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Combinatorial analysis and algorithms for quasispecies reconstruction using next-generation sequencing

机译:使用下一代测序的准物种重建的组合分析和算法

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BackgroundNext-generation sequencing (NGS) offers a unique opportunity for high-throughput genomics and has potential to replace Sanger sequencing in many fields, including de-novo sequencing, re-sequencing, meta-genomics, and characterisation of infectious pathogens, such as viral quasispecies. Although methodologies and software for whole genome assembly and genome variation analysis have been developed and refined for NGS data, reconstructing a viral quasispecies using NGS data remains a challenge. This application would be useful for analysing intra-host evolutionary pathways in relation to immune responses and antiretroviral therapy exposures. Here we introduce a set of formulae for the combinatorial analysis of a quasispecies, given a NGS re-sequencing experiment and an algorithm for quasispecies reconstruction. We require that sequenced fragments are aligned against a reference genome, and that the reference genome is partitioned into a set of sliding windows (amplicons). The reconstruction algorithm is based on combinations of multinomial distributions and is designed to minimise the reconstruction of false variants, called in-silico recombinants.
机译:背景技术下一代测序(NGS)为高通量基因组学提供了独特的机会,并有潜力在许多领域取代Sanger测序,包括从头测序,重新测序,元基因组学和感染性病原体(如病毒)的表征准种。尽管已经为NGS数据开发并完善了用于全基因组组装和基因组变异分析的方法和软件,但是使用NGS数据重建病毒准种仍然是一个挑战。该应用对于分析与免疫反应和抗逆转录病毒疗法暴露有关的宿主内进化途径将是有用的。在这里,我们介绍了一组用于准物种的组合分析的公式,给出了NGS重测序实验和用于准物种重建的算法。我们要求已测序的片段与参考基因组比对,并且参考基因组被划分为一组滑动窗口(扩增子)。重建算法基于多项式分布的组合,旨在将假变异(称为计算机重组)的重建减至最少。

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