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序列匹配的适配器剪切器为RNA病毒的Illumina测序生成一致的质量和组装指标

Grace Nabakooza^1,2, Darlene D Wagner³, Nehalraza Momin³

¹Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee, United States, assigned to Centers for Disease Control and Prevention, Atlanta, GA, USA. sxv8@cdc.gov.

BMC research notes

|October 14, 2024

概括

适配器修剪对于下一代测序 (NGS) 分析至关重要. 在病毒数据集中,Trimmomatic和AdapterRemoval显示一致的性能,指导病毒基因组分析的最佳软件选择.

科学领域:

基因组学就是基因组学.
生物信息学是一种生物信息学.
计算生物学计算生物学

背景情况:

下一代测序 (NGS) 数据中的适配器序列和低质量的基因可以阻碍下游基因组分析.
有效的数据预处理对于准确的病毒基因组组装和变异调用至关重要.

研究的目的:

为了评估六个适配器修剪程序的性能,实施了五种不同的算法.
评估修剪对病毒数据集的读取质量,结合组合和单核酸多态性 (SNP) 分析的影响.
为了指导病毒基因组研究的最佳修剪工具的选择.

主要方法:

对六个修剪软件包进行比较分析:Trimmomatic,BBDuk,FastP,AdapterRemoval,SeqPurge和Skewer. 这些软件包包括:
这些剪切器应用于对结的Illumina iSeq和MiSeq测序数据,这些数据来自脊髓灰质炎病毒,SARS-CoV-2和诺罗病毒.
评估指标包括适配器移除效率,读取质量改进,连接组装指标 (长度,覆盖范围),SNP质量和一致性.

主要成果:

在所有测试的病毒数据集中,Trimmomatic和BBDuk展示了优越的适配器移除效率.
所有测试的剪切器都成功提高了读数质量 (Q≥30),Trimmomatic,AdapterRemoval和FastP保留了最高质量的读数.
虽然所有修剪器都改善了病毒基因组组装指标,但BBDuk修剪的读数导致了最短的结合.
在所有修剪器 (>97.7%) 中,SNP一致性仍然很高,但BBDuk产生了最低质量的SNP.

结论:

使用传统序列匹配算法 (Trimmomatic,AdapterRemoval) 的修剪程序在病毒基因组分析中表现一致.
修剪软件的选择对下游分析有很大的影响,特别是在紧密组装和SNP质量方面.
研究结果为选择合适的修剪工具提供了关键的见解,并为未来的病毒基因组学多功能生物信息软件的开发提供了信息.

关键词:

适配器修剪适配器修剪在新的组装 De novo.这就是Illumina Illumina.这是下一代测序.质量控制质量控制 RNA病毒的RNA病毒

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