NextPolish2: A Repeat-aware Polishing Tool for Genomes Assembled Using HiFi Long Reads

IF 11.5 2区生物学 Q1 GENETICS & HEREDITY

Genomics, Proteomics & Bioinformatics Pub Date : 2024-01-04 DOI:10.1093/gpbjnl/qzad009

Jiang Hu, Zhuo Wang, Fan Liang, Shan-Lin Liu, Kai Ye, De-Peng Wang

引用次数: 0

Abstract The high-fidelity (HiFi) long-read sequencing technology developed by PacBio has greatly improved the base-level accuracy of genome assemblies. However, these assemblies still contain base-level errors, particularly within the error-prone regions of HiFi long reads. Existing genome polishing tools usually introduce overcorrections and haplotype switch errors when correcting errors in genomes assembled from HiFi long reads. Here we describe an upgraded genome polishing tool–NextPolish2, which can fix base errors remaining in those “highly accurate” genomes assembled from HiFi long reads without introducing excessive overcorrections and haplotype switch errors. We believe that NextPolish2 has a great significance to further improve the accuracy of telomere-to-telomere (T2T) genomes. NextPolish2 is freely available at https://github.com/Nextomics/NextPolish2.

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NextPolish2：使用 HiFi 长读数组装基因组的重复感知抛光工具

摘要 PacBio 公司开发的高保真（HiFi）长读数测序技术大大提高了基因组组装的碱基精确度。然而，这些装配仍然包含碱基水平错误，尤其是在 HiFi 长读数的易错区域。现有的基因组抛光工具在纠正由 HiFi 长读数组装的基因组中的错误时，通常会引入过校正和单倍型转换错误。在这里，我们介绍一种升级版基因组抛光工具--NextPolish2，它可以修正那些由 HiFi 长读数组装的 "高精度 "基因组中残留的碱基错误，而不会引入过多的过校正和单倍型转换错误。我们相信，NextPolish2 对进一步提高端粒到端粒（T2T）基因组的准确性具有重要意义。NextPolish2 可在 https://github.com/Nextomics/NextPolish2 免费获取。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Genomics, Proteomics & Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry

CiteScore

14.30

自引率

4.20%

发文量

844

审稿时长

61 days

期刊介绍： Genomics, Proteomics and Bioinformatics (GPB) is the official journal of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. It aims to disseminate new developments in the field of omics and bioinformatics, publish high-quality discoveries quickly, and promote open access and online publication. GPB welcomes submissions in all areas of life science, biology, and biomedicine, with a focus on large data acquisition, analysis, and curation. Manuscripts covering omics and related bioinformatics topics are particularly encouraged. GPB is indexed/abstracted by PubMed/MEDLINE, PubMed Central, Scopus, BIOSIS Previews, Chemical Abstracts, CSCD, among others.