Malhis Nawar, Butterfield Yaron S N, Ester Martin, Jones Steven J M
Genome Sciences Centre, BC Cancer Agency, Vancouver and School of Computing Science, Simon Fraser University, Burnaby, BC, Canada.
Bioinformatics. 2009 Jan 1;25(1):6-13. doi: 10.1093/bioinformatics/btn565. Epub 2008 Oct 30.
A plethora of alignment tools have been created that are designed to best fit different types of alignment conditions. While some of these are made for aligning Illumina Sequence Analyzer reads, none of these are fully utilizing its probability (prb) output. In this article, we will introduce a new alignment approach (Slider) that reduces the alignment problem space by utilizing each read base's probabilities given in the prb files.
Compared with other aligners, Slider has higher alignment accuracy and efficiency. In addition, given that Slider matches bases with probabilities other than the most probable, it significantly reduces the percentage of base mismatches. The result is that its SNP predictions are more accurate than other SNP prediction approaches used today that start from the most probable sequence, including those using base quality.
已经创建了大量的比对工具,旨在最适合不同类型的比对条件。虽然其中一些是用于比对Illumina序列分析仪读取的数据,但这些工具都没有充分利用其概率(prb)输出。在本文中,我们将介绍一种新的比对方法(Slider),该方法通过利用prb文件中给出的每个读段碱基的概率来减少比对问题空间。
与其他比对器相比,Slider具有更高的比对准确性和效率。此外,由于Slider以除最可能的概率之外的概率匹配碱基,它显著降低了碱基错配的百分比。结果是,其单核苷酸多态性(SNP)预测比目前使用的其他从最可能的序列开始的SNP预测方法更准确,包括那些使用碱基质量的方法。