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Reference-free prediction of rearrangement breakpoint reads

机译:重排断点读取的无参考预测

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Motivation: Chromosome rearrangement events are triggered by atypical breaking and rejoining of DNA molecules, which are observed in many cancer-related diseases. The detection of rearrangement is typically done by using short reads generated by next-generation sequencing (NGS) and combining the reads with knowledge of a reference genome. Because structural variations and genomes differ from one person to another, intermediate comparison via a reference genome may lead to loss of information. Results: In this article, we propose a reference-free method for detecting clusters of breakpoints from the chromosomal rearrangements. This is done by directly comparing a set of NGS normal reads with another set that may be rearranged. Our method SlideSort-BPR (breakpoint reads) is based on a fast algorithm for all-against-all comparisons of short reads and theoretical analyses of the number of neighboring reads. When applied to a dataset with a sequencing depth of 100x, it finds similar to 88% of the breakpoints correctly with no false-positive reads. Moreover, evaluation on a real prostate cancer dataset shows that the proposed method predicts more fusion transcripts correctly than previous approaches, and yet produces fewer false-positive reads. To our knowledge, this is the first method to detect breakpoint reads without using a reference genome.
机译:动机:染色体重排事件是由非典型的DNA分子断裂和重新结合触发的,在许多与癌症相关的疾病中都观察到这种现象。重排的检测通常是通过使用下一代测序(NGS)生成的短读本,并将这些读本与参考基因组的知识相结合来完成的。由于每个人的结构变异和基因组不同,因此通过参考基因组进行中间比较可能会导致信息丢失。结果:在本文中,我们提出了一种从染色体重排中检测断点簇的无参考方法。这是通过直接将一组NGS正常读数与可能重新排列的另一组读数进行比较来完成的。我们的方法SlideSort-BPR(断点读取)基于一种快速算法,可对短读取进行全部-所有比较,并对相邻读取的数量进行理论分析。当将其应用于测序深度为100倍的数据集时,它可以正确地找到约88%的断点,而不会出现假阳性读数。此外,对真实前列腺癌数据集的评估表明,与以前的方法相比,所提出的方法可正确预测更多的融合转录本,而产生的假阳性读数则更少。据我们所知,这是无需参考基因组即可检测断点读数的第一种方法。

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