenges for accurate genome assembly and long-read alignment. Efficient processing methods are in need to prioritize high-quality reads for improving the results of error correction and assembly. In this study, we proposed a novel Read Quality Evaluation and Selection Tool (REQUEST) for evaluating the quality of third-generation long reads. REQUEST generates training data of high-quality and low-quality reads which are characterized by their nucleotide combinations. A linear regression model was built to score the quality of reads. The method was tested on three datasets of different species. The results showed that the top-scored reads prioritized by REQUEST achieved higher alignment accuracies. The contig assembly results based on the top-scored reads also outperformed conventional approaches that use all reads. REQUEST is able to distinguish high-quality reads from low-quality ones without using reference genomes, making it a promising alternative sequence-quality evaluation method to alignment-based algorithms. View Full-Text
Keywords: genomics; read quality assessment; third-generation sequencing genomics; read quality assessment; third-generation sequencing

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Zhang, W.; Huang, N.; Zheng, J.; Liao, X.; Wang, J.; Li, H.-D. A Sequence-Based Novel Approach for Quality Evaluation of Third-Generation Sequencing Reads. Genes 2019, 10, 44.

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