Reference-free prediction of rearrangement breakpoint reads
Reference-free prediction of rearrangement breakpoint reads
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DOI：
10.1093/bioinformatics/btu360
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发表时间：
2014-09-15
期刊：
影响因子：
5.8
通讯作者：
Hamada, Michiaki
中科院分区：
文献类型：
--
作者：
Wijaya, Edward;Shimizu, Kana;Hamada, Michiaki
动机：染色体重排事件由DNA分子的非典型断裂和重新连接触发，这在许多癌症相关疾病中观察到。重排的检测通常通过使用由下一代测序（NGS）生成的短读段并将读段与参考基因组的知识组合来完成。由于结构变异和基因组不同，从一个人到另一个，通过参考基因组的中间比较可能会导致lossofinformation.Results：在这篇文章中，我们提出了一个参考的方法检测集群的断点从染色体重排。这是通过直接比较一组NGS正常读段与另一组可以重新排列的读段来完成的。我们的方法SlideSort-BPR（断点读取）是基于一种快速算法，用于所有对所有短读取的比较和相邻读取数量的理论分析。当应用于测序深度为100 x的数据集时，它正确地找到了88%的断点，没有假阳性读数。此外，对真实的前列腺癌数据集的评估表明，所提出的方法比以前的方法正确预测更多的融合转录本，但产生更少的假阳性读数。据我们所知，这是第一种在不使用参考基因组的情况下检测断裂点读数的方法。
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.