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ACCUSA-accurate SNP calling on draft genomes

机译:ACCUSA准确的SNP呼吁基因组草案

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摘要

Next generation sequencing technologies facilitate genome-wide analysis of several biological processes. We are interested in whole-genome genotyping. To our knowledge, none of the existing single nucleotide polymorphism (SNP) callers consider the quality of the reference genome, which is not necessary for highquality assemblies of well-studied model organisms. However, most genome projects will remain in draft status with little to no genome assembly improvement due to time and financial constraints. Here, we present a simple yet elegant solution ('ACCUSA') that considers both the read qualities as well as the reference genome's quality using a Bayesian framework. We demonstrate that ACCUSA is as good as the current SNP calling software in detecting true SNPs. More importantly, ACCUSA does not call spurious SNPs, which originate from a poor reference sequence.
机译:下一代测序技术促进了多种生物学过程的全基因组分析。我们对全基因组基因分型感兴趣。据我们所知,现有的单核苷酸多态性(SNP)调用者均未考虑参考基因组的质量,这对于经过充分研究的模型生物的高质量装配而言不是必需的。但是,由于时间和资金的限制,大多数基因组项目仍将处于草稿状态,而基因组组装几乎没有改善。在这里,我们提出一个简单而优雅的解决方案('ACCUSA'),该解决方案使用贝叶斯框架同时考虑了读取质量和参考基因组质量。我们证明了ACCUSA在检测真实SNP方面与当前的SNP调用软件一样好。更重要的是,ACCUSA不会调用虚假的SNP,这些SNP源自不良的参考序列。

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