Exploration of multivariate analysis in microbial coding sequence modeling
Exploration of multivariate analysis in microbial coding sequence modeling
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DOI：
10.1186/1471-2105-13-97
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发表时间：
2012-05-14
影响因子：
3
通讯作者：
Snipen, Lars
中科院分区：
文献类型：
--
作者：
Mehmood, Tahir;Bohlin, Jon;Snipen, Lars
背景：基因发现是一个复杂的过程，其中包含编码序列建模、启动子区域识别、重叠基因问题等的算法。在本研究中，我们重点关注编码序列建模算法；也就是说，从基因组 DNA 中识别和预测实际编码序列的算法。在这方面，我们推广了一种称为规范幂偏最小二乘法 (CPPLS) 的新型多元方法，作为常用插值马尔可夫模型 (IMM) 的替代方法。对取自具有不同基因组特性的多个物种的高度保守基因的 DNA、密码子和蛋白质序列进行了这些方法之间的比较。结果：在同一组序列上，多元 CPPLS 方法对编码序列的分类明显优于常用的 IMM。我们还发现，使用具有密码子表示的 CPPLS 比使用蛋白质 (p < 0.001) 和 DNA (p < 0.001) 的 IMM 具有更好的分类结果。此外，尽管平均性能相似，但 CPPLS 密码子表示性能的变化明显小于 IMM (p < 0.001)。结论：通过使用基于应用于密码子或 DNA 频率的多元 CPPLS 方法的算法，可以显着提高编码序列建模的性能。
Background: Gene finding is a complicated procedure that encapsulates algorithms for coding sequence modeling, identification of promoter regions, issues concerning overlapping genes and more. In the present study we focus on coding sequence modeling algorithms; that is, algorithms for identification and prediction of the actual coding sequences from genomic DNA. In this respect, we promote a novel multivariate method known as Canonical Powered Partial Least Squares (CPPLS) as an alternative to the commonly used Interpolated Markov model (IMM). Comparisons between the methods were performed on DNA, codon and protein sequences with highly conserved genes taken from several species with different genomic properties.Results: The multivariate CPPLS approach classified coding sequence substantially better than the commonly used IMM on the same set of sequences. We also found that the use of CPPLS with codon representation gave significantly better classification results than both IMM with protein (p < 0.001) and with DNA (p < 0.001). Further, although the mean performance was similar, the variation of CPPLS performance on codon representation was significantly smaller than for IMM (p < 0.001).Conclusions: The performance of coding sequence modeling can be substantially improved by using an algorithm based on the multivariate CPPLS method applied to codon or DNA frequencies.