Segmentation algorithm for DNA sequences
Segmentation algorithm for DNA sequences
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DOI：
10.1103/physreve.72.041917
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发表时间：
2005-10-01
影响因子：
2.4
通讯作者：
Zhang, R
中科院分区：
文献类型：
--
作者：
Zhang, CT;Gao, F;Zhang, R
提出了一种新的衡量方法，用于量化两个概率分布之间的差异，称为二次散度。基于二次散度，提出了一种新的分割算法，将给定的基因组或 DNA 序列划分为组成不同的域。新算法已应用于人类24条染色体序列的分割，并获得了每条染色体的等容线边界。与基于Jensen-Shannon散度的熵分割算法得到的结果相比，两种算法得到的分割点坐标全部相同。给出了两种分割算法的等效性的解释。新算法有许多优点。特别是，它比基于熵的方法更简单、更快。因此，新算法更适合分析长基因组序列，例如人类和其他新测序的真核生物基因组序列。
A new measure, to quantify the difference between two probability distributions, called the quadratic divergence, has been proposed. Based on the quadratic divergence, a new segmentation algorithm to partition a given genome or DNA sequence into compositionally distinct domains is put forward. The new algorithm has been applied to segment the 24 human chromosome sequences, and the boundaries of isochores for each chromosome were obtained. Compared with the results obtained by using the entropic segmentation algorithm based on the Jensen-Shannon divergence, both algorithms resulted in all identical coordinates of segmentation points. An explanation of the equivalence of the two segmentation algorithms is presented. The new algorithm has a number of advantages. Particularly, it is much simpler and faster than the entropy-based method. Therefore, the new algorithm is more suitable for analyzing long genome sequences, such as human and other newly sequenced eukaryotic genome sequences.