利用最大评分子序列和gpu对两两全基因组序列比对进行高分片段选择

Abdulrhman Aljouie, Ling Zhong, Usman Roshan
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引用次数: 2

摘要

全基因组比对程序使用带有散列表的字符串匹配来识别查询和目标序列之间的高分片段,然后围绕这些片段构建完整的比对。最近一项比较比对程序的研究表明,虽然进化上相似的基因组很容易比对,但不同的基因组仍然对现有方法构成挑战。为了填补这一空白,我们探索使用最大得分子序列来识别高分片段。我们将查询基因组分成几个片段,并使用先前发表的短读比对并行算法将它们与目标对齐。然后,我们将这些高分片段传递给LASTZ程序,以获得更完整的比对。在模拟数据上,我们获得了比LASTZ给出的校准平均至少高出20%的精度,但代价是增加几个小时的运行时间。我们的源代码可以在http://web.njit.edu/usman/MSGA上免费获得
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High scoring segment selection for pairwise whole genome sequence alignment with the maximum scoring subsequence and GPUs
Whole genome alignment programs use string matching with hash tables to identify high scoring fragments between a query and target sequence around which a full alignment is then built. A recent study comparing alignment programs showed that while evolutionary similar genomes were easy to align, divergent genomes still posed a challenge to existing methods. To fill this gap we explore the use of the maximum scoring subsequence to identify high scoring fragments. We split the query genome into several fragments and align them to the target with a previously published parallel algorithm for short read alignment. We then pass such high scoring fragments on to the LASTZ program to obtain a more complete alignment. On simulated data we obtain an average of at least 20% higher accuracy than the alignment given by LASTZ at the expense of few hours of additional runtime. Our source code is freely available at http://web.njit.edu/usman/MSGA
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