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
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Genes 2019, 10(1), 44; https://doi.org/10.3390/genes10010044
Received: 29 November 2018
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Revised: 7 January 2019
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Accepted: 8 January 2019
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Published: 14 January 2019
(This article belongs to the Special Issue Selected Papers from the Third CFF Bioinformatics Conference (CBC2018))
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.
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MDPI and ACS Style
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. https://doi.org/10.3390/genes10010044
AMA Style
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(1):44. https://doi.org/10.3390/genes10010044
Chicago/Turabian StyleZhang, Wenjing, Neng Huang, Jiantao Zheng, Xingyu Liao, Jianxin Wang, and Hong-Dong Li. 2019. "A Sequence-Based Novel Approach for Quality Evaluation of Third-Generation Sequencing Reads" Genes 10, no. 1: 44. https://doi.org/10.3390/genes10010044
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