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Rearrangement Scenarios Guided by Chromatin Structure

机译:染色质结构引导的重排感

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Genome architecture can be drastically modified through a succession of large-scale rearrangements. In the quest to infer these rearrangement scenarios, it is often the case that the parsimony principal alone does not impose enough constraints. In this paper we make an initial effort towards computing scenarios that respect chromosome conformation, by using Hi-C data to guide our computations. We confirm the validity of a model - along with optimization problems MINIMUM LOCAL SCENARIO and MINIMUM LOCAL PARSIMONIOUS SCENARIO - developed in previous work that is based on a partition into equivalence classes of the adjacencies between syntenic blocks. To accomplish this we show that the quality of a clustering of the adjacencies based on Hi-C data is directly correlated to the quality of a rearrangement scenario that we compute between Drosophila melanogaster and Drosophila yakuba. We evaluate a simple greedy strategy to choose the next rearrangement based on Hi-C, and motivate the study of the solution space of MINIMUM LOCAL PARSIMONIOUS SCENARIO.
机译:通过连续的大规模重排可以彻底修改基因组结构。在寻求推断这些重排方案中,往往是单独的分析校长不施加足够的限制的情况。在本文中,我们通过使用Hi-C数据来指导我们的计算来指导致密染色体构象的场景进行初步努力。我们确认了模型的有效性 - 以及优化问题,最小的本地场景和最小本地解析情景 - 在以前的工作中开发,该方案基于分区进入同期块之间的邻接等级等级的等效类。要做到这一点,我们表明,基于的Hi-C数据的邻接的聚类的质量直接关系到重排的情况,我们果蝇和果蝇yakuba之间计算的质量。我们评估了一个简单的贪婪策略来选择基于Hi-C的下一个重新排列,并激励对最低局部定义情景的解决方案空间的研究。

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