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A new pheromone trail-based genetic algorithm for comparative genome assembly.

机译:一种新的基于信息素踪迹的遗传算法,用于比较基因组组装。

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Gap closing is considered one of the most challenging and time-consuming tasks in bacterial genome sequencing projects, especially with the emergence of new sequencing technologies, such as pyrosequencing, which may result in large amounts of data without the benefit of large insert libraries for contig scaffolding. We propose a novel algorithm to align contigs with more than one reference genome at a time. This approach can successfully overcome the limitations of low degrees of conserved gene order for the reference and target genomes. A pheromone trail-based genetic algorithm (PGA) was used to search globally for the optimal placement for each contig. Extensive testing on simulated and real data sets shows that PGA significantly outperforms previous methods, especially when assembling genomes that are only moderately related. An extended version of PGA can predict additional candidate connections for each contig and can thus increase the likelihood of identifying the correct arrangement of each contig. The software and test data sets can be accessed at http://sourceforge.net/projects/pga4genomics/.
机译:间隙闭合被认为是细菌基因组测序项目中最具挑战性和最耗时的任务之一,尤其是随着诸如焦磷酸测序之类的新测序技术的出现,这种技术可能会导致产生大量数据,而没有用于重叠群的大型插入文库的好处。脚手架。我们提出了一种新颖的算法,一次可将重叠群与多个参考基因组比对。这种方法可以成功克服参考基因和目标基因组保守基因顺序低的局限性。基于信息素轨迹的遗传算法(PGA)用于全局搜索每个重叠群的最佳位置。在模拟和真实数据集上的大量测试表明,PGA明显优于以前的方法,尤其是在组装仅具有中等相关性的基因组时。 PGA的扩展版本可以预测每个重叠群的其他候选连接,因此可以增加识别每个重叠群正确排列的可能性。可以从http://sourceforge.net/projects/pga4genomics/访问软件和测试数据集。

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