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Multidimensional Scaling Applied to Histogram-Based DNA Analysis

机译:多维缩放应用于基于直方图的DNA分析

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This paper aims to study the relationships between chromosomal DNA sequences of twenty species. We propose a methodology combining DNA-based word frequency histograms, correlation methods, and an MDS technique to visualize structural information underlying chromosomes (CRs) and species. Four statistical measures are tested (Minkowski, Cosine, Pearson product-moment, and Kendallτrank correlations) to analyze the information content of 421 nuclear CRs from twenty species. The proposed methodology is built on mathematical tools and allows the analysis and visualization of very large amounts of stream data, like DNA sequences, with almost no assumptions other than the predefined DNA “word length.” This methodology is able to produce comprehensible three-dimensional visualizations of CR clustering and related spatial and structural patterns. The results of the four test correlation scenarios show that the high-level information clusterings produced by the MDS tool are qualitatively similar, with small variations due to each correlation method characteristics, and that the clusterings are a consequence of the input data and not method’s artifacts.
机译:本文旨在研究二十种染色体DNA序列之间的关系。我们提出了一种结合基于DNA的词频直方图,相关方法和MDS技术的方法,以可视化染色体(CR)和物种的结构信息。测试了四个统计量度(Minkowski,余弦,Pearson积矩和Kendallτrank相关性)以分析来自二十个物种的421个核CR的信息含量。所提出的方法是建立在数学工具的基础上的,它允许对非常大的流数据(如DNA序列)进行分析和可视化,而除了预定义的DNA“字长”之外几乎没有其他假设。这种方法能够对CR聚类以及相关的空间和结构模式产生可理解的三维可视化效果。四个测试关联方案的结果表明,MDS工具生成的高级信息聚类在质量上相似,并且由于每个关联方法的特性而有很小的差异,并且聚类是输入数据的结果,而不是方法的伪像。 。

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