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KPop: Accurate, Assembly-Free, and Scalable Comparative Analysis of Microbial Genomes

biorxiv(2022)

School of Life Sciences and Department of Statistics | Biomathematics and Statistics Scotland

Cited 0|Views16
Abstract
The recent explosion in the amount of available sequencing data challenges existing analysis techniques. Here we introduce KPop, a novel versatile method based on full k -mer spectra and dataset-specific transformations, through which thousands of assembled or unassembled microbial genomes can be quickly compared. Unlike minimizer-based methods that produce distances and have lower resolution, KPop is able to accurately map sequences onto a low-dimensional space. Extensive validation on simulated and real-life viral and bacterial datasets shows that KPop can correctly separate sequences at both species and sub-species levels even when the overall genomic diversity is low. KPop also rapidly identifies related sequences and systematically outperforms minimizer-based methods. KPop’s code is open-source and available on GitHub at . ### Competing Interest Statement The authors have declared no competing interest.
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要点】:本文介绍了KPop,一种基于完整k-mer谱和特定数据集变换的微生物基因组比较新方法,具有准确性、无需组装和可扩展性的特点,能够在种和亚种水平上准确区分序列。

方法】:KPop利用全k-mer谱和针对数据集特定的变换,将成千上万的组装或未组装的微生物基因组快速映射到低维空间。

实验】:通过在模拟和真实病毒和细菌数据集上进行的大量验证,KPop能够正确区分种和亚种水平的序列,即使在整体基因组多样性较低的情况下也能表现出色。KPop的代码是开源的,可在GitHub上获取。