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Indelign: a probabilistic framework for annotation of insertions and deletions in a multiple alignment

机译:Indelign:用于在多重比对中插入和删除的注释的概率框架

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Motivation: A quantitative study of molecular evolutionary events such as substitutions, insertions and deletions from closely related genomes requires (1) an accurate multiple sequence alignment program and (2) a method to annotate the insertions and deletions that explain the 'gaps' in the alignment. Although the former requirement has been extensively addressed, the latter problem has received little attention, especially in a comprehensive probabilistic framework.Results: Here, we present Indelign, a program that uses a probabilistic evolutionary model to compute the most likely scenario of insertions and deletions consistent with an input multiple alignment. It is also capable of modifying the given alignment so as to obtain a better agreement with the evolutionary model. We find close to optimal performance and substantial improvement over alternative methods, in tests of Indelign on synthetic data. We use Indelign to analyze regulatory sequences in Drosophila, and find an excess of insertions over deletions, which is different from what has been reported for neutral sequences.
机译:动机:定量研究分子进化事件(例如密切相关的基因组中的取代,插入和缺失)需要(1)准确的多序列比对程序和(2)注释插入和缺失的方法来解释基因组中的``缺口''对准。尽管前者的要求已得到广泛解决,但后者问题却很少受到关注,尤其是在一个综合的概率框架中。结果:在这里,我们介绍了Indelign,该程序使用概率进化模型来计算最可能的插入和删除情况与输入的多重对齐方式一致。它还能够修改给定的比对,以便与进化模型更好地达成一致。在Indelign对合成数据的测试中,我们发现最佳性能和相对其他方法的显着改进。我们使用Indelign分析果蝇中的调控序列,发现插入序列超过了缺失序列,这与已报道的中性序列有所不同。

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