Comparing segmentations by applying randomization techniques.
Comparing segmentations by applying randomization techniques.
复制标题
通过应用随机技术比较分割。
DOI：
10.1186/1471-2105-8-171
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发表时间：
2007-05-23
影响因子：
3
通讯作者：
Terzi, Evimaria
中科院分区：
文献类型：
--
作者：
Haiminen, Niina;Mannila, Heikki;Terzi, Evimaria
基因组序列的分割技术有很多，也可以基于多种不同的生物特征进行分割。我们展示了如何评估和比较通过不同的技术和不同的生物特征获得的分割质量。我们应用随机化技术来评估给定分割的质量。我们的示例应用包括等长检测和编码-非编码结构的发现。我们通过应用不同的技术获得相关序列的分割，并使用替代特征对其进行分割。我们发现有些分割结果与真实的分割结果非常相似，而且这种相似性在统计上是显著的。对于其他一些分段，我们表明同样好的结果可能会偶然出现。我们介绍了一个评估分割质量的框架，并在两个片段基因组结构的例子中演示了它的使用。我们将质量评价的过程从简单地查看分割，转变为获得表示分割相似度重要性的p值。
There exist many segmentation techniques for genomic sequences, and the segmentations can also be based on many different biological features. We show how to evaluate and compare the quality of segmentations obtained by different techniques and alternative biological features. We apply randomization techniques for evaluating the quality of a given segmentation. Our example applications include isochore detection and the discovery of coding-noncoding structure. We obtain segmentations of relevant sequences by applying different techniques, and use alternative features to segment on. We show that some of the obtained segmentations are very similar to the underlying true segmentations, and this similarity is statistically significant. For some other segmentations, we show that equally good results are likely to appear by chance. We introduce a framework for evaluating segmentation quality, and demonstrate its use on two examples of segmental genomic structures. We transform the process of quality evaluation from simply viewing the segmentations, to obtaining p-values denoting significance of segmentation similarity.