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Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm

机译:提高3Seq重组检测算法的算法复杂性

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摘要

Identifying recombinant sequences in an era of large genomic databases is challenging as it requires an efficient algorithm to identify candidate recombinants and parents, as well as appropriate statistical methods to correct for the large number of comparisons performed. In 2007, a computation was introduced for an exact nonparametric mosaicism statistic that gave high-precision P values for putative recombinants. This exact computation meant that multiplecomparisons corrected P values also had high precision, which is crucial when performing millions or billions of tests in large databases. Here, we introduce an improvement to the algorithmic complexity of this computation from O(mn(3)) to O(mn(2)), where m and n are the numbers of recombination-informative sites in the candidate recombinant. This new computation allows for recombination analysis to be performed in alignments with thousands of polymorphic sites. Benchmark runs are presented on viral genome sequence alignments, new features are introduced, and applications outside recombination analysis are discussed.
机译:鉴定大型基因组数据库时代中的重组序列是具有挑战性的,因为它需要一种有效的算法来识别候选重组剂和父母,以及纠正大量比较的适当统计方法。在2007年,引入了用于确切的非参数镶嵌统计学的计算,其为推定重组剂提供了高精度的P值。这种确切的计算意味着多重组合体纠正的P值也具有高精度,这在在大型数据库中执行数百万或数十亿测试时至关重要。这里,我们向O(Mn(3))至O(Mn(2))的该计算的算法复杂性提高,其中M和N是候选重组中的重组信息位点的数量。该新计算允许重组分析以与数千个多态性位点的对齐进行。基准运行呈现在病毒基因组序列比对上,介绍了新的特征,并讨论了在重组分析外的应用。

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