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Rapid and precise alignment of raw reads against redundant databases with KMA

机译:使用KMA快速准确地将原始读取与冗余数据库对齐

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摘要

BackgroundAs the cost of sequencing has declined, clinical diagnostics based on next generation sequencing (NGS) have become reality. Diagnostics based on sequencing will require rapid and precise mapping against redundant databases because some of the most important determinants, such as antimicrobial resistance and core genome multilocus sequence typing (MLST) alleles, are highly similar to one another.In order to facilitate this, a novel mapping method, KMA (k-mer alignment), was designed. KMA is able to map raw reads directly against redundant databases, it also scales well for large redundant databases. KMA uses k-mer seeding to speed up mapping and the Needleman-Wunsch algorithm to accurately align extensions from k-mer seeds. Multi-mapping reads are resolved using a novel sorting scheme (ConClave scheme), ensuring an accurate selection of templates.
机译:背景技术随着测序成本的下降,基于下一代测序(NGS)的临床诊断已成为现实。基于测序的诊断将需要针对冗余数据库进行快速,准确的定位,因为一些最重要的决定因素(例如抗微生物剂耐药性和核心基因组多基因座序列分型(MLST)等位基因)彼此高度相似。设计了一种新颖的作图方法,KMA(k-mer对齐)。 KMA能够直接将原始读取映射到冗余数据库,并且还可以很好地扩展到大型冗余数据库。 KMA使用k-mer播种加快映射速度,并使用Needleman-Wunsch算法精确对齐k-mer种子的扩展名。使用新颖的排序方案(ConClave方案)可以解决多重映射读取问题,从而确保模板的准确选择。

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