Application of discrete Fourier inter-coefficient difference for assessing genetic sequence similarity.

Brian R King, Maurice Aburdene, Alex Thompson, Zach Warres
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引用次数: 12

Abstract

Digital signal processing (DSP) techniques for biological sequence analysis continue to grow in popularity due to the inherent digital nature of these sequences. DSP methods have demonstrated early success for detection of coding regions in a gene. Recently, these methods are being used to establish DNA gene similarity. We present the inter-coefficient difference (ICD) transformation, a novel extension of the discrete Fourier transformation, which can be applied to any DNA sequence. The ICD method is a mathematical, alignment-free DNA comparison method that generates a genetic signature for any DNA sequence that is used to generate relative measures of similarity among DNA sequences. We demonstrate our method on a set of insulin genes obtained from an evolutionarily wide range of species, and on a set of avian influenza viral sequences, which represents a set of highly similar sequences. We compare phylogenetic trees generated using our technique against trees generated using traditional alignment techniques for similarity and demonstrate that the ICD method produces a highly accurate tree without requiring an alignment prior to establishing sequence similarity.

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离散傅立叶间系数差在基因序列相似性评估中的应用。
由于这些序列固有的数字性质,用于生物序列分析的数字信号处理(DSP)技术继续受到欢迎。DSP方法在检测基因编码区域方面已经取得了早期的成功。最近,这些方法被用于建立DNA基因相似性。我们提出了系数间差分(ICD)变换,这是离散傅里叶变换的一种新扩展,可以应用于任何DNA序列。ICD方法是一种数学的、无比对的DNA比较方法,可为任何DNA序列生成遗传标记,用于生成DNA序列之间相似性的相对度量。我们在进化范围广泛的物种中获得的一组胰岛素基因和一组禽流感病毒序列上展示了我们的方法,这些序列代表了一组高度相似的序列。我们比较了使用我们的技术生成的系统发育树与使用传统比对技术生成的树的相似性,并证明了ICD方法可以产生高度精确的树,而无需在建立序列相似性之前进行比对。
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