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Benefit-of-doubt (BOD) scoring: A sequencing-based method for SNP candidate assessment from high to medium read number data sets

机译:不确定性(BOD)评分:一种基于序列的SNP候选者评估方法可从高中读取数据集

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摘要

Identification of single nucleotide polymorphisms (SNPs) is a key element in sequence-based genetic analysis. Next generation sequencing offers a cost-effective basis to generate the necessary, large sequence data sets, and bioinformatic methods are being developed to process sequencing machine readouts. We were interested in detection of SNPs in a 350 kb region of an EMS-mutagenized Arabidopsis chromosome 3. The region was selectively analyzed using PCR-generated, overlapping fragments for Solexa sequencing. The ensuing reads provided a high coverage and were processed bioinformatically. In order to assess the SNP candidates obtained with a frequently used alignment program and SNP caller, we developed an additional method that allows the identification of high confidence SNP loci. The method can easily be applied to complete genome sequence data of sufficient coverage.
机译:单核苷酸多态性(SNP)的鉴定是基于序列的遗传分析中的关键要素。下一代测序为生成必要的大型序列数据集提供了具有成本效益的基础,并且正在开发生物信息学方法来处理测序机读数。我们对在EMS诱变的拟南芥3号染色体350 kb区域中检测SNP感兴趣。使用PCR生成的重叠片段对Solexa测序进行选择性分析。随后的读物提供了很高的覆盖率,并进行了生物信息学处理。为了评估通过经常使用的比对程序和SNP调用者获得的SNP候选者,我们开发了另一种方法,该方法可以识别高可信度SNP基因座。该方法可以很容易地应用于完整的基因组序列数据的足够覆盖。

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