TopoQual polishes circular consensus sequencing data and accurately predicts quality scores.

IF 2.9 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Minindu Weerakoon, Sangjin Lee, Emily Mitchell, Haynes Heaton
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引用次数: 0

Abstract

Background: Pacific Biosciences (PacBio) circular consensus sequencing (CCS), also known as high fidelity (HiFi) technology, has revolutionized modern genomics by producing long (10 + kb) and highly accurate reads. This is achieved by sequencing circularized DNA molecules multiple times and combining them into a consensus sequence. Currently, the accuracy and quality value estimation provided by HiFi technology are more than sufficient for applications such as genome assembly and germline variant calling. However, there are limitations in the accuracy of the estimated quality scores when it comes to somatic variant calling on single reads.

Results: To address the challenge of inaccurate quality scores for somatic variant calling, we introduce TopoQual, a novel tool designed to enhance the accuracy of base quality predictions. TopoQual leverages techniques including partial order alignments (POA), topologically parallel bases, and deep learning algorithms to polish consensus sequences. Our results demonstrate that TopoQual corrects approximately 31.9% of errors in PacBio consensus sequences. Additionally, it validates base qualities up to q59, which corresponds to one error in 0.9 million bases. These improvements will significantly enhance the reliability of somatic variant calling using HiFi data.

Conclusion: TopoQual represents a significant advancement in genomics by improving the accuracy of base quality predictions for PacBio HiFi sequencing data. By correcting a substantial proportion of errors and achieving high base quality validation, TopoQual enables confident and accurate somatic variant calling. This tool not only addresses a critical limitation of current HiFi technology but also opens new possibilities for precise genomic analysis in various research and clinical applications.

TopoQual抛光循环共识测序数据,并准确预测质量分数。
背景:太平洋生物科学公司(PacBio)循环共识测序(CCS),也被称为高保真度(HiFi)技术,通过产生长(10 + kb)和高度精确的读取,彻底改变了现代基因组学。这是通过对环状DNA分子进行多次测序并将它们组合成一个一致的序列来实现的。目前,HiFi技术提供的精度和质量值估计对于基因组组装和种系变异召唤等应用已经绰绰绰用。然而,当涉及到单个读取的体细胞变异呼叫时,估计质量分数的准确性存在局限性。结果:为了解决体细胞变异呼叫质量评分不准确的挑战,我们引入了TopoQual,一个旨在提高基础质量预测准确性的新工具。TopoQual利用包括偏序对齐(POA)、拓扑并行碱基和深度学习算法在内的技术来优化共识序列。我们的研究结果表明,TopoQual纠正了PacBio共识序列中大约31.9%的错误。此外,它验证了高达q59的碱基质量,这相当于90万个碱基中的一个错误。这些改进将显著提高使用HiFi数据进行体细胞变异呼叫的可靠性。结论:TopoQual通过提高PacBio HiFi测序数据的碱基质量预测的准确性,代表了基因组学的重大进步。通过纠正相当大比例的错误并实现高基础质量验证,TopoQual使自信和准确的体细胞变异呼叫成为可能。该工具不仅解决了当前HiFi技术的一个关键限制,而且为各种研究和临床应用中的精确基因组分析开辟了新的可能性。
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
BMC Bioinformatics
BMC Bioinformatics 生物-生化研究方法
CiteScore
5.70
自引率
3.30%
发文量
506
审稿时长
4.3 months
期刊介绍: BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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