V-pipe: a computational pipeline for assessing viral genetic diversity from high-throughput data.
V-pipe: a computational pipeline for assessing viral genetic diversity from high-throughput data.
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DOI：
10.1093/bioinformatics/btab015
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发表时间：
2021-07-19
期刊：
影响因子：
--
通讯作者：
Beerenwinkel N
中科院分区：
文献类型：
--
作者：
Posada-Céspedes S;Seifert D;Topolsky I;Jablonski KP;Metzner KJ;Beerenwinkel N
高通量测序技术不仅越来越多地用于病毒基因组学研究，而且还用于临床监测和诊断。这些技术有助于评估宿主内病毒种群的遗传多样性，从而影响病毒感染的传播、毒力和发病机制。然而，分析病毒多样性存在两个主要挑战。首先，扩增和测序错误混淆了真正生物变异的识别，其次，大数据量代表了计算限制。为了支持病毒高通量测序研究，我们开发了 V-pipe，这是一种生物信息学管道，结合了各种最先进的统计模型和计算工具，用于对原始测序读数进行自动端到端分析。 V-pipe 支持质量控制、读取映射和比对、低频突变调用以及病毒单倍型的推断。为了生成高质量的读取比对，我们开发了一种名为 ngshmmalign 的新方法，该方法基于轮廓隐藏马尔可夫模型，并针对小型且高度多样化的病毒基因组进行了定制。 V 型管道还包括基准测试功能，为不同管道配置的比较评估提供标准化环境。我们通过评估三种不同的读取对齐器（Bowtie 2、BWA MEM、ngshmmalign）和两种不同的变体调用程序（LoFreq、ShoRAH）对在宿主内病毒群体中调用单核苷酸变体的性能的影响来证明这种能力。 V 型管道支持各种管道配置，并以模块化方式实施，以方便适应不断变化的技术环境。 V-pipe 可在 https://github.com/cbg-ethz/V-pipe 免费获取。 补充数据可在生物信息学在线获取。
High-throughput sequencing technologies are used increasingly not only in viral genomics research but also in clinical surveillance and diagnostics. These technologies facilitate the assessment of the genetic diversity in intra-host virus populations, which affects transmission, virulence and pathogenesis of viral infections. However, there are two major challenges in analysing viral diversity. First, amplification and sequencing errors confound the identification of true biological variants, and second, the large data volumes represent computational limitations. To support viral high-throughput sequencing studies, we developed V-pipe, a bioinformatics pipeline combining various state-of-the-art statistical models and computational tools for automated end-to-end analyses of raw sequencing reads. V-pipe supports quality control, read mapping and alignment, low-frequency mutation calling, and inference of viral haplotypes. For generating high-quality read alignments, we developed a novel method, called ngshmmalign, based on profile hidden Markov models and tailored to small and highly diverse viral genomes. V-pipe also includes benchmarking functionality providing a standardized environment for comparative evaluations of different pipeline configurations. We demonstrate this capability by assessing the impact of three different read aligners (Bowtie 2, BWA MEM, ngshmmalign) and two different variant callers (LoFreq, ShoRAH) on the performance of calling single-nucleotide variants in intra-host virus populations. V-pipe supports various pipeline configurations and is implemented in a modular fashion to facilitate adaptations to the continuously changing technology landscape. V-pipe is freely available at https://github.com/cbg-ethz/V-pipe. Supplementary data are available at Bioinformatics online.
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