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Alignment-free genomic sequence comparison using FCGR and signal processing

机译:使用FCGR和信号处理的无序基因组序列比较

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BACKGROUND:Alignment-free methods of genomic comparison offer the possibility of scaling to large data sets of nucleotide sequences comprised of several thousand or more base pairs. Such methods can be used for purposes of deducing "nearby" species in a reference data set, or for constructing phylogenetic trees.RESULTS:We describe one such method that gives quite strong results. We use the Frequency Chaos Game Representation (FCGR) to create images from such sequences, We then reduce dimension, first using a Fourier trig transform, followed by a Singular Values Decomposition (SVD). This gives vectors of modest length. These in turn are used for fast sequence lookup, construction of phylogenetic trees, and classification of virus genomic data. We illustrate the accuracy and scalability of this approach on several benchmark test sets.CONCLUSIONS:The tandem of FCGR and dimension reductions using Fourier-type transforms and SVD provides a powerful approach for alignment-free genomic comparison. Results compare favorably and often surpass best results reported in prior literature. Good scalability is also observed.
机译:背景:无转基因比较方法的基因组比较方法提供了缩放到由几千或更多碱基对组成的核苷酸序列的大数据集的可能性。这些方法可用于在参考数据集中推导“附近”物种,或用于构建系统发育树质。结果:我们描述了一种提供了一个赋予了相当强烈的结果的方法。我们使用频率混沌游戏表示(FCGR)来创建来自此类序列的图像,然后我们减少维度,首先使用傅里叶触发变换,然后是单数值分解(SVD)。这给出了适度长度的载体。这些反过来用于快速序列查找,系统发育树木的构建以及病毒基因组数据的分类。我们说明了这种方法在几个基准测试集中的准确性和可扩展性。结论:使用傅立叶型变换和SVD的FCGR和尺寸减少的串联提供了一种有关的对齐基因组比较的强大方法。结果比较有利,经常超越现有文学中报告的最佳结果。还观察到良好的可扩展性。

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